Probing political bias on Twitter with drifter bots

September 24, 2021Fil, NaN, Newsbias, echo-chamber, information networks, misinformation, papers, politics, social bots, social media, social networks, Twitterfil

Our latest paper “Neutral bots probe political bias on social media” by Wen Chen, Diogo Pacheco, Kai-Cheng Yang & Fil Menczer just came out in Nature Communications. We find strong evidence of political bias on Twitter, but not as many think: (1) it is conservative rather than liberal bias, and (2) it results from user interactions (and abuse) rather than platform algorithms. We tracked neutral “drifter” bots to probe political biases. In the figure, we see the drifters in yellow and a sample of their friends and followers colored according to political alignment. Large nodes are accounts sharing a lot of low-credibility links.

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ICWSM Test of Time Award

June 11, 2021Fil, NaN, Newsaward, ICWSM, papers, social media, social networks, Twitterfil

Our 2011 paper Political Polarization on Twitter was recognized at the 2021 AAAI International Conference on Web and Social Media (ICWSM) with the Test of Time Award. First author Mike Conover, who was then a PhD student and is now Director of Machine Learning Engineering at Workday, accepted the award at a ceremony at the end of the ICWSM conference. Other authors are Jacob Ratkiewicz (now a Tech Lead at Google), Bruno Gonçalves (now VP at JPMorgan Chase), Matt Francisco (now Lecturer at IU Luddy School), Alessandro Flammini (Professor of Informatics at IU Luddy), and Filippo Menczer (Distinguished Professor and Director of the Observatory on Social Media at IU).

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New grant on AI and multilayer networks

May 9, 2021News, Santograph embedding, network sciencesanto

The Army Research Office has awarded the grant Multilayer network embeddings and applications to real-world problems to CNetS faculty Santo Fortunato and Filippo Radicchi. The project lies at the interface between artificial intelligence and network science and aims at developing embeddings of multilayer networks in vector space. While graph embeddings have become very popular over the past decade, most of the research in this area focuses on the analysis of isolated graphs. However, networks in the real world do not exist in isolation, but they are coupled with other networks. For example in social media, the same person may interact with different individuals depending on the online platform.

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Distinguished Master’s Thesis Award

November 1, 2020Fil, NaN, Newsaward, fakey, hoaxy, misinformation, social media, studentsfil

CNetS alumnus Mihai Avram is the recipient of the 2020 Indiana University Distinguished Master’s Thesis Award for his work on Hoaxy and Fakey: Tools to Analyze and Mitigate the Spread of Misinformation in Social Media. This award recognizes a “truly outstanding” Master’s thesis based on criteria such as originality, documentation, significance, accuracy, organization, and style. Some of the findings in Mihai’s thesis have recently been published in the paper Exposure to social engagement metrics increases vulnerability to misinformation, in The Harvard Kennedy School Misinformation Review. Congratulations Mihai!

Evidence of a coordinated network amplifying inauthentic narratives in the 2020 US election

September 25, 2020Fil, NaN, Newsmanipulation, misinformation, Network Analysis, networks, politics, social bots, Twitterfil

On 15 September 2020, The Washington Post published an article by Isaac Stanley-Becker titled “Pro-Trump youth group enlists teens in secretive campaign likened to a ‘troll farm,’ prompting rebuke by Facebook and Twitter.” The article reported on a network of accounts run by teenagers in Phoenix, who were coordinated and paid by an affiliate of conservative youth organization Turning Point USA. These accounts posted identical messages amplifying political narratives, including false claims about COVID-19 and electoral fraud. The same campaign was run on Twitter and Facebook, and both platforms suspended some of the accounts following queries from Stanley-Becker. The report was based in part on a preliminary analysis we conducted at the request of The Post. In this brief we provide further details about our analysis.

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UPDATE: BotSlayer tool to expose disinformation networks

September 18, 2020Fil, NaN, Newsbotometer, misinformation, OSoMe, social bots, social media, social networks, software, toolfil

We are excited to announce the new v.1.3 of BotSlayer, our OSoMe cloud tool that lets journalists, researchers, citizens, & civil society organizations track narratives and detect potentially coordinated inauthentic information networks on Twitter in real-time. Improvements and new features include better stability, a new alert system, a Mac installer, and many additions to the interface. This version is released in time for those who would like to use BotSlayer to monitor #Election2020 manipulation.

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Knight Fellows

August 21, 2020Fil, NaN, Newsfellowship, misinformation, OSoMefil

Harry Yan matt_deverna 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 @ NetSci 2020

July 10, 2020Fil, NaN, News, Santonetwork science, talksDiogo Pacheco

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.

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