About

Dr. Kate Kenski is a Professor in the Department of Communication at the University of Arizona. She holds a Ph.D. from the University of Pennsylvania, obtained in 2006. Her teaching areas include political communication, public opinion, and research methods. Prior to her current position, she was a senior analyst at the Annenberg Public Policy Center at the University of Pennsylvania. Her research focuses on social media and incivility, gender and politics, and the development of online platforms that enhance users’ reasoning quality. Dr. Kenski has co-authored books on the 2008 election and campaign dynamics, and she is a co-editor of The Oxford Handbook of Political Communication. She has published extensively in various academic journals, contributing over 70 book chapters, articles, and research notes. She is actively involved in research that examines the effects of media on political processes and public discourse.

Research topics

• Political Science
• Social psychology
• Psychology
• Machine Learning
• Artificial Intelligence
• Law
• Sociology
• Natural Language Processing
• Computer Science
• Public relations
• World Wide Web

Selected publications

• Misinformation exposure per se may not trigger cynicism, but perceived prevalence of misinformation and hostile information does

  Information Communication & Society · 2026-02-04

  articleSenior author
  