Computational Social Science for the World Wide Web WSTNet Web-Science Summer School 2016, U. of Koblenz-Landau Markus Strohmaier Claudia Wagner Ingmar Weber Luca Maria Aiello GESIS – Leibniz Inst. for the Social QCRI Yahoo Labs Thanks to Ingmar and Luca: the slides used Sciences and Uni. of Koblenz-Landau in today‘s tutorial are based on a tutorial Markus Strohmaier held at WWW‘16 by all four tutors. 1
Markus Strohmaier I am a computer scientist in a social science institute. • Professor at the Dept. of Computer Science University of Koblenz-Landau, Germany • Founder & Scientific Director, Dept. of Computational Social Science GESIS – Leibniz Institute for the Social Sciences http://markusstrohmaier.info Cologne, Germany @mstrohm Post-Doc at U. of Toronto (2006/07) Visiting Researcher at (Xerox) Parc (2010/11), Visiting Assistant Professor at Stanford (2011/12), Assistant Professor at Graz University of Technology (2007-13) Interested in understanding social phenomena via new kinds of data, from a methodological, empirical and theoretical perspective. Communities: WWW, ICWSM, Web-Science, ICCSS Markus Strohmaier 2
WHO ARE YOU? Markus Strohmaier 3
Computational Social Science Tutorials Last year (WWW ‘ 15): • A great tutorial on Online Experiments for Computational Social Science by Eytan Bakshy & Sean J. Taylor • Focus on “making your own data” , using PlanOut useful if you have operational access to large online social platforms (eg. Wikipedia, Facebook) This year (WWW’16): Wagner, Strohmaier, Weber, Aiello • Focus on “found data” and social issues, useful if you don’t have operational access to platforms, but access to web data • We will cover theory , data and methods / models Markus Strohmaier 4
Found data in the social sciences There are two general types of found data: Accretion - a build-up of physical traces Erosion - the wearing away of material Markus Strohmaier 5
Found data on the web Polarization in Weblogs Polarization on Twitter during the US 2004 election during the German 2013 election Adamic, Lada A., and Natalie Glance. "The political blogosphere H. Lietz, C. Wagner, A. Bleier, and M. Strohmaier. When and the 2004 US election: divided they blog." Proceedings of the politicians talk: Assessing online conversational practices of 3rd international workshop on Link discovery . ACM, 2005. political parties on twitter. In International AAAI Conference on Weblogs and Social Media (ICWSM2014), Ann Arbor, MI, USA, June 2-4, 2014. Markus Strohmaier 6 6
Social Issues on the Web: Growing Global Inequality TBL: the Web has the potential to be a great equalizer , but only “ if we hardwire the rights to privacy, freedom of expression, affordable access and net neutrality into the rules of the game .” http://thewebindex.org/ Equal access to information, knowledge, opportunity Markus Strohmaier 7
Stereotypes Google image query: „ Doctor “ Google image query: „ Nurse “ „evidence for stereotype exaggeration and systematic underrepresentation of women” Kay, Matthew, Cynthia Matuszek, and Sean A. Munson. "Unequal Representation and Gender Stereotypes in Image Search Results for Occupations." Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems . ACM, 2015. Markus Strohmaier 8
Discrimination “ non-black hosts are able to charge approximately 12% more than black hosts , holding location, rental characteristics, and quality constant.“ Edelman, Benjamin G. and Luca, Michael, Digital Discrimination: The Case of Airbnb.com (January 10, 2014). Harvard Business School NOM Unit Working Paper No. 14-054. http://dx.doi.org/10.2139/ssrn.2377353 Markus Strohmaier 9
Racism Photo app tagging black people as „gorillas“ Markus Strohmaier https://twitter.com/jackyalcine/status/615331869266157568 10
Inequality “ the way women are portrayed on Wikipedia starkly differs from the way men are portrayed.” “ Women on Wikipedia tend to be more linked to men than vice versa” C. Wagner, D. Garcia, J. Mohsen, and M. Strohmaier. It’s a man’s Wikipedia? assessing gender inequality in an online encyclopedia. In International AAAI Conference on Web and Social Media (ICWSM2015), Oxford, UK, May 26-29, 2015. Markus Strohmaier 11
Price discrimination we find evidence for price steering and price discrimination on four general retailers and five travel sites. Measuring Price Discrimination and Steering on E-commerce Web Sites, Aniko Hannak, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson, In Proceedings of the 14th ACM/USENIX Internet Measurement Conference (IMC'14) , Vancouver, Canada, November 2014. Markus Strohmaier 12
