Author archives

Filippo Menczer is a Luddy distinguished professor of informatics and computer science, and the director of the Observatory on Social Media at Indiana University, Bloomington. He holds a Laurea in Physics from the Sapienza University of Rome and a Ph.D. in Computer Science and Cognitive Science from the University of California, San Diego. Dr. Menczer is a Fellow of the ACM and a board member of the IU Network Science Institute. He previously served as division chair in the IUB School of Informatics and Computing, director of the Center for Complex Networks and Systems Research, visiting scientist at Yahoo Research, Fellow of the Institute for Scientific Interchange Foundation in Torino, Italy, and Fellow-at-large of the Santa Fe Institute. He has been the recipient of Fulbright, Rotary Foundation, and NATO fellowships, and a Career Award from the National Science Foundation. His research, supported by the NSF, DoD, McDonnell Foundation, Craig Newman Philanthropies, and Knight Foundation, focuses on Web and data science, social network analysis, social computation, Web mining, and modeling of complex information networks. His work on the spread of information and misinformation in social media has been covered in many US and international news sources, including The New York Times, Wall Street Journal, Washington Post, NPR, PBS, CNN, BBC, Economist, Guardian, Atlantic, Reuters, Science, and Nature. Menczer received multiple service awards and currently serves as associate editor of the Network Science journal and on the editorial boards of EPJ Data Science, PeerJ Computer Science, and HKS Misinformation Review.

How foreign operations are manipulating social media to influence your views

Filippo Menczer and his colleagues study influence campaigns and design technical solutions – algorithms – to detect and counter them. State-of-the-art methods developed in our center use several indicators of this type of online activity, which researchers call inauthentic coordinated behavior. They identify clusters of social media accounts that post in a synchronized fashion, amplify the same groups of users, share identical sets of links, images or hashtags, or perform suspiciously similar sequences of actions.

Subjects: AI, Competitive Intelligence, Legal Research, Search Engines, Social Media