Alexander Spangher
Adam Fourney
Eric Horvitz
ABSTRACT
The Russia-based Internet Research Agency (IRA) carried out a broad information campaign in the U.S. before and after the 2016 presidential election. The organization created an expansive set of internet properties: web domains, Facebook pages, and Twitter bots, which received traffic via purchased Facebook ads, tweets, and search engines indexing their domains. In this paper, we focus on IRA activities that received exposure through search engines, by joining data from Facebook and Twitter with logs from the Internet Explorer 11 and Edge browsers and the Bing.com search engine.
We find that a substantial volume of Russian content was apolitical and emotionally-neutral in nature. Our observations demonstrate that such content gave IRA web-properties considerable exposure through search-engines and brought readers to websites hosting inflammatory content and engagement hooks. Our findings show that, like social media, web search also directed traffic to IRA generated web content, and the resultant traffic patterns are distinct from those of social media.
- P. Aldhous. 2018. How Russia’s Online Trolls Engaged Unsuspecting American Voters. https://www.buzzfeednews.com/article/peteraldhous/russia-online-trolls-viral-strategy. Buzzfeed (2018).Google Scholar
- Rosenn I. C. M. L. A. Bakshy, E.2012. The Role of Social Networks in Information Diffusion. In WWW.Google Scholar
- A. Bessi. 2016. Personality Traits and Echo Chambers on Facebook. Computers in Human Behavior(2016). https://doi.org/10.1016/j.chb.2016.08.016Google Scholar
- Ferrara E. Bessi, A.2016. Social bots distort the 2016 U.S. Presidential election online discussion. First Monday 21, 11 (Nov. 2016). http://firstmonday.org/ojs/index.php/fm/article/view/7090Google Scholar
- L. Bittman. 1985. The KGB and Soviet disinformation: an insider’s view. Washington: Pergamon-Brassey’s.Google Scholar
- Spangher A. A. F. B. N. G. R. J. P. E. H. Boyd, R.2018. Characterizing the Internet Research Agency’s Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses. https://psyarxiv.com/ajh2q.Google Scholar
- Samantha Bradshaw and Philip N Howard. 2019. The global disinformation order: 2019 global inventory of organised social media manipulation. Project on Computational Propaganda.Google Scholar
- Agrawal D. A. A. Budak, C.2011. Limiting the Spread of Misinformation in Social Networks. In WWW.Google Scholar
- A. Chen. 2015. The Agency. https://www.nytimes.com/2015/06/07/magazine/the-agency.html. The New York Times (2015).Google Scholar
- Ratkiewicz J. M. F. B. G. F. M. A. F. Conover, M.2011. Political Polarization on Twitter.ICWSM (2011).Google Scholar
- Rubin V. Y. C. Conroy, N.2015. Automatic deception detection: Methods for finding fake news. In ASISST Annual Meeting. Am. Society for Information Science.Google Scholar
- Shaffer K. B. R. D. S. R. M. R. F. J. A. B. J. DiResta, R.2018. The Tactics & Tropes of the Internet Research Agency. https://disinformationreport.blob.core.windows.net/disinformation-report/NewKnowledge-Disinformation-Report-Whitepaper.pdf. (2018).Google Scholar
- Deb A. E. F. Dutt, R.2018. “Senator, We Sell Ads”: Analysis of the 2016 Russian Facebook Ads Campaign. https://arxiv.org/pdf/1809.10158.pdf. (2018).Google Scholar
- Hermann Ebbinghaus. 1913. Memory: A Contribution to Experimental Psychology; Translated by Henry A. Ruger and Clara E. Bussenius. Teachers College, Columbia University, New York.Google ScholarCross Ref
- A. A. W. Ellick. [n.d.]. Disinformation as collaborative work: Surfacing the participatory nature of strategic information operations. The New York Times([n. d.]). https://www.nytimes.com/2018/11/12/opinion/russia-meddling-disinformation-fake-news-elections.htmlGoogle Scholar
- Deng S. D. K. Elnoshokaty, A.2016. Success factors of online petitions: Evidence from change. org. In 2016 49th Hawaii International Conference on System Sciences (HICSS). IEEE, 1979–1985.Google Scholar
- Robertson R. Epstein, R.2015. The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences 112, 33(2015), E4512–E4521.Google ScholarCross Ref
- Robertson R. D. L. C. W. Epstein, R.2017. Suppressing the search engine manipulation effect. Proceedings of the ACM on Human-Computer Interaction 1, CSCW(2017), 42.Google Scholar
- Racz M. G. R. M. M. E. H. Fourney, A.2017. Geographic and Temporal Trends in Fake News Consumption During the 2016 US Presidential Election. In CIKM. ACM.Google Scholar
- De Francisci Morales G. A.G. M.M. Garimella, K.2018. Political Discourse on Social Media: Echo Chambers, Gatekeepers, and the Price of Bipartisanship. In WWW. https://doi.org/10.1145/3178876.3186139Google Scholar
- GDELT. 2018. Global Events Database.https://www.gdeltproject.org.Google Scholar
- Yuan A. M. S. V. S. R. D. Gillani, N.2018. Me, My Echo Chamber, and I: Introspection on Social Media Polarization. In Proceedings of the 2018 World Wide Web Conference. 823–831. https://doi.org/10.1145/3178876.3186130Google Scholar
