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Big Data: Spotify

Group 6

by: Buse Dikici, Jai Khanna, Jasmin Stallzus, Noah Wolford

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Spotify is one of the most known and used music streaming services in the world. Starting in 2008, it has now over 100 million active users including 30 million users that are paying for it. Spotify has over 20 million songs and everyday over 20.000 new songs are added to the database. Big data helps Spotify to use techniques and tools to improve the wishes of their users and propose recommendations. Without Big data Spotify would never have been popular as it is used nowadays around the globe. The key activities of Spotify is to maintain the platform because it is the only way of connecting with the customers. Any distribution of the service would result in customer loss, which would damage the company itself.

Background:

Spotify is a music streaming service which was launched in 2008 by Daniel EK and Martin Lorentzon in Sweden. It allows users to either stream music for free or stream music through a paid premium account. Premium account users do not have any advertisements and can even listen to music while offline. These streaming services can be used on a personal computer (PC) as well as on a mobile phone/device. Spotify is currently the “best option available for an on-demand streaming music service” (Hayes, 2016) due to its free access and user friendliness. Furthermore, Spotify is available in more than 60 countries globally. Nevertheless, Spotify also experienced some setbacks for instance, in 2009 “Spotify announced that there had been a security flaw in the Spotify service” (Casinos, 2011), that caused private user information to be potentially exposed. Additionally, some artists are being critical towards Spotify because they perceive that the compensation they receive for their music is low. Consequently some artists like Taylor Swift do not want their music on Spotify.

Key Resources and Channels:

Spotify, at its heart, has a massive and growing data set. The data they collect is mostly user-centric. For example, they can use information about a user’s activity and personal background like the location, what artists they listen to and like based on the Facebook profiles of most Spotify users, at what time of the day and what their friends listen to,etc. These information are used to generate recommendations, an understanding of tastes and preferences of users and groups which enables the service to develop playlists based on a user’s preference. This is where Big Data comes into the picture. It creates a service that feels personal for millions of people and analyses each and every one of those people. At the same time, by having such a large collection of music, Spotify can provide interesting analytics of music. For example, if a user wants to listen to a specific kind of genre or type of music, Spotify uses interesting algorithms and machine learning techniques to find the right kind of music for that person. Just to give an idea, in total, Spotify has over 28 petabytes of storage spread over four global data centres and collects about 4 terabytes of user data every day.

4Vs of Spotify’s Big Data:

We will now look at what makes up Spotify’s big data analytics from the point of view of four characteristic features.

Veracity

Spotify strives to be entirely data driven, ie. deliver insights and make decisions entirely based off data. Spotify’s idea behind behind data driven is that it is important to rely on data as much as possible to make decisions without human biases. Veracity (trustworthiness) of data is necessary in this context. Since Spotify collects most of its data from user activity and information over the internet, the data they collect can generally be considered reliable.

Volume and Velocity

In total, Spotify has over 28 petabytes of storage spread over four global data centres and collects about 4 terabytes of user data every day. This is huge amounts of data and requires analytics using technologies like HADOOP, particularly HDFS, which they can use to perform faster and distributed computing. In fact, Spotify has the largest HADOOP cluster in Europe. Spotify also uses Kafka for collecting data and databases to analyse and visualize it.

Variety

Spotify uses a variety of structured data from users and groups of users, such as: number of songs played by a user in a day, number of users listening to a particular album at a time etc. They can then use this to generate new insights such as predictions of what a user would like to listen to at a certain time during the day, what new artists a user might like etc. In general, they deal with a large variety of data that is useful to their analytics.

Key Partners and Customer Segments

By far, Spotify’s largest business partner is Facebook. Facebook was an integral component of Spotify’s first entry into the US market in 2011. Today, Facebook remains to be Spotify’s best sources for advertisement and new user acquisition. The integration between Facebook and Spotify is very sensible and intelligent. Spotify users have the option to link their Spotify account with their Facebook account. In doing so, they now have the capability to share songs, albums, artists, or playlists they are listening to. They also can now see the music their Facebook friends are listening to. However, shared music is not only shown to other Spotify users, but also non-users that are on Facebook. For Spotify as a business, this partnership has the advantage of both creating a more compelling and interactive product, and also helps expose their product to the larger market of Facebook users. Facebook also gains considerably from this partnership although in a less obvious manner. By integrating Spotify into the social media platform, Facebook generates additional user activity that makes its product more compelling to use. It also importantly gains more user information that can be used to better specialize advertisements and therefore make advertising space more valuable.

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Source: https://valuechaingeneration.com/2015/06/14/how-spotify-experiments-with-partnership-enabled-business-model-innovation/

More recently adopted partners of Spotify include Starbucks and Tinder. Starbucks’ partnership with Spotify works by offering free Spotify premium accounts to Starbucks retail locations. In return, Starbucks creates and promotes Starbucks sponsored playlists on Spotify. These playlists are advertised both in store locations and online. The partnership creates advertising and promotional space for both companies. Spotify advertises its service in the retail domain of Starbucks locations, and Starbucks gains the ability to promote its brand to Spotify users (and consequently Facebook users). The online dating service Tinder’s partnership with Spotify functions in much the same way as Spotify’s partnership with Facebook. Tinder users can display their music preferences and likes on their profile with Spotify links. Tinder obtains a more compelling service, and Spotify can better access new markets and users.

As one might suspect for an online and socially interactive music service, Spotify’s user demographics trend very young. Millennials are responsible for 72% of music streaming across mobile and desktop usage. This equates to approximately 1.3 billion songs per week. Despite this, Spotify continues to advertise to younger audiences rather than older ones. Spotify currently controls around 41% of the paid music streaming market but faces considerable competition from other streaming services like Apple Music, Pandora, and Tidal. As could be concluded from the company’s aforementioned partners, Spotify continues to advertise in younger markets as a means to draw users to its service instead of those of its competitors. This is thought to be a more beneficial strategy than to attempt to attract older demographics who will likely not use streaming services at all in most circumstances.

Value Propositions:

The value propositions of Spotify are that it enables customers to listen to music. There are two ways that make this possible. The first and preferred way that the customers can listen to music is, when they have a free account which is a big advantage. However the disadvantage that comes with it, is that the customers are forced to listen to advertisements without being able to skip them. These advertisements appear every thirty minutes. Another way of having access to the whole database is by making a premium account, where the customers buy the right to stream songs for a period of time without having to listen to any advertisements. Compared to other music streaming services, at Spotify customers pay roughly 5-10 Dollars monthly to listen to more than 12 million songs without being forced to listen to advertisements counter to free accounts. At other music streaming services the customers need to pay a much higher price just for one song out of a whole album. In conclusion the value for customers is that they exchange their owner rights to any of the songs in order to have access to all of them but they don’t have to make a choice between which song to buy or listen to because they can access all of them.

