Big data and what this entails for social science researchers: Facebook partners with Social Science Research Council.

Kaylee Anne
Sep 1, 2018 · 4 min read

Sir Tim Berners-Lee, founder of the world wide web, envisioned the online sphere as an open space intended to facilitate the sharing of information and collaboration across otherwise existent borders. I think that we can agree that the web has lived up to this vision, however, in recent commentary, he expressed concern regarding our willingness to give up our personal data and perhaps how naïve we are with regards to the ramifications of our personal data falling into the hands of others (World Wide Web, 2017). We don’t tend to recognize the benefits we’re missing out on by surrendering our direct control of our data. This often occurs as a result to signing up for website which provide content in exchange for personal data, however, we are not privy to what data they access and how they choose to share it nor are we given the opportunity beyond the fact to indicate which data we’d rather not share. Another factor that we seem to overlook is the fact that it’s far too easy for misinformation to spread via the world wide web. The websites which this information is shared upon generate a profit based on advertisements generated as a result of active algorithms that are being gathered regularly (World Wide Web, 2017). The advertisements or content the web presents us with constitutes ‘fake news’ which is capable of spreading out of control (World Wide Web, 2017). Sir Tim Berners-Lee shares concerns that this information can be manipulated by actors in order for financial or political gain (World Wide Web, 2017).

Big data has recently been defined by Boyd & Crawford (2012) as “a cultural, technological, and scholarly phenomenon that rests on the interplay of technology, analysis, and mythology…” (p. 663). The literature distinguishes the three pillars as computation power and algorithmic accuracy with regards to gathering, analysing, linking and comparing large data sets, identification of emergent patterns in the data as well as the belief that these large data sets are able to provide information capable of inferring things otherwise unknown (Boyd & Crawford, 2012). Big data, however, is a topic of grave controversy. It has the capabilities of providing us with insights but also bears the consequences of invasion of privacy, infringement upon civil liberties, and imposition of further controls (Boyd & Crawford, 2012).

Although the collection, use, and dissemination of big data and recent developments in technology garners these ramifications, it also provides a great deal of opportunity for researchers, particularly social scientists. Digital scholarship, big data, and open access embody transparency, collaboration, and participation (Hicks & Sinkinson, 2015; Weller, 2011). Open data and sources which provide it such as Twitter, have led to a pleather of studies ranging from criminal behaviour to economics and financial markets or health care (Birkin, 2018). The use of big data in studies has to be addressed thoroughly by researchers as a method employed in the data collection phase and the possible limitations need to be acknowledged (Kitchin, 2014; Birkin, 2018).

Facebook has recently partnered with the Social Science Research Council granting access to Facebook data. Facebook’s social science program intends on supplying grants for university scientists to study the effects of social media upon elections. An expert commission will be appointed in order to act as a buffer between Facebook, the SSRC, funders, and the scientists as well as ensure the integrity of the research process with safeguards to protect users’ privacy. If this project is successful, it will be the stepping stone for more to come and has the potential of generating many very valuable insights. Read more about it by clicking here.

Work Cited

Birkin, M., (2018). Big Data for Social Science Research: Big Data. Magazine Ubiquity; Association for Computing Machinery; Vol. 2018, №1, p. 1–7. DOI: 10.1145/3158339.

Boyd, D., & Crawford, K., (2012). Critical questions for big data — Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society; Vol.15, №5, p. 662–679. DOI: 10.1080/1369118X.2012.678878.

Diep, F., (2018). Facebook is planning on turning its data over to social scientists. Should users trust the project? Pacific Standard. Retrieved from https://psmag.com/news/facebook-is-planning-on-turning-its-data-over-to-social-scientists-should-users-trust-the-project.

Hicks, A., & Sinkinson, C., (2015). Examining Mendeley: Designing learning opportunities for digital scholarship. Portal: Libraries and the Academy; Vol. 15, №3, p. 531–549. DOI: 10.1353/pla.2015.0035.

Kitchin, R., (2014). The data revolution: Big data, open data, data infrastructures & their consequences. Los Angeles, CA: SAGE Publications.

Weller, M., (2011). The Digital Scholar: How Technology is Transforming Scholarly Practice. London, UK: Bloomsbury Academic. Retrieved from https://ebookcentral.proquest.com/lib/uwsau/detail.action?docID=773623.

World Wide Web Foundation, (March, 2017). Three challenges for the web, according to its inventor. Web Foundation, News and Blogs. Retrieved from https://webfoundation.org/2017/03/web-turns-28-letter/.

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