- T. Gitlin. 2002. Media sociology: the dominant paradigm. na.Google Scholar
- David H.2012. A Tale of Two Sites: Twitter vs. Facebook and the Personality Predictors of Social Media Usage.Google Scholar
- Jung N.and S. V. Homero, G.2012. Social media use for news and individuals’ social capital, civic engagement and political participation. Journal of Computer-Mediated Communication(2012).Google Scholar
- Ganesh B. D. L. J. K. C. F. Howard, P.2018. The IRA, Social Media and Political Polarization in the United States, 2012-2018. https://comprop.oii.ox.ac.uk/wp-content/uploads/sites/93/2018/12/IRA-Report-2018.pdf. (2018).Google Scholar
- Chandrasekharan E. J. S. P. L. T. D A. B. L. H D. J. E. G. Im, J.2019. Still out there: Modeling and Identifying Russian Troll Accounts on Twitter. arXiv:1901.11162 (2019).Google Scholar
- Khamkham K. Cristea T. D. A. R. A. P. J. R. L. A. L. Inel, O. and S. R.2014. Crowdtruth: Machine-Human Computation Framework for Harnessing Disagreement in Gathering Annotated Data. In ISWC. Springer, 486–504.Google Scholar
- Intelligence Community Assessment. 2017. Background to “Assessing Russian Activities and Intentions in Recent US Elections”: The Analytic Process and Cyber Incident Attribution. Technical Report ICA 2017-01D. Office of the Director of National Intelligence.Google Scholar
- Warren P. Linvill, D.2018. ”The Troll Factories: The Internet Research Agency and State-Sponsored Agenda Building”. http://pwarren.people.clemson.edu/Linvill_Warren_TrollFactory.pdf.Google Scholar
- N. MacFarquhar. [n.d.]. A Powerful Russian Weapon: The Spread of False Stories. The New York Times([n. d.]). https://www.nytimes.com/2016/08/29/world/europe/russia-sweden-disinformation.htmlGoogle Scholar
- T. Mak. 2018. Russian Influence Campaign Sought To Exploit Americans’ Trust In Local News. www.npr.org/2018/07/12/628085238/russian-influence-campaign-sought-to-exploit-americans -trust-in-local-news. National Public Radio(2018).Google Scholar
- A. Marwick and R. Lewis. 2017. Media Manipulation and Disinformation Online. New York: Data & Society Research Institute (2017).Google Scholar
- Pruksachatkun Y. Metaxas, T.2017. Manipulation of search engine results during the 2016 US congressional elections. (2017).Google Scholar
- R. Mueller. 2018. Internet Research Agency Indictment. https://www.justice.gov/file/1035477/download.Google Scholar
- R. Mueller. 2018. Report On The Investigation Into Russian Interference In The 2016 Presidential Election. https://www.justice.gov/storage/report.pdf.Google Scholar
- United States. Department of State. 1987. Soviet Influence Activities: A Report on Active Measures and Propaganda, 1986-87. Vol. 9627. US Department of State.Google Scholar
- [38] O Offer.2018. https://www.similarweb.com/.Google Scholar
- Garimella K. I. W. Rama, V. Rama. 2017. A long-term analysis of polarization on Twitter. In Eleventh International AAAI Conference on Web and Social Media. https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15592Google Scholar
- Garrett R. T. K. S. M. N. S. Resnick, P.2013. Bursting Your (Filter) Bubble: Strategies for Promoting Diverse Exposure. CSCW (2013).Google Scholar
- Saha K. Ribeiro, F.2108. On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook. ”arxiv”:”cs.SI”/arXiv:1808.09218Google Scholar
- A. Schiff. 2018. Statement on Release of Facebook Advertisements. https://democrats-intelligence.house.gov/news/documentsingle.aspx?DocumentID=379.Google Scholar
- A. Schiff. 2018. Statement on Release of Twitter Ads, Accounts and Data. https://democrats-intelligence.house.gov/news/documentsingle.aspx?DocumentID=396.Google Scholar
- S Scott. 2017. These Are the Ads Russia Bought on Facebook in 2016. https://www.nytimes.com/2017/11/01/us/politics/russia-2016-election-facebook.html. The New York Times (2017). https://www.nytimes.com/2017/11/01/us/politics/russia-2016-election-facebook.htmlGoogle Scholar
- Sliva A. S. W. J. T. H. L. Shu, K.2017. Fake news detection on social media: A data mining perspective. KDD (2017).Google Scholar
- A. A. T. W. Starbird, K.2019. Disinformation as collaborative work: Surfacing the participatory nature of strategic information operations. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–26.Google Scholar
- Arif A. K. S. Stewart, L.2018. Examining trolls and polarization with a retweet network. In WSDM Workshop on Misinformation and Misbehavior Mining on the Web.Google Scholar
- C. Sunstein. 2018. # Republic: Divided Democracy in the Age of Social Media. Princeton University Press.Google Scholar
Index Terms
- Characterizing Search-Engine Traffic to Internet Research Agency Web Properties
Index terms have been assigned to the content through auto-classification.
Recommendations
Web search engine multimedia functionality
Web search engines are beginning to offer access to multimedia searching, including audio, video and image searching. In this paper we report findings from a study examining the state of multimedia search functionality on major general and specialized ...
Comments