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Customer Relationship:

Spotify’s customer relationship is a big success because the relationship between Spotify and its customers enables customers to build a relationship among themselves by sharing their favourite songs and artists with their friends who then also become Spotify users and share their music further with their friends with the consequence that this whole process benefits Spotify. Spotify has 75 million active users and over 20 million subscribers in over 15 countries. In order to track what every customer and every song that is playing, Spotify uses Salesforce Customer Relationship Management to manage a growing file of tracks that is being delivered to millions of listeners in over 15 countries. Spotify’s goal is to make music accessible to everyone and connect with everybody by using social networks such as Facebook, Twitter and Tumblr in order for the customers to share their music and their favourite artists with all their social media contacts which enables Spotify to be used further by just music being constantly shared. This approach is also the backbone of how Spotify runs its business. According to Jonathan Forster, VP of Sales, EMEA “Connections are important to [the] business”. Spotify is constantly asking its customers for feedback caused by how fast they are moving so that it would be a disadvantage to wait a year for the feedback of customers. The company’s main focus is though to first ‘’connect all the people inside the company.” [Martin Lorentzon. Founder and Chairman]

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Cost Structure and Revenue Streams

Spotify services two types of accounts: free advertisement based accounts and premium subscription based accounts. Free users experience advertisements between every few songs where premium users pay a $10/month subscription fee. As one might expect, the number of free accounts well exceeds the number of premium accounts. Following the end of 2015, Spotify had approximately 160 million users of which only 39 million were premium subscribers. However, despite the disparity between the number of free and premium users, 90% of Spotify’s revenue comes from its subscription based accounts. Spotify is working to change this however and make its free users more profitable. In 2015, the company spent 250 million USD on researching user behavior and advertisement specialization. Spotify hopes to make increase the value of the advertisement space it offers in order to increase revenue.

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Source: https://www.bloomberg.com/gadfly/articles/2016-08-30/spotify-can-t-live-on-that-10-a-month-subscription-fee

Although profits have been found in some specific markets, as a whole, Spotify has not made a profit since its founding in 2006. In addition to the company’s largely unprofitable free user base, this also due in large part to the considerable costs associated with music streaming. The greatest cost by far is that of music licensing. In 2015, 55% of Spotify’s sales (1.8 billion USD) went towards covering licensing costs. Currently, Spotify is negotiating with major record labels to reduce these costs before the company attempts to become public in 2017. It is thought that reducing licensing costs to fall below 50% of sales would significantly improve the value of Spotify’s IPO. Another large cost that Spotify must cover is music streaming itself. In 2009, Spotify’s 5 million users streamed an average of 420,000 gigabytes of music per day. In 2015, Spotify’s now has approximately 160 million users who can also stream at higher bit rates than in years past; they likely stream over 14 million gigabytes of music on a daily basis. This, in addition to an ever expanding music library that must be physically stored, contributes to Spotify’s costs of operation and helps explain how such a large company can remain unprofitable.

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Source: (https://www.bloomberg.com/gadfly/articles/2016-08-30/spotify-can-t-live-on-that-10-a-month-subscription-fee)

SWOT Analysis:

Strength

Spotify’s main strength is its accessibility, it can be easily accessed from various devices, “it lets you play just about any song instantly without having to purchase or download it”(Chandler,n.d.) and it is user friendly. Consequently Spotify has currently about “100 million active users” (McIntyre, 2016) and 2 million artists with more than 20 million songs which makes it very popular among users.

As spotify is paying royalties to the artists and right holders the music on spotify can be streamed legally for free. On the other hand, Spotify tries to generate revenues through advertisements. However, users who do not want advertisements can create a Premium account and pay 9.99 € per month.

Weakness

One major weakness of spotify is that regardless of it’s many users it is not profitable due to its free streaming service.  Spotify has about 30 million paying users meaning they cannot pay high royalties. Furthermore, the “Music library is still limited by artists” (Hausman, 2013).  Some artists do not want to publish their music on spotify.

Opportunities

The music streaming industry has a large number of potential users and there is still a lot of potential to further expand digital streaming services. Moreover Spotify’s services of streaming music for free makes users who might have been used to “illegal or unreliable options for their digital music needs” (Hausman, 2013) switch to using their services.

Threats

Spotify’s major threat is their business model. Since they are not profitable, they can only pay small royalties to artists so artists like Taylor Swift who can make more money by selling albums will either continue to leave or not join their streaming services. If more artist continue to leave Spotify the number of users will drastically reduce, as their music needs will not be met by spotify. Moreover, David Lorry filed a $200 million lawsuit against Spotify due to copyright infringements. Additionally Spotify has a large amount of strong competitors like YouTube, AppleMusic and Amazon.

This shows that although Spotify is facing tough competition and has some weaknesses in its business model it has still a lot of potential to grow in the future. Besides the digital music streaming industry is a still expanding.

Conclusion:

In conclusion, we chose Spotify for our Big Data Project because we are all Spotify users, enjoying their services on a daily basis. Our goal with this project was to get a deeper insight on how Spotify operates, which challenges they are facing and how they use our information for their service. Furthermore we wanted to introduce the class to the Big Data of Spotify on how it works, what role it plays, and what its strengths and weaknesses are, as well as to address what kind of opportunities and threats it faces.

References:

Casinos, F. (2011). It All Makes Sense. It All Makes Sense. Retrieved from https://allmakessense.wordpress.com/.

Chandler, N. (n.d.). How Spotify Works. How Stuff Works Tech. Retrieved from http://electronics.howstuffworks.com/gadgets/audio-music/spotify4.htm

Hausman, A. (2013). The Spotify Business Model: No Guts No Glory. Capitalist Creations Entrepreneurship, Passions & Politics. Retrieved from http://capitalistcreations.com/the-spotify-business-model-no-guts-no-glory/

Hayes, T. (2016). The best music streaming service Spotify. The Sweet SetUp. Retrieved from http://thesweetsetup.com/apps/best-music-streaming-service/

McIntyre, H. (2016). With 30 Million Users, Spotify Is Gaining Subscribers Faster And Faster. Forbes. Retrieved from http://www.forbes.com/sites/hughmcintyre/2016/03/21/with-30-million-users-spotify-is-gaining-subscribers-faster-and-faster/#3fe709c6402e

Resnikoff, P. (2016). How Spotify Crushed a $200 Million Songwriter Lawsuit…. Digital Music News. Retrieved from http://www.digitalmusicnews.com/2016/07/12/spotify-crushing-david-lowery-lawsuit/

Spotify Solvay Case.(n.d.)The Business Model. Retrieved from https://spotifycase.wordpress.com/5-the-business-model/

Salesforce tops Spotify’s Playlist. Retrieved from http://www.salesforce.com/customers/stories/spotify.jsp

Doorneweert, Bart. How Spotify Experiments with Partnership-Enabled Business Model Innovation.. June 14, 2015. Retrieved from https://valuechaingeneration.com/2015/06/14/how-spotify-experiments-with-partnership-enabled-business-model-innovation/

Starbucks Announces Spotify Partnership. Billboard Staff. 19 January 2016. Retrieved from http://www.billboard.com/articles/business/6844194/starbucks-spotify-partnership-app-integration

McIntyre, Hugh. Millennials Are Leading The Spotify Revolution. Retrieved from http://www.forbes.com/sites/hughmcintyre/2016/04/20/millennials-are-leading-the-spotify-revolution/#75b56bb12f20

How much does Spotify cost to run? The Guardian. Retrieved from https://www.theguardian.com/technology/blog/2009/oct/08/spotify-internet

Spotify Can’t Live On 10 Dollars a Month. Bloomberg. Retrieved from https://www.bloomberg.com/gadfly/articles/2016-08-30/spotify-can-t-live-on-that-10-a-month-subscription-fee

Ingham,Tim. Spotify revenues topped 2 billion Dollar last year. Retrieved from http://www.musicbusinessworldwide.com/spotify-revenues-topped-2bn-last-year-as-losses-hit-194m/

Danielle, Jabin. Data at Spotify. Retrieved from http://www.slideshare.net/dj4b1n/data-at-spotify

Palmer, Jason. Analytics at Spotify. Spotify Labs. Retrieved from https://labs.spotify.com/2013/05/13/analytics-at-spotify/

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E-Governance: Representation and Citizen Engagement in the Information Age

Authors: Ma Hung-Jui (Arash Mahmoudian), Bhavyay Aurora, Gloria Mico, Majorka Thanasi.

