Indiana University’s Observatory on Social Media, funded in part last year with a $3 million grant from the John S. and James L. Knight Foundation, has named two new Knight Fellows. Matthew DeVerna and Harry Yaojun Yan will help advance the center’s ongoing investigations into how information and misinformation spread online. The Observatory on Social Media, or OSoMe (pronounced “awesome”), is a collaboration between CNetS in the Luddy School of Informatics, Computing and Engineering; The Media School; and the IU Network Science Institute. Congratulations to Harry and Matt! More…
CNetS students, postdocs, and faculty members will give 7 regular talks and present 13 posters at NetSci 2020, held online this year due to COVID-19. Regular talks will cover research on many topics including COVID-19, forecasting social contagion of anti-vax ideas, political bias in social media, coordinated manipulation online, the scientific development of nations, hierarchy in faculty hiring networks, and citation cartels in journals.Continue reading CNetS @ NetSci 2020
CNetS students, postdocs, and faculty members will be presenting 12 papers, 7 posters, and a tutorial on OSoMe tools at the 2000 International Conference on Computational Social Science (IC2S2), held online this year due to COVID-19. In addition, Fil Menczer will deliver one of the keynotes. Continue reading CNetS @ IC2S2
In the groundbreaking new PBS series “NetWorld,” Niall Ferguson visits network theorists, social scientists and data analysts (including at CNetS!) to explore the intersection of social media, technology and the spread of cultural movements. Reviewing classic experiments and cutting-edge research, NetWorld demonstrates how human behavior, disruptive technology and profit can energize ideas and communication, ultimately changing the world.
I am very honored and feel that this is a recognition of years of teamwork with wonderful colleagues and amazing students and postdocs at IU.
The book A First Course in Network Science by CNetS faculty members Filippo Menczer and Santo Fortunato and CNetS PhD graduate Clayton A. Davis was recently published by Cambridge University Press. This textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Extensive tutorials, datasets, and homework problems provide plenty of hands-on practice. The book has been endorsed as “Rigorous” (Alessandro Vespignani), “comprehensive… indispensable” (Olaf Sporns), “with remarkable clarity and insight” (Brian Uzzi), “accessible” (Albert-László Barabási), “amazing… extraordinary” (Alex Arenas), and “sophisticated yet introductory… an excellent introduction that is also eminently practical” (Stephen Borgatti). It was ranked by Amazon #1 among new releases in physics. More…
Indiana University will establish a $6 million research center to study the role of media and technology in society. With leadership by CNetS faculty, the Observatory on Social Media will investigate how information and misinformation spread online. It will also provide students, journalists and citizens with resources, data and training to identify and counter attempts to intentionally manipulate public opinion. Major support for the center comes from the John S. and James L. Knight Foundation, which will contribute $3 million, as well as funds from the university. The center is a collaboration between the IU School of Informatics, Computing and Engineering, The Media School and the IU Network Science Institute. More…
UPDATE: This paper is ranked #3 most read among all articles published by Nature Communications in 2018
Analysis by CNetS researchers of information shared on Twitter during the 2016 U.S. presidential election has found that social bots played a disproportionate role in spreading misinformation online. The study, published in the journal Nature Communications, analyzed 14 million messages and 400,000 articles shared on Twitter between May 2016 and March 2017 — a period that spans the end of the 2016 presidential primaries and the presidential inauguration on Jan. 20, 2017. Among the findings: A mere 6 percent of Twitter accounts that the study identified as bots were enough to spread 31 percent of the low-credibility information on the network. These accounts were also responsible for 34 percent of all articles shared from low-credibility sources. The study also found that bots played a major role promoting low-credibility content in the first few moments before a story goes viral. Continue reading Twitter bots play disproportionate role spreading misinformation
Congratulations to Clayton A. Davis, who successfully defended his PhD dissertation titled “Collect, Count, and Compare”: Expanding Access and Scope of Social Media Analysis. Dr. Davis’ work explored ways to facilitate research using massive social data through tools that are friendly for non-technical users, robust to manipulation by social bots, and that offer strict anonymity guarantees. His work has been featured on the cover of Communications of the ACM and quoted in top worldwide media venues. Web interfaces for his projects, including Botometer, Kinsey Reporter, and the Observatory on Social Media, have served millions of queries to thousands of Internet users. Davis has also made key pedagogical contributions, and co-authored a textbook on network science to be published later this year by Cambridge University Press.
Congratulations to Dimitar Nikolov, who successfully defended his PhD dissertation on Information Exposure Biases in Online Behaviors. Dr. Nikolov’s research explored the unintentional biases introduced by filtering, ranking, and recommendation algorithms that mediate our online consumption of information. His findings show that our reliance on modern online technologies limits exposure to diverse points of view and makes us vulnerable to misinformation. In particular, he analyzed two massive Web traffic datasets to quantify the popularity and homogeneity bias of several popular online platforms including social media, email, personalized news, and search engines. He also leveraged Twitter data to characterize the link between political partisanship and vulnerability to online pollution, such as fake news, conspiracy theories, and junk science. His dissertation contributes to the field of computational social science by putting the study of bias in information consumption and derived phenomena like political polarization, echo chambers, and online pollution on a more firm quantitative foundation.