News on Algorithms and Automation

‘Phrenology’ has an old-fashioned ring to it. It sounds like it belongs in a history book, filed somewhere between bloodletting and velocipedes. We’d like to think that judging people’s worth based on the size and shape of their skull is a practice that’s well behind us. However, phrenology is once again rearing its lumpy head. […]

The topic of fake and satire news has drawn attention from both the public and the academic communities. Such misinformation has the potential for extremely negative impacts on individuals and society. Automatic fake and satire news detection is a challenging problem in deception detection, and it has tremendous real-word political and social impacts. In this […]

This final chapter borrows the concept of force of falsity from the famous Italian semiotician and novelist Umberto Eco to describe how manipulated information remains visible and accessible despite efforts to debunk it. In particular, search engine indexes are getting confused by disinformation and they too often fail to retrieve the authentic piece of content, […]

The U.S. health care system uses commercial algorithms to guide health decisions. Obermeyer et al. find evidence of racial bias in one widely used algorithm, such that Black patients assigned the same level of risk by the algorithm are sicker than White patients (see the Perspective by Benjamin). The authors estimated that this racial bias […]

The arm race between spambots and spambot-detectors is made of several cycles (or generations): a new wave of spambots is created (and new spam is spread), new spambot filters are derived and old spambots mutate (or evolve) to new species. Recently, with the diffusion of the adversarial learning approach, a new practice is emerging: to […]

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 […]

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Political bots are social media algorithms that impersonate political actors and interact with other users, aiming to influence public opinion. This study examines perceptions of bots with partisan personas by conducting an online experiment (N = 656) that examines the ability to differentiate bots from humans on Twitter. We explore how characteristics of the experiment […]

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. […]

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 […]

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 […]

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 […]

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