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Figure 1 (http://pioneer-e-solutions.com/wp-content/uploads/2015/10/e-governance_COE.png)

 

E-Governance

E-governance, otherwise ‘electronic governance’, is an application of Information Technology in government functioning in order to create a more efficient and ‘smart’ government. It establishes instances for different (modern) styles of leadership, ways of debating and deciding policy and investment, ways of accessing education, ways of listening to citizens and ways of organizing and delivering information and services.

Governance relates to the processes of interaction and decision-making among the actors involved in a collective problem that lead to the creation, reinforcement, or reproduction of social norms and institutions [1]. These interactions include the exercise of political, economic and administrative authority in the management of a country’s affairs, including citizens’ articulation of their interests and exercise of their legal rights and obligations.

E-governance is defined as the performance of this governance via the electronic medium – Information and Communications Technology (ICT) –  in order to facilitate an efficient, prompt and transparent process of broadcasting information to the public, and other agencies, and for performing administrative projects.

This sort of governing can bring about a change in the way how citizens relate to governments and to each other. It can bring forth new concepts of citizenship, both in terms of citizen needs and responsibilities. Its objective is to engage, enable and empower the citizen. Leading governments, with democratic intent, are incorporating information and communication technologies into their e-government activities. By utilizing the best practices, technologies, and strategies will deepen and enhance participatory democracy and ensure representation and citizen engagement in the information age. It is upon this foundation that opportunities for greater online engagement and deliberation among citizens and their governments will demonstrate the value of information and communication technologies in effective and responsive participatory democracy [2].

There are multiple generic models described by The Digital Governance Initiative that can, in turn, be used to design an e-government initiative depending on local situation and governance activities that are expected to be delivered [3]. These models are comprised of the broadcasting / wider-dissemination model, critical flow model, comparative analysis model, e-advocacy / lobbying and pressure group model, and interactive-service model.

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Figure 2 E-Governance models.

The Broadcasting Model: The model is based on dissemination of governance information which is in the public domain into the wider public domain through the use of ICT and convergent media.

The Critical Flow Model: The model is based on disseminating information of critical value (which by its nature would be disclosed by those involved in ‘bad’ governance) to the intended audience i.e. the media, opposition parties, &c. or into the wider public domain through the use of ICT and convergent media.

Comparative Analysis Model: The model can be used for empowering people by matching cases of ‘bad’ governance with those of ‘good’ governance, and then analyzing the different aspects of ‘bad’ governance and its impact on the people. E.g. Human development indicators.

E-Advocacy / Pressure Model: The model is based on setting up a planned, directed flow of information to build strong virtual allies to complement actions in the real world. Virtual communities which share similar values and concerns are formed, and these communities in turn link up with or support real-life groups/ activities for concerted action. The model builds the momentum of real-world processes by adding the opinions and concerns expressed by virtual communities.

Interactive-Service Model: The model directly avails the various services offered by the government to its citizens in an interactive manner. It does so by opening up an interactive government to consumer to government channel in various aspects of governance, such as election of government officials; online passports; sharing of concerns and providing expertise; opinion polls on various issues &c.

 

E-Government and Democracy

Democracy & Populism

Populist movements are found in many democratic nations. Cas Mudde wrote that, “Many observers have noted that populism is inherent to representative democracy; after all, do populists not juxtapose ‘the pure people’ against ‘the corrupt elite’?” [4]

Essentially, populism is defined by the political doctrine that supports the rights and powers of the common people in their struggle with the privileged elite.

From a democratic standpoint, “the people” are defined as citizens who possess rights and duties. They have sovereignty that must be exercised within the limits of the law often codified in a constitution or charter.

According to Locke (commonly known as the “Father of Liberalism”), a ruler gains authority through the consent of the governed. The duty of that government is to protect the natural rights of the people, which Locke believed to include “no one ought to harm another in his life, health, liberty or possessions”. If the government should fail to protect these rights, its citizens would have the right to overthrow that government.

When the populace is frustrated with their perceived inability to affect legislation and regulate governance, they find populism encouraging. Leaders of an anti-establishment faction will often take a populist approach, rallying the followers with promises that the movement will address the wrongs committed against them by the ruling class. Such factions may resort to the E-advocacy model where parties undertake e-participation as well as general civic engagement policy work and allocate specific resources to such activities.

The presidential election of 2016 in United States of America saw candidates resort to online social media activities to portray political stances and policy proposals to the public mass. The former candidate, now president-elect, Donald J. Trump commonly utilized e-governance to disseminate information to the public (whether true or not) – such use of e-governance falls under the broadcasting model. Supporters of Trump were able to efficiently communicate using social media activities (particularly Twitter) to build the momentum of real-world processes by adding the opinions and concerns expressed.

Civil society led efforts work to establish information-age public spheres designed to encourage political and issue-based conversation, discussion and debate among citizens and their governments. With proper resources, structure and trust, it can play a deliberative role in public decision-making.

References

  1. Hufty, Marc. The Governance Analytical Framework. ACADEMIA. [Online] [Cited: November 22, 2016.] http://www.academia.edu/8012331/The_Governance_Analytical_Framework.
  2. Clift, Steven L. E-Government and Democracy. Publicus. [Online] February 2004. [Cited: November 20, 2016.] http://www.publicus.net/articles/cliftegovdemocracy.pdf.
  3. The Digital Governance Initiative. Generic E-Governance Models. [Online] [Cited: November 20, 2016.] http://www.digitalgovernance.org/index.php/models.
  4. The Populist Zeitgeist. Mudde, Cas. 4, s.l. : Cambridge Journals, 2004, Government and Opposition, Vol. 39, p. 560.

 

WIKILEAKS

Authors: Ma Hung-Jui (Arash Mahmoudian), Bhavyay Arora, Gloria Mico, Majorka Thanasi

Wikileaks is a “non-profit media organization,” launched in 2006 by its founder Julian Assange, an Australian activist, for the purposes of distributing original documents from anonymous sources and leakers. WikiLeaks is self-described to specialize in the analysis and publication of large datasets of censored or otherwise restricted official materials involving state affairs –  according to its website, Wikileaks has published more than 1.2 million documents and associated analyses.

In accordance to its website, “Wikileaks will accept restricted or censored material of political, ethical, diplomatic or historical significance. We do not accept rumor, opinion, other kinds of first-hand accounts or material that is publicly available elsewhere (Wikileaks n.d.).” Wikileaks acts as an innovative, secure and anonymous drop box for sources to leak information to journalists.

