Dr. Marian-Andrei Rizoiu of University of Technology Sydney

Serious concerns have been raised about the role of ‘socialbots’ in manipulating public opinion and influencing the outcome of elections by retweeting partisan content to increase its reach. Here we analyze the role and influence of socialbots on Twitter by determining how they contribute to retweet diffusions. We collect a large dataset of tweets during the 1st U.S. presidential debate in 2016 and we analyze its 1.5 million users from three perspectives: user influence, political behavior (partisanship and engagement) and botness. First, we define a measure of user influence based on the user’s active contributions to information diffusions, i.e. their tweets and retweets. Next, we use partisan hashtag analysis to quantify user political polarization and engagement. Finally, we use the BotOrNot API to measure user botness (the likelihood of being a bot). We build a two-dimensional “polarization map” that allows for a nuanced analysis of the interplay between botness, partisanship and influence. We find that not only are socialbots more active on Twitter – starting more retweet cascades and retweeting more – but they are 2.5 times more influential than humans, and more politically engaged. Moreover, pro-Republican bots are both more influential and more politically engaged than their pro-Democrat counterparts.

Biography:

Dr. Marian-Andrei Rizoiu is lecturer with the University of Technology Sydney, leading the Behavioral Data Science group, studying the dynamics of human attention in the online environment. His research has made several key contributions, particularly to the areas of online popularity prediction and online privacy. For the past four years, he has been developing theoretical models for online information diffusion, which can account for complex social phenomena, such as the rise and fall of online popularity, the spread of misinformation or the adoption of disruptive technologies. Marian-Andrei has also worked on detecting the evolution of privacy loss over time. Marian-Andrei published in the most selective venues of the field (such as WWW, WSDM, ICWSM or CIKM) and his work has received significant media attention, including from the Wikimedia Foundation for the work concerning the privacy of Wikipedia editors (which featured in the March 2016 Wikimedia Research Showcase). See more at http://www.rizoiu.eu