Publications

2018

  • The Government Spies Using Our Webcams: The Language of Conspiracy Theories in Online Discussions
    M. Samory, T. Mitra  |  CSCW 2018  |  paper  |  doi
    What do users talk about when they discuss conspiracy theories online? What are the recurring elements in their discussions? What do they tell us about the way users think? By focusing on three key elements - the conspiratorial agent, their actions, and their targets, this work answers the above questions.
  • FeedReflect: A toolkit for engaging users in active reflection on Twitter
    M. Bhuiyan, K. Zhang, K. Vick, M. Horning, & T. Mitra  |  Extended Abstract of CSCW 2018  |  paper  |  doi
    We introduced a system to engage users in careful evaluation of news credibility on Twitter.
  • Framing Hate with Hate Frames: Designing the Codebook
    S. Phadke, J. Lloyd, J. Hawdon, & T. Mitra  |  Extended Abstract of CSCW 2018  |  paper  |  doi
    By using Snow and Benfords framing theory we establish a coding scheme for analyzing characteristics of hate-group communications online.
  • Conspiracies Online: User discussions in a Conspiracy Community Following Dramatic Events
    M. Samory, T. Mitra  |  ICWSM 2018  |  paper  |  doi
    By focusing on four tragic events and 10 years of discussions in a popular online conspiracy theory community on Reddit, we study the evolution of users’ tenures in the community and the effects of the events on their discusion dynamics.
  • Credibility and the Dynamics of Collective Attention
    T. Mitra, G. Wright & E. Gilbert  |  CSCW 2018 Online First  |  paper  |  doi
    Representing collective attention by the aggregate temporal signatures of an event’s reportage, we found that the amount of continued attention focused on an event provides information about its associated levels of perceived credibility.
  • Spread of Employee Engagement in a Large Organizational Network: A Longitudinal Analysis
    T. Mitra, M. Muller, N. Shami, A Golestani & M. Masli  |  CSCW 2018 Online First  |  paper  |  doi
    Using employees' organizational social media data and their workplace hierarchical network structure, we studied contagion across a large multinational corporation, focusing on an important workplace behavior – employee engagement.
  • Growth in Social Network Connectedness among Different Roles in Organizational Crowdfunding
    Michael Muller, T. Mitra, Werner Geyer  |  GROUP 2018  |  paper  |  doi
    In a large-scale organizational crowdfunding campaign, we found that people in different crowdfunding roles experience different degrees of growth in their social networks, during and after the campaign.

2017

  • A Parsimonious Language Model of Social Media Credibility Across Disparate Events
    T. Mitra, G. Wright & E. Gilbert  |  CSCW 2017  |  paper  |  doi
    We present a parsimonious model that maps language cues to perceived levels of credibility. Our results show that certain linguistic categories and their associated phrases are strong predictors surrounding disparate social media events. For example, hedge words and positive emotion words are associated with lower credibility.

2016

  • Understanding Anti-Vaccination Attitudes in Social Media
    T. Mitra, S. Counts & J. W. Pennebaker  |  ICWSM 2016  |  paper  |  doi
    By developing a statistical framework using survival analysis, we find that recovery on Tumblr is protracted. Only half of the population shows likelihood of recovery after four years, and a vast minority is not estimated to recover even at the end of six years.
  • Recovery Amid Pro-Anorexia: Analysis of Recovery in Social Media
    S. Chancellor & T. Mitra & M. Choudhury  |  CHI 2016  |  paper  |  doi
    By developing a statistical framework using survival analysis, we find that recovery on Tumblr is protracted. Only half of the population shows likelihood of recovery after four years, and a vast minority is not estimated to recover even at the end of six years.

2015

  • CREDBANK: A Large-scale Social Media Corpus With Associated Credibility Annotations
    T. Mitra & E. Gilbert  |  ICWSM 2015  |  paper  |  doi
    We present a parsimonious model that maps language cues to perceived levels of credibility. Our results show that certain linguistic categories and their associated phrases are strong predictors surrounding disparate social media events. For example, hedge words and positive emotion words are associated with lower credibility.
  • Comparing Person-and Process-centric Strategies for Obtaining Quality Data on Amazon Mechanical Turk
    T. Mitra, C.J. Hutto & E. Gilbert  |  CHI 2015  |  paper  |  doi
    We present a parsimonious model that maps language cues to perceived levels of credibility. Our results show that certain linguistic categories and their associated phrases are strong predictors surrounding disparate social media events. For example, hedge words and positive emotion words are associated with lower credibility.

2014

  • Modeling Factuality Judgments in Social Media Text
    S. Soni, T. Mitra, E. Gilbert & J. Eisenstein  |  ACL 2014  |  paper  |  doi
    As events unfold, journalists and political commentators use quotes — often indirect — to convey potentially uncertain information and claims from their sources and informants. By obtaining annotations of perceived certainty of quoted statements in Twitter and comparing the ability of linguistic and extra-linguistic features to predict readers’ assessment of the certainty, we find that readers are influenced by linguistic framing devices and do not consider other factors, e.g. sources, journalist.
  • The Language that Gets People to Give: Phrases that Predict Success on Kickstarter
    T. Mitra & E. Gilbert  |  CSCW 2014  |  paper  |  doi
    We explore the factors which lead to funding on Kickstarter. Applying natural language methods and statistical analysis techniques to a corpus of crowdfunded projects, we find that the language used in the project has surprising predictive power–accounting for 58.56% of the variance around successful funding. A closer look at the phrases shows they exhibit general persuasion principles.

2013

  • Analyzing Gossip in Workplace Email
    T. Mitra & E. Gilbert  |  ACM Newsletter Winter 2013  |  paper  |  doi
    Adopting the Enron email dataset and natural language techniques, we find that workplace gossip is common at all levels of the organizational hierarchy, with people most likely to gossip with their peers
  • Mechanical Turk is Not Anonymous.
    M. Lease, J. Hullman, J.P. Bigham, M.S. Bernstein, J. Kim, W.S. Lasecki, S. Bakhshi, T. Mitra & R.C. Miller.  |  Social Science Research Network 2013  |  paper  |  doi
    Adopting the Enron email dataset and natural language techniques, we find that workplace gossip is common at all levels of the organizational hierarchy, with people most likely to gossip with their peers

2013

  • Have You Heard?: How Gossip Flows Through Workplace Email
    T. Mitra & E. Gilbert  |  ICWSM 2012  |  paper  |  doi
    Gossip is fundamental to social life. Here, we present the first large-scale study of gossip in CMC, looking at email where someone is mentioned in the message body but not included on the recipient list. We find that gossip emails are often more negative and people have a greater likelihood of sending gossip messages to smaller audiences.
  • Cost, Precision, and Task Structure in Aggression-Based Arbitration for Minimalist Robot Cooperation
    T. Mitra & D. A. Shell  |  SAB 2012  |  paper  |  doi