WikiLeaks specializes in publishing, curating, and ensuring easy access to full online archives of information that has been censored or suppressed, or is likely to be lost.

Purpose

“To radically shift regime behavior we must think clearly and boldly for if we have learned anything, it is that regimes do not want to be changed. We must think beyond those who have gone before us, and discover technological changes that embolden us with ways to act in which our forebears could not. Firstly we must understand what aspect of government or neocorporatist behavior we wish to change or remove. Secondly we must develop a way of thinking about this behavior that is strong enough carry us through the mire of politically distorted language, and into a position of clarity. Finally must use these insights to inspire within us and others a course of ennobling, and effective action.”

Julian Assange, “State and Terrorist Conspiracies”

Wikileaks is a multi-national media organization and associated library founded by its publisher Julian Assange in 2006. Julian Assange is an Australian citizen who is said to have served as the editor-in-chief and spokesperson for Wikileaks since its founding in 2006. The media and popular imagination currently equate him with Wikileaks itself, although with uncertain accuracy. Assange’s political philosophy is described as an opposition to the ‘stratagem-based, authoritarian conspiracy governments,’ which as he stated includes the United States of America and many other non-conventionally defined authoritarian states (Sklar 2010). He claims by exposing government secrets, he is weakening the government, and tries to hold governments accountable by leaking classified information.

 

 

 

SWOT Analysis

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Figure 1 Shows the summary SWOT analysis of Wikileaks.

Strengths

Strong management

Due to the fact that Wikileaks is practically independent, they are granted the opportunity to better run the organization in accordance with their own goals and beliefs. A strong management allows Wikileaks to reach its potential by utilizing strengths and eliminating vulnerability.

Loose infrastructure

Their global following and volunteer staff allows them to have a very loose organization. Little if any direction or coordination is actually passed (it is just inferred as part of the cause) (BRYANT 2010). Such structuring becomes very difficult to attack and disrupt, as larger infrastructure cease to exist. Many other points and organizations will be tasked to distribute the information and will help setting up new hosting services.

Weak competitions

Due to the radical approach to the utilization of technology and journalism, Wikileaks is not met by many competitors as most do not engage in or survive from risky endeavors (Greenberg 2012). Remarkable technology in encryptions allow Wikileaks to operate as intended – that is transferring documents to a country that offers a degree of legal protection.

Strong reputation

Because of their primary-source and factual documents, people are trustful towards WikiLeaks since there are no bias and-or editorial commentaries. Wikileaks has created a strong brand name and it has proven to be one of its strengths. This gives WikiLeaks the ability to efficiently disseminate content since people and other news agencies put additional value on the brand.

Weakness

Online presence

The online market is essential for displaying information. A weak online presence in many countries and regions can result in lost opportunities for WikiLeaks.

Technical challenges

Due to the nature of hardware, servers can overload causing extra effort and capital to maintain. Similarly, as Wikileaks grows, so does its database, the more information the site gets, the more difficult it is to store and protect all of it (Sutter 2010). If technical capabilities are not kept on par, the organization loses its purpose of anonymity as encryptions are no longer reliable. This can result in the shutdown of Wikileaks, whether through financial shortages or through governmental actions, etc.

Financial pressure

Financially, Wikileaks is under increasing pressure because authorities are blocking their funding sources (ZETTER 2012). WikiLeaks has long shown signs of financial distress. A financial model that exclusively depends on donations is not the most reliable.

Governmental laws

The legality of Wikileaks is on difficult ground because many of the documents published are confidential (if nothing else, publishing such documents is often a breach of copyright). Wikileaks has for now protected itself in the way it is structured. For example, it has no registered address or property in America, making it much harder for US organizations to take legal action against it. But measures like this is not enough when cases are brought up against Wikileaks. Although they have sometimes been taken offline temporarily, the site has yet to be shut down altogether. Assange remains under legal pressure in Europe and the United States (Savange 2010). He also being investigated by a grand jury in the United States.

Opportunities

Wikileaks is appealing to many, as it does not have substantial competitors. Many people and even news agencies are interested in the publications made by Wikileaks. Traditional journalists get to show the value that comes from parsing through complicated details, attracting new organizations (Anderson 2010). Wikileaks fulfills the desire people have towards equal right to information, by exposing the innerworkings of most governments.

Wikileaks ability to impact society with their documentation leaks proves to be an opportunity for them. With cables being analyzed, and published their popularity peaks, such recognition helps raise funds as more become aware and donate.

With modernization of many sovereign states, Wikileaks is able to expand into many new domains. And since many nations do not enforce proper internet laws (e.g. Romania) (Henderson n.d.), Wikileaks can set up new infrastructure to protect their data and servers.

Dead man’s switch. Wikileaks has an encrypted “insurance” files (contents of which are unknown) that can be found on various peer-to-peer networks (Murdock 2016). If ever Wikileaks is shutdown, the key to the files will be distributed world-wide. This gives them a higher chance to survive as an organization, since governmental officials will be concerned about the mutual-destruction.

Threats

Changes to governmental rules and laws can be a serious threat to Wikileaks, which has infrastructure in multiple countries registered from a library (Australia) to a charity organization (United States) (Whalen and Crawford 2010). If Wikileaks does not tread carefully, the government can easily target Wikileaks if popular support is attained.

Governmental measure to prevent whistleblowers from leaking confidential documents can be an issue for Wikileaks (Williams 2013). As this will prevent them from publishing new materials, as a result, their popularity will diminish and funding will be lost gradually. Although Wikileaks does not pay full-time to the hundreds of volunteers working with them, they still spend a large portion of their budget on constant maintenance of infrastructure, and for a time, travel expenses of members who risked being arrested by authorities. With high expenditures and an unreliable funding, the shutdown of Wikileaks is a high probability.

References

Anderson, C. W., interview by Jayshree Bajoria. 2010. How WikiLeaks Affects Journalism CFR. December 29. Accessed December 3, 2016. http://www.cfr.org/media-and-foreign-policy/wikileaks-affects-journalism/p23696.

BRYANT, MARTIN. 2010. “Why hasn’t the US government crushed Wikileaks?” The Next Web. October 23. Accessed December 3, 2016. http://thenextweb.com/us/2010/10/23/why-hasnt-the-us-government-crushed-wikileaks/.

Greenberg, Andy. 2012. “The WikiLeaks Spinoff That Wasn’t: An Exclusive Excerpt From This Machine Kills Secrets.” Wired. September 13. Accessed December 3, 2016. https://www.wired.com/2012/09/this-machine-kills-secrets/all/.

Henderson, Andrew. n.d. The five best host countries for website data privacy. Accessed December 3, 2016. http://nomadcapitalist.com/2013/12/15/top-5-best-countries-host-website-data-privacy/.

Murdock, Jason. 2016. “WikiLeaks unleashes new 88GB ‘insurance file’ onto the web – but what’s inside them?” International Business Times. June 21. Accessed Decemebr 3, 2016. http://www.ibtimes.co.uk/wikileaks-unleashes-new-88gb-insurance-file-onto-web-whats-inside-them-1566702.

Savange, Charlie. 2010. “U.S. Weighs Prosecution of WikiLeaks Founder, but Legal Scholars Warn of Steep Hurdles.” New York Times. December 1. Accessed December 3, 2016. http://www.nytimes.com/2010/12/02/world/02legal.html.