Map personalization China's territory [ … ] was shown to be about 21% larger by pixel count when it was depicted on Google Maps localized for mainland Chinese consumption. To be presented this week! MapWatch: Detecting and Monitoring International Border Personalization on Online MapsGary Soeller, Karrie Karahalios, Christian Sandvig, and Christo Wilson, Proceedings of the 25th International World Wide Web Conference (WWW 2016)Montreal, Quebec, Canada, April 2016 Markus Strohmaier 13
Why our community should care about social issues on the Web The web reflects and helps shape : • Inequality • Elections • Social Structures • Polarization • Discrimination • Views and Opinions • Beliefs and Religions • Radicalization • Hate • Personality • Crime • Perceptions How do we describe them? How do we shape them? Markus Strohmaier 14
the Web has the potential to be a great equalizer , but only “if we hardwire the rights to privacy, freedom of expression, affordable access and net neutrality into the rules of the game.” equal access to information, knowledge, opportunity e e r v u o ? s a r t p n e m a m w i ? e e s e ? w w w a e n i o o t b i e d l d a e m u w w w o q o o e n e H H n h e h i t s p g i n l t a i t a i s c h i W o x e s http://webfoundation.org/2014/12/recognise-the-internet-as-a-human-right-says-sir-tim-berners-lee-as-he-launches-annual-web-index/ Markus Strohmaier 15
So when TBL asks: What kind of web do we want? https://webwewant.org/ We (Web-researchers) need to lead the way in exploring and devising the web you want. this means: build measurement instruments, understand social phenomena, devise policies, test and experiment with ideas, regulation and standardization, etc Markus Strohmaier 16 16
http://webwewant.org/ Markus Strohmaier 17
Computational Social Science Computational Social Science : “The science that investigates social phenomena through the medium of computing and algorithmic data processing.” [adapted from CSSSA] CSSSA: http://computationalsocialscience.org/ So is this a new field The WWW community for social scientists to needs to join the effort to engage in? shape the WebWeWant! • Harvard iQS, • Stanford IRiSS, • CMU CASOS, • ESRC COSMOS • Web Observatories • … 18 Markus Strohmaier 18
Where to go from here To shape the WebWeWant , there is a need to learn about • Social issues • Social science theories • Social science hypotheses and methods • Social science data Social science has a lot to contribute! Markus Strohmaier 19
Polarization in the US Congress 1949-2011 1949 2011 http://www.mamartino.com/projects/rise_of_partisanship/ Markus Strohmaier sources: Andris, C. et al (2013) santa fe institute working paper (nov. 11, 2013) Andris, C. (2011) doctoral dissertation, mit, chapter 5 20
Gender inequality World Economic Forum Hausmann, Ricardo, Laura D. Tyson, and Saadia Zahidi. "The global gender gap index 2012." The Global Gender Gap Report (2012): 3-27. Markus Strohmaier 21
Social Science Data: US Census rich in attributes : • Age and Sex • Race and Origin • Housing • Living Arrangements • Education • Health • Economy • Transportation • Income and Poverty Markus Strohmaier 22
Social Science Data: World Value Survey Markus Strohmaier 23
The Social Sciences* *a simplified view … are interested in understanding how people • think/feel/behave in social situations (social psychology), • relate to each other (sociology), • govern themselves (political science), The web as a universal • handle wealth (socioeconomics), and data source for • create culture (anthropology). social science questions? M. Strohmaier, C. Wagner, Computational Social Science for the World Wide Web, IEEE Intelligent Systems 29(5): 84-88, 2014. Markus Strohmaier 24
The value of Web data for social science research Web data is often Web data is also • not representative • highly granular • population biases • high temporal resolution • poor in attributes • rich in structure • unknown demogr. attributes • multi-relational data • dominated by a few • rich in sources • Power law phenomena • integration of diff. data types • shaped by systems • complete • algorithmically mediated • systems capture all interactions • noisy • users != people Markus Strohmaier 25
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