Bio

Motahhare Eslami is a 4th year PhD candidate at Computer Science department, University of Illinois at Urbana-Champaign. Her research interests are in social computing, human computer interaction and data mining areas. She is interested in performing research to analyze and understand people’s behavior in online social networks. Her recent work has focused on the effects of feed personalization in social media and how the awareness of filtering algorithm’s existence affects users’ perception and behavior. Her work has published at prestigious conferences and also appeared internationally in the press-in the Washington Post, TIME, MIT Technology Review, New Scientist, the BBC, CBC Radio, Oglobo (a prominent Brazilian newspaper), numerous biogs, Fortune, and more. Motahhare has been nominated as a Google PhD Fellowship Nominee (2015) by University of Illinois as one of the two students from the entire College of Engineering. Her research has received honorable mention award at Facebook Midwest Regional Hackathon 2013 and the best paper award at CHI 2015.

Reasoning about Invisible Algorithms in News Feeds

Reasoning about Invisible Algorithms in News Feeds

Our daily digital life is full of algorithmically selected content such as social media feeds, recommendations and personalized search results. These algorithms have great power to shape users’ experiences, yet users are often unaware of their presence. Whether it is useful to give users insight into these algorithms’ existence or functionality and how such insight might affect their experience are open questions. To address them, we conducted a user study with 40 Facebook users to examine their perceptions of the Facebook News Feed curation algorithm. Surprisingly, more than half of the participants (62.5%) were not aware of the News Feed curation algorithm’s existence at all. Initial reactions for these previously unaware participants were surprise and anger. We developed a system, FeedVis, to reveal the difference between the algorithmically curated and an unadulterated News Feed to users, and used it to study how users perceive this difference. Participants were most upset when close friends and family were not shown in their feeds. We also found participants often attributed missing stories to their friends’ decisions to exclude them rather than to Facebook News Feed algorithm. By the end of the study, however, participants were mostly satisfied with the content on their feeds. Following up with participants two to six months after the study, we found that for most, satisfaction levels remained similar before and after becoming aware of the algorithm’s presence, however, algorithmic awareness led to more active engagement with Facebook and bolstered overall feelings of control on the site.