Sklar, Urizenus. 2010. “Understanding Conspiracy: The Political Philosophy of Julian Assange.” The Huffington Post. August 12. Accessed December 3, 2016. http://www.huffingtonpost.com/urizenus-sklar/understanding-conspiracy-_b_793463.html.

Sutter, John D. 2010. “The technical muscle behind WikiLeaks.” CNN. July 27. Accessed December 3, 2016. http://edition.cnn.com/2010/TECH/innovation/07/26/how.wikileaks.works/.

Whalen, Jeanne, and David Crawford. 2010. “How WikiLeaks Keeps Its Funding Secret.” The Wall Street Journal. August 23. Accessed December 3, 2016. http://www.wsj.com/articles/SB10001424052748704554104575436231926853198.

Wikileaks. n.d. Submissions. Accessed December 3, 2016. https://wikileaks.org/wiki/WikiLeaks:Submissions.

Williams, Lauren C. 2013. “How The Obama Administration Is Trying To Stop The Next Edward Snowden.” ThinkProgress. December 20. Accessed December 3, 2016. https://thinkprogress.org/how-the-obama-administration-is-trying-to-stop-the-next-edward-snowden-d4e0fdd68084#.vn929myie.

ZETTER, KIM. 2012. “WikiLeaks Wins Icelandic Court Battle Against Visa for Blocking Donations.” Wired. July 12. Accessed December 3, 2016. https://www.wired.com/2012/07/wikileaks-visa-blockade/.

 

The Use of Big Data in E-Commerce

Blog written by: Raghav Natarajan, Sagar Kumar, Ibrahim Malik, Lalit Singh.

Markets in the E-commerce industry are developing really quickly through the use of Big Data. With a large online user base, the E-commerce industry has been gathering big data in order to analyze past trends and performances to help markets grow, and increase customer satisfaction. Big data is used to track a customer’s journeys through online markets. Many websites use cookies to track what customers are looking at on the website. Through this data, customer preferences are segmented according to individual customers and this can help customers be more efficient in browsing items. Data consists of structured and unstructured information. Structured information is basic information about a customer while unstructured information consists of social media trends from Facebook, Twitter etc. Collecting the data from day-to-day operations helps the E-commerce industry analyze customer data in real time, enabling them to be more efficient in customer service. In order for the E-commerce industry to expand, customer experience needs to be built. Customers expects E-commerce businesses to treat them nicely, which in turn could help keep customers satisfied and loyal. Using Big Data, companies can use Predictive Analytics to predict what customers might buy. Amazon is one of the only companies to have perfected this method and has had great success in doing so. Due to real time analytics, Pricing can be changed constantly in order to keep up with the competition in the market. The management of supply chain would also become a lot easier through the use of Big Data as it can help track outsourced services. Big data analytics increasingly provides value to e-commerce firms by using the dynamics of people, processes, and technologies to transform data into insights for robust decision making and solutions to business problems. This is a holistic process which deals with data, sources, skills, and systems in order to create a competitive advantage. Leading e-commerce firms such as Google, Amazon, eBay, ASOS, Netflix and Facebook have already embraced big data analytics and experienced enormous growth. Through its systematic review and creation of taxonomy of the key aspects of big data analytics, this study presents a useful starting point for the application of big data analytics in emerging e-commerce research.

DATA SCIENCE AND ITS USAGE IN BANKING

Blog written/edited by: Sagar Kumar, Ibrahim Malik, Lalit Singh, Raghav Natarajan.

With the rapid advancements in technology, the amount of Big Data that is being accumulated has grown dramatically. All large companies are constantly relying on this data to improve their services, while in the case for governments, Big Data is the driver for E-Governance, a main contemporary method employed by governments to serve their citizens.

A major player in the story is data science. Data science uses more than just the conventional methods to extract extremely valuable information for the company/organization to make use of. It employs more complex algorithms and powerful systems to process information and is doing so quicker than ever before. There are several advantages of this: enhancements in security, law enforcement, different analyses, health care and disaster preparedness being a few of them. “The New York City Fire Department, for example, was one of the earlier success stories of using data science to proactively identify buildings most at risk from fire.” (finextra.com)

In banking, big data is a great arsenal that any proactive firm can use to take the lead over its competitors. “By using data science to collect and analyze Big Data, banks can improve, or reinvent, nearly every aspect of banking.” (finextra.com). By using the credit history of its customers, a bank can enhance various of its risk-management systems, including fraud detection and cyber analytics. Banks can track the cellular record of mobile phone users that are not even registered in the formal financial system.

There is, however, a challenge that exists. Reading, understanding and then analyzing the vast amounts of data that is produced every day is not an easy task, and requires extremely skilled and possibly experienced workers. Without data science, it is too difficult to identify patterns and come to concrete conclusions in research. Data science is an immense tool to help develop patterns and identify the trends that the vast data available represent. “‘Advanced data visualization’, an offshoot of the Big Data revolution, is the newest approach to business analytics and intelligence.” (finextra.com). However, it must never be ignored that skilled labor will always be the most valuable asset that any firm possesses, even when it comes to analyzing stuff as complex as Big Data.

 

Reference

https://www.finextra.com/newsarticle/28541/the-force-awakens-big-data-in-banking

VESTAS WIND SYSTEM: EVIDENCES

 

EVIDENCES (RESEARCH AND DEVELOPMENT)

-Vesta spent 92 million euro i.e. 1.4% of revenue on research and development in 2009.

– It has filed 787 wind turbine patents per United kingdom intellectual property office(UK-IPO) which is greater than General electric and Siemen wind power.

-In October 2009, It has claimed a successful test of stealth wind turbine blade mitigating radar reflection problems for aviation.

– In 2011, Vesta Super computer fire storm

-Donated super computer to Aolborg University

-In 2011, Floating wind turbine system in Portugal offshore.

– Dr. Chris Spruce, Research

– QUADCORE wind turbine test in April 2016, 3 months test theoretically confirmed

 

CHALLENGES

VESTA WIND SYSTEM

-founded in 1945

-largest wind power company, Danish company

-has manufacturing plants in different countries like USA, UK, Denmark, India , Germany,Romania,etc

-Employs 21,000 globally

– In 2012, installed 48,000 wind turbines for capacity of 55 GW in over 70 countries of 5 continents

CANDIDATE FOR SUSTAINABLE AND ULTIMATE SOLUTION TO ENERGY CRISIS PROBLEMS

 

Big Data and Social Media

Written by: David Duvall

Social media in the past several years has grown exponentially and will continue to grow as an increasing number of people around the world are gaining access to the Internet. Social media is defined as “forms of electronic communication (as Web sites for social networking and microblogging) through which users create online communities to share information, ideas, personal messages, and other content (as videos). This is clearly a broad spectrum and will continue to grow as innovations and more users change the social media industry over time. This summary will describe some advantages, disadvantages, opportunities, and threats to the use of social media both personally and corporately. Barack Obama’s 2008 campaign will also be analyzed because they able to effectively use social media and technology as an integral part of the campaign’s strategy.

