Social data revolution

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The social data revolution is the shift in human communication patterns towards increased personal information sharing and its related implications, made possible by the rise of social networks in early 2000s. This phenomenon has resulted in the accumulation of unprecedented amounts of public data.[1]

This large and frequently updated data source has been described as a new type of scientific instrument for the social sciences.[2] Several independent researchers have used social data to "nowcast" and forecast trends such as unemployment, flu outbreaks,[3] mood of whole populations,[4] travel spending and political opinions in a way that is faster, more accurate and cheaper than standard government reports or Gallup polls.[2]

Social data refers to data individuals create that is knowingly and voluntarily shared by them. Cost and overhead previously rendered this semi-public form of communication unfeasible, but advances in social networking technology from 2004-2010 has made broader concepts of sharing possible.[5] The types of data users are sharing include geolocation, medical data,[6] dating preferences, open thoughts, interesting news articles, etc.

Early examples of social data are Craigslist and the wishlists of Amazon.com. Both enable users to communicate information to anybody who is looking for it. They differ in their approach to identity. Craigslist leverages the power of anonymity, while Amazon.com leverages the power of persistent identity, based on the history of the customer with the firm. The job market is even being shaped by the information people share about themselves on sites like LinkedIn and Facebook.[7]

Examples of more mature social data are Twitter and Facebook. On Twitter, sending a message or tweet is as simple as sending an SMS text message. Twitter made this C2W, customer to world: Any tweet a users sends can potentially be read by the entire world. Facebook focuses on interactions between friends, C2C in traditional language. It provides many ways for collecting data from its users: "tag" a friend in a photo, "comment" on what they posted, or just "like" it. These data are the basis for sophisticated models of the relationships between users. They can be used to significantly increase the relevance of what is shown to the user, and for advertising purposes.[8]

The social data revolution does not only enable new business models like the ones on Amazon.com, but also provides large opportunities to improve decision-making for public policy and international development.[9]

The analysis of large amounts of social data leads to the field of Computational Social Science. Classic examples include the study of media content or of social media content.[3][4]

See also[edit]

References[edit]

  1. ^ Weigend, Andreas. "The Social Data Revolution". Harvard Business Review. Retrieved July 15, 2009. 
  2. ^ a b Hubbard, Douglas (2011). Pulse: The New Science of Harnessing Internet Buzz to Track Threats and Opportunities. John Wiley & Sons. 
  3. ^ a b Vasileios Lampos and Nello Cristianini. Nowcasting Events from the Social Web with Statistical Learning. ACM TIST 3(4), n.72, 2012. http://dl.acm.org/citation.cfm?doid=2337542.2337557
  4. ^ a b Nowcasting the mood of the nation - Significance Magazine Thomas Lansdall‐Welfare, Vasileios Lampos, Nello Cristianini Aug 09, 2012 - Volume 9 Issue 4 (August 2012)
  5. ^ Swathi Dharshana Naidu (Dec 2009). "Social Data Revolution". Posterous. Retrieved 7/8/2010.  Check date values in: |accessdate= (help)
  6. ^ Dyson, Esther (March 23, 2010). "Health, not Health Care!". Huffington Post. Retrieved 6/8/2010.  Check date values in: |accessdate= (help)
  7. ^ Reid Hoffman (June 26, 2009). "Future of Jobs & Social Data Revolution". Techaffair.com. Retrieved 7/2/2010.  Check date values in: |accessdate= (help)
  8. ^ Dyson, Esther (February 11, 2008). "The Coming Ad Revolution". The Wall Street Journal. Retrieved 4/10/2010.  Check date values in: |accessdate= (help)
  9. ^ "Big Data for Development: From Information- to Knowledge Societies", Martin Hilbert (2013), SSRN Scholarly Paper No. ID 2205145). Rochester, NY: Social Science Research Network; http://papers.ssrn.com/abstract=2205145