Algorithms and Automation
Automation is a crucial tool of many disinformation campaigns, while algorithms are the complex sets of rules that affect what we see online. Because algorithms are designed by humans, they may reproduce biases and ideologies while making those biases seem natural. Researchers are also exploring how algorithms and automation can be used to study misinformation or counter malicious uses of the same kinds of tools.
Live Research Review
Teaching & Learning
Explore course modules, handouts, teaching tools and syllabi about dis- and misinformation.
Latest News on Algorithms and Automation
Misinformation is one of the most critical issues of recent years, which does harm to democracy, economics, and society. Despite all the attempts, traditional techniques are not powerful enough to address new challenges arising from the 4Vs (volume, variety, velocity, veracity) of Big Data. First, large volumes of data on social platforms are generated at […]
By Karl Aberer, Ioannis Katakis, Quoc Viet Hung (Henry) Nguyen, & Hongzhi Yin
We are looking for a postdoctoral fellow to join the Observatory on Social Media (OSoMe, pronounced awe•some) at Indiana University Bloomington (IUB) under the direction of Filippo Menczer. The research will address the intersection of computing, network, data, and media sciences with a focus on (mis/dis)information diffusion and the detection and countering of online manipulation. […]
By CNetS
Over the long Memorial Day weekend, a Twitter storm blew in about bots, those little automatic programs that talk to us in the digital dimension as if they were human. What first caught the attention of Darius Kazemi was the headline on an article from NPR, “Researchers: Nearly Half of Accounts Tweeting About Coronavirus Are […]
By Siobhan Roberts
Long before the coronavirus pandemic, the tech industry yearned to prove its indispensability to the world. Its executives liked to describe their companies as “utilities.” They came by their self-aggrandizement honestly: The founding fathers of Big Tech really did view their creations as essential, and essentially good. In recent years, however, our infatuation with these creations […]
By Franklin Foer
Are machine-learning algorithms biased, wrong, and racist? Let citizens decide. Essentially rule-based structures for making decisions, machine-learning algorithms play an increasingly large role in our lives. They suggest what we should read and watch, whom we should date, and whether or not we are detained while awaiting trial. Their promise is huge–they can better detect […]
By Federica Carugati
Misinformation is one of the most critical issues of recent years, which does harm to democracy, economics, and society. Despite all the attempts, traditional techniques are not powerful enough to address new challenges arising from the 4Vs (volume, variety, velocity, veracity) of Big Data. First, large volumes of data on social platforms are generated at […]
By Karl Aberer, Ioannis Katakis, Quoc Viet Hung (Henry) Nguyen, & Hongzhi YinWe are looking for a postdoctoral fellow to join the Observatory on Social Media (OSoMe, pronounced awe•some) at Indiana University Bloomington (IUB) under the direction of Filippo Menczer. The research will address the intersection of computing, network, data, and media sciences with a focus on (mis/dis)information diffusion and the detection and countering of online manipulation. […]
By CNetSOver the long Memorial Day weekend, a Twitter storm blew in about bots, those little automatic programs that talk to us in the digital dimension as if they were human. What first caught the attention of Darius Kazemi was the headline on an article from NPR, “Researchers: Nearly Half of Accounts Tweeting About Coronavirus Are […]
By Siobhan RobertsLong before the coronavirus pandemic, the tech industry yearned to prove its indispensability to the world. Its executives liked to describe their companies as “utilities.” They came by their self-aggrandizement honestly: The founding fathers of Big Tech really did view their creations as essential, and essentially good. In recent years, however, our infatuation with these creations […]
By Franklin FoerAre machine-learning algorithms biased, wrong, and racist? Let citizens decide. Essentially rule-based structures for making decisions, machine-learning algorithms play an increasingly large role in our lives. They suggest what we should read and watch, whom we should date, and whether or not we are detained while awaiting trial. Their promise is huge–they can better detect […]
By Federica Carugati