  • Advantages of Social Media:
    • People are able to interact globally and at any time, in many cases.
    • Social media can serve as an effective marketing tool because of the large and diverse amount of people that use social media.
    • Information can be shared quickly.
    • A relatively inexpensive method of marketing to a large audience.
    • Provides companies with a medium for feedback from customers.
    • Allows for trends and market research to be done more easily because people around the world share their opinions about different goods, services, and companies on social media.
  • Disadvantages of Social Media:
    • It can be distracting. In 2012, a study found that teens spend nearly 80% of their online time on social networks.
    • People must be careful what they post online, employers and universities in some countries screen people using their social media profiles.
    • Studies have found that social networks can give you negative emotions and potentially amplify a person’s depression.
    • Data cannot necessarily be guaranteed to be 100% safe and secure.
  • Opportunities of Social Media:
    • Social networking continues to grow, especially among young people.
    • Provides a platform to expand business contacts.
    • Marketing is not necessarily constrained to national boundaries.
    • Provides alternative methods for employees and people to collaborate.
  • Threats of Social Media:
    • It can be unproductive when misused in places such as a workplace or school.
    • People can share too much information on social media and leave themselves vulnerable to someone who could take advantage of someone’s personal information.
    • Employers can use social media to discriminate against potential employees.
    • Misinformation can be spread quickly.
    • Data cannot necessarily be guaranteed to be 100% safe and secure.

Barack Obama was elected the 44th president of the United States on November 4th, 2008. A major contributor to his campaign’s success was the use of social media to both raise money and create a base of empowered volunteers who felt they could make a difference. Obama was able to establish online credibility and trust by gradually increasing his social media presence. He was also able to garner large support by focusing on involving and engaging voters, instead of focusing primarily on getting votes and money. Obama was more prevalent on all forms of social media than his Republican counterpart, John McCain. Barack Obama’s use of social media proved to be a significant method of marketing his name and goals as president.

In conclusion, social media is still growing and will continue to do so. Companies and people alike must know the potential disadvantages associated with this form of media, however, the benefits clearly outweigh possible threats. Social media has proven to be an effective way to spread ideas and opinions across the globe in a short amount of time and as more people join these sites it will only become more prevalent in society.

 

Big Data in Society: Security, Terrorism, Conflict and Intervention

Written by: David Duvall

Big data is changing societies around the world in a number of ways, it has many benefits but there are also disadvantages to this development. This summary will discuss how security, terrorism, conflict, and intervention have changed over the last decades and how big data has had a significant influence on this change.Big data has allowed for continuous and near ubiquitous observation and surveillance. This has influenced how nations on a large scale and people on a much smaller scale attempt to achieve and maintain their security. On a national scale the United States is world renowned for collecting large amounts of information and processing it for potential terrorist threats. The United States has several times overstepped though, such as when the NSA “tapped” Chancellor Merkel’s phone. This is a clear potential disadvantage if misused. On a small scale, big data could be used for a responsive home monitoring system among other uses.Connectivity is increased by the use of big data, which has had an effect on security, terrorism, conflict, and intervention. Security is improved because it is able to be more responsive and potentially prevent an event before it occurs. Terrorist groups are able to spread their message further and to more people through the use of social media, most notably. On the other hand, governments and their agencies are able to communicate and cooperate more effectively and efficiently to counteract these groups. Big data has made cyber attacks more prevalent in terms of conflict as several countries store large sums of data with personal and confidential information across the world. Intervention has also changed due to connectivity because both documenting and spreading the news of events has become easier and more accessible across the world. Storage of this data has become possible but it is a potential threat because it could be vulnerable to unauthorized access. The large sums of personal and confidential information held by countries like the U.S. could potentially be used against these people in a number of ways such as identity theft or blackmail. The spreading of terrorist group’s ideas and videos on the Internet highlights the inability of total control on the Internet. Governments that permit the use of the Internet can monitor the Internet but cannot effectively control it. Another example of this are websites which offer pirated material on the internet. Big data has also raised the question of trust throughout society. Among people the issue is how much information a person should share with others on the Internet, some if not many of these being people they might not actually know. The other issue is the amount of control and surveillance the governments and institutions have and are able to use with big data.

BIG DATA: Good or Evil?

Blog post written by group: Sagar Kumar, Ibrahim Malik, Lalit Singh, Raghav Natarajan.

Big Data has a lot of potential, even though that potential might not be so beneficial to us. Big retail super markets are a huge influence on today’s community, with almost €60,000 to €80,000 in revenue each day. Supermarkets are able to store, save and analyse the shopping patterns and their customer’s behaviors. In a world full of data tracking us, are we really ever alone. I want to take a look at this by talking about a real life anecdote concerning the digital personal space being violated through the use of Big Data in supermarkets.

A few years ago in Minneapolis, an angry dad barged into the popular target store Target. He claimed that Target was encouraging his daughter to get pregnant because his daughter had been receiving mail of posters and coupons selling baby diapers, cribs etc. A few weeks later, after an official apology from Target, the dad wrote back to Target stating that his “daughter was due in August, I owe you an apology”

As it turns out, target’s internal algorithms had been tracking and processing his daughter’s purchases. Patterns such as certain vitamin supplements or scent free soap, were taken into account; little hints that might signal a pregnancy. Without being told, Target knew that a girl was pregnant, before her own father.

We are being tracked and followed in this digital age now more than ever before either through DNA analysis, browser cookies, finger printing, cell phones, GPS and traceable debit cards. Target, for example, gives each customer a Guest ID, which links the customer’s demographics information such as:

  1. Age
  2. If they are married or not
  3. How many kids you have
  4. How long it takes for you to drive to the store
  5. Which part of town you live in
  6. Your estimated salary
  7. Whether or not you have moved recently
  8. What bank you have an account in
  9. Browser history and cookies etc.

This is thanks to their “predictive analysis” department that is devoted to understanding not only their customer’s shopping habits but also their personal habits in order to “market them” more efficiently. All this information that is collected and analysed is thanks to Big Data.

Read more about the Target story here: http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=1&_r=3&hp&

Digital Governance: Summary

Big Data: Summary

Authors: Ermira Salihu, Ilir Henci, Lorik Muçolli, Mohit Shrestha

shutterstock_108757142

Image 1

When we think about e-governance, we involuntarily associate it to every type of online governance, including terms such as e-government and digital governance. Fortunately, there is a difference between these terms and such difference must be acknowledged. E-government is a term used to describe the processes and methods that a single government uses to improve its online relationship with the citizens. It focuses on one aspect of improvement of the internal operations and public services.

E-governance on the other hand has a much broader scope. It is a concept that would be able to bring change to the way citizens relate to their government and the way they understand the idea of their government being reached at online. E-governance is able to bring forward new concepts and ideas that single government could use to improve their e-government. The idea behind e-governance is very simple. The goal it strives to achieve is enhancement of good governance. Good governance it characterized by accountability, participation, and transparency. The technological advancements that have happened in the past decade have allowed for such participation and transparency. In order for such e-governance to function, the framework of digital governance must be applied. Digital governance has the widest scope. It is considered the framework for establishing roles and decision making authority of an organization’s digital presence. Digital governance applies to every online organization, and not only that of the government. (UNESCO, 2005)

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Image 2 – Digital Governance Framework

E-Governance

As stated above, e-governance has a very broad range of topics and a very wide scope. It ranges with ideas from different concepts such as: ICT, Efficiency, Productivity, Reach, Sharing of Information, Service delivery, and Welfare. All of these aspects interact with each other when ensuring an efficient, transparent, and active model of e-governance. E-governance itself allows people who have access to the internet obtain information regarding passed laws, policies and decisions of local but also federal governments. It is present in developed countries and is in the process of releasing in most developing nations, as many governments do see the benefit of it. E-governance does not give everyone the ability to access any information they need. As people are, the government is also entitled to privacy. According to US law, the government could hold back any information which could be deemed as a threat to public order and to the people of the United States. This shows us that E-governance does not incorporate and publish all of the information that a government collects. It rather spreads information to the general public, that would have otherwise been done through other means, such as newspapers, journal publishing, pamphlets, or television. The goal of E-governance is to rather make the current information easily accessible than generating more information and data which would otherwise not be accessible. In order to ensure information and access flows of transparent and accountable e-governance, models must be utilized. The following models elaborate on how e-governance works (Chen & Hsieh, 2014).

Wider Disseminating Model

This model is considered the most crucial model of the geometrically sensitive e-governance systems. The reason for this is that it catalyses free access and the flow of valuable information to all part of the society and is often seen as the foundation of a good governance. The model is based on dissemination of relevant information to make best of governance, thus information that is already available through the public domain should be available to a wider public domain through the use of ICT, convergent media and other means of communication. The importance of the model relies on the informed citizen. An informed citizen is able to understand the governance mechanisms and is empowered to make rational choices and exercise its rights and responsibilities in a constructive manner.

Critical Flow Model

This model mainly aims to inform intended users about certain terms of information. It exposes the weakest aspects of governance and decision-making mechanisms by focusing the critical aspect of information. It informs people about specific cases of bad-governance by channeling information from the Private Domain Information to the Targeted Domain through ICT and convergent media. The model requires foresight to understand the importance of the information provided and ways of using it correctly and efficiently. On special cases, it involves locating certain people and informing them for particular information. Its strength relies on the characteristics of ICT that make the notion of time and distance redundant.

Comparative Analysis Model

This model deals with using lots of ICT and social media to compare information that is available in the private and public domain. For instance, say a certain district A built 2 schools with a certain amount of funds, whereas another district B built 5 schools with a similar amount. A comparative analysis model would analyze this information, along with other information available on both districts, and compare them. This could help determine if, say, there was any embezzlement of funds, and analyze why district A is inefficient compared to B. This model essentially compares the “best practice” of a certain government office and uses that as a comparison point to compare with other similar offices. One of the biggest advantages this model provides is the almost infinite amount of information that can be stored in digital media, as well as be transmitted with ease across geographical barriers. For example, the Human Development Report of UNDP uses archived statistical information to assess the progress made by different countries, and suggest policy recommendations based on that.

Mobilization and Lobbying Model

This model is more focused on a virtual community that links communities, individuals, networks and interest groups together, all of whom have a common goal. They all work towards a common goal by aligning force in the virtual community. An example of this model would be the combination of the following models:  SMS and Mobile Campaigns (in the Philippines and and Ukraine), Signature Campaigns (India: Petition OnlineCorruption), e-Signature Campaigns (Pakistan), e-Groups on Agriculture, Zimbabwe Kubatana.net (using emails for lobbying) and so on. If we look further into the ways of how this model works, you will find out all of these methods of data gathering are planned, directed, strategic flows of information that is provided for the real world out there.

Service Delivery Model

This model is often used as a way of consolidating the earlier digital governance models and for opening paths of direct participation of individuals in the governance processes. The “interactive” system sets the foundation of a healthy Citizen-Government relationship. It makes possible that the various services offered by the government are available to the citizens to use at any desired time. Having an interactive consumer is crucial for the e-governance because the various functions offered like filing tax returns, sharing of concerns and conducting opinion polls will actually be used properly and the consumer will be well informed about its responsibilities. This model is more of a characteristic of well developed countries but has also been proposed to be replicated in developing countries.

Populism and Community

The concept  of populism and community as a whole raise a critical point when it comes to them expanding their use of the Net. Will that produce a qualitatively distinct political system in the near future? At the end of the 1990’s two rather different claims have been made commonly and the one that set a more optimistic outlook was that the internet would make communities stronger, but the other was a populist claim of the opposite.

  • Populist Claim

This comes as a result of people’s claims that the internet will erode the influence of organized groups and political elites. According to this theory, the development of the internet will increase the community capacity, which will later increase citizen influence as well but decrease the influence of traditional political intermediaries on the other side. However, this claim was seen to be criticized by Bimber based on Lippmann (1934, Public Opinion) as he said that with the development of the internet it is true that communication capacity will increase but it does not also mean that the influence of the citizens will increase as well.

 

  • Community Building Claim

The community building claim differs from that of the Populist claim. This claim lays its foundation on changes within a community that occur between citizen to citizens; a citizen – citizen communication model. This communication would occur at a personal level and could bring together people with the same ideologies who would otherwise never have met each other. The internet services as a building block of such a claim. This is due to immediate access and instant communication services between people who share an opinion and ideology. The community building claim can also serve in forming movements, which could cause a change in the community as a whole and effect several people for the better or for the worse.  

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Image 3 – GreatAgain.Gov Homepage

Case: http://www.greatagain.gov

An example of a successful e-governance idea is the website released by Donald Trump and his team, www.greatagain.gov. This is considered so due to the reason that transparency is at its highest, with new updates from Trump’s transition team on a daily basis. It also promotes digital participation with the option given to people, to share their ideas on how to make America great again. With such in mind, the Big Data collected from such e-governance would be quite large and consistent, giving the Trump administration ideas on where to focus during their 4 years. As we can see, e-governance can also help collect data, rather than just spread to the citizens, as is it’s primary goal (“www.greatagain.gov,” 2016).

Trump Twitter Bots

Even though the idea of twitter bots influencing voters does not seem plausible, anything is possible with accurate use of Big Data. Automated accounts, also referred to as bots, were said to be used by Trump supporters that claimed to be spreading only what was the “truth”, Trumps victory. As claimed by Twitter statistics, the increase of automated accounts occurred when polls pointed to a lead for Hillary Clinton. The bots spammed a different story, which put Trump in the lead. Such claims are fairly controversial, and conspiracy theories rose claiming that Trump and his team did the act. This is due to Trump’s’ constant claims of having great reach within social media.

The bots were said to use big data algorithms, such that infiltrated pro Hillary supporters within twitter, and starting spreading false information, memes, and fake polls regarding her campaign and the user’s previous posts. Such use of big data would require fast and efficient processing methods, leading to the proposal that it would require efficient and costly software and hardware to accomplish, something an average person would not be able to do on their own (Markoff, 2016).

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Image 4 – Trump Twitter Bots

Arab Spring

It is believed that social media played a crucial role in shaping the political debates in the Arab Spring. The Arab Spring had many causes, but one of them was social media and the way it was used to put people in the side of political oppression. There are traces and evidence that show how social media was used to ignite political controversy in the key demographic group of the revolution.  It is hard to decide whether online information was driving people to the streets or that the presence of these people fed an online ongoing rage. Either way, it worked. Most people were writing blogs and “tweeting” about liberty, democracy and revolutions in order to ignite mass protests. Many governments recognized the power of the opposition that was using online information for its empowerment. In Tunisia, officials tried blocking social media sites and arresting bloggers who used their web-sites for writing criticizing articles about the government. To counter this, several hackers and talented computer programmers helped these activists in their tasks and were also able to shutter government services online and provide protesters with avoid the censorship (Howard et al., 2011).

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Image 5 – Arab Spring Revolution

References:  

UNESCO. (2005, August 3). Defining e-governance: UNESCO-CI. Retrieved November 27, 2016, from http://portal.unesco.org/ci/en/ev.php-URL_ID=4404&URL_DO=DO_TOPIC&URL_SECTION=201.html

Chen, Y.-C., & Hsieh, T.-C. (2014).  Big data for digital government: Opportunities, Challenges, and Strategies. Retrieved November 27, 2016, from  International Journal of Public Administration in the Digital Age, 1(1), 1–14. doi:10.4018/ijpada.2014010101

GreatAgain.Gov (2016). Retrieved November 28, 2016, from https://www.greatagain.gov/

Markoff, J. (2016, November 18). Automated pro-trump Bots overwhelmed Pro-Clinton messages, researchers say. Technology. Retrieved from http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html?_r=0

Howard, P. N., Duffy, A., Freelon, D., Hussain, M. M., Mari, W., & Mazaid, M. (2011). Opening closed regimes: What was the role of social media during the Arab spring? SSRN Electronic Journal. doi:10.2139/ssrn.2595096

Image References:

Image 1 – http://www.silicon.co.uk/wp-content/uploads/2014/08/shutterstock_108757142.jpg

Image 2 – Digital Governance Framework – https://blogs.adobe.com/digitalmarketing/wp-content/uploads/2013/01/digital_governance_framework_overview.png

Image 3 – GreatAgain.Gov Homepage – http://image.prntscr.com/image/0da109de226545bea4e454e4d74d0ae8.png

Image 4 – Trump Twitter Bots – http://cdn.thedailybeast.com/content/dailybeast/articles/2016/06/15/a-twitter-bot-is-beating-trump-fans/jcr:content/image.crop.800.500.jpg/48867792.cached.jpg

Image 5 – Arab Spring Revolution – http://www.newstatesman.com/sites/default/files/styles/nodeimage/public/blogs_2015/05/gettyimages-134083902.jpg?itok=Qhwt4uFo

Big Data: Cohealo

Group 13

By Dilara Misel, Janosch Jassim, Revazi Chikviladze, Alexandr Korolchuk

cohealo5Introduction

Every year, hospitals in the US spend around 150$ billions on medical equipment with an average usage of only 42%.

Cohealo, a technology company founded in 2012 by Mark Slaughter, Michael Slocombe and Brett Reed, made it their mission to increase such utilisation rates and to avoid unnecessary and extremely expensive purchases and rentals.

But how does this concept work?

The concept

Cohealo has cloud-based software, combining analytics and logistics that lets hospitals exchange and share their non-emergency medical equipment. When in need of a machinery, the hospitals can look up which hospital nearby is not in need of the specific equipment at the moment and pick it up from them. So it has a method similar to Uber or Airbnb. Big Data is being used in order to share medical resources and costs. To do so, a software with an easy interface drawing on real-time data and usage analytics was created. Hospitals can register their equipment and get access to a broad centralized data base on a single technology platform on which they provide the assets to anyone who needs it. Cohealo offers a big network of hospitals that have access to more equipment than they actually have in stock.

Who are the people who had the idea?

Cohealo was founded 2012 in Boston, Massachusetts mainly by Mark Slaughter with the help of Michael Slocombe and Brett Reed. Mark Slaughter graduated from the University of Miami Business School in 2012 and has since then received several awards including: Forbes 30 under 30 Healthcare (January 2015) or Fast Company World’s Top 10 Most Innovative Companies in Healthcare (January 2015).

 

For everyone who is interested in getting to know the founder of Cohealo and what he has to say about his idea, can watch this interesting interview with Mark Slaughter:

What the system provides

  • High quality care which is available and convenient for all patients (they do not have to drive to several hospitals in order to have a successful therapy).
  • Minimize equipment related therapy delays and cancellations.
  • It offers analytics to gain operational insight and more efficiently deploy assets.
  • On-demand access to every asset in your system.
  • Alerts when new technology was added to the system.
  • Run usage reports and view predictive analysis.

cohealo2

On the right side you can see the customer needs before the invention of Cohealo. The left side depicts advantages and disadvantages of the product. With the help of this image you can determine whether and in what way the product is suitable to the customer needs that were already existing before. The right side shows that before Cohealo, hospitals had problems with over- and under-utilisation of their clinical assets, and therefore had unnecessary high expenses or were not able to perform certain activities due to the lack of appropriate machineries. Moreover, there was no uniform system before which gave an overview of the availability of medical devices. Through Cohealo, a cloud based software was being created, offering a central system that provides an overview for each hospital about how to invest into new devices and also which already owned devices are utilized efficiently. With this,  the decision making process has become more facilitated. Furthermore, the software offers the opportunity to build up a huge network of hospitals to exchange their medical machineries with logistics already being cared about by Cohealo, so the use of those devices can be created more efficiently and costs can be shared.

To sum it all up, Cohealo offers access to clinical assets, the ability of centralized decision-making, a real-time data and usage analytics and the transport of clinical assets.

cohealo1

The Partners

Apart from their main partners being hospitals and logistics companies, the following are the most important financial supporters of the start-up company:

Romulus Capital

“Romulus has been an incredible partner to our growth in many ways – we could not have gotten started or won the Applebee’s deal without their support. They’re a very entrepreneurial group”. – Raj Suri, Cohealo Manager

In 2005, the Romulus foundation provided 2 millions of dollars to support Cohealo financially. Romulus made a great contribution by helping the start-up company to distribute their data to local hospitals as an experiment how it will go. After a first success, Romulus has offered an equal partnership with Cohealo with the agreement of regular funding Cohealo company with the opportunity that Cohealo is going to develop the strategies how to spread the Medicine Big Data to foreign countries.

Krillion Ventures

New investor Miami-based Krillion Ventures led the recently completed $9 million Series A financing that also included a number of notable individual investors. The financing was composed of both equity and convertible-note financing and builds upon seed investment from Romulus Capital. The proceeds will be used primarily for adding intellectual capital as the company looks to bring on additional engineers, sales executives and support staff, and further develop the Cohealo Platform.

 

SWOT-Analysis

cohealo4

References

Ehrenberg, M. (2016). The future of integrated facility management: A convergence of business trends is driving dynamic transformation and a new paradigm for integrated facility management in 2016. Corporate Real Estate Journal, 5(3), 238-247(10).

http://www.bloomberg.com/news/articles/2014-01-23/how-much-do-medical-devices-cost-doctors-have-no-idea

www.cohealo.com

http://romuluscap.com/

http://bostinno.streetwise.co/2016/09/07/cohealo-shared-medical-equipment-gets-funding-from-romulus/

 640 × 280 – krillionventures.com 

 1842 × 1407 – cohealo.com 

 986 × 599 – hitconsultant.net 

 1431 × 1007 – cohealo.com 

 565 × 298 – cohealo.com 

 700 × 466 – miamiherald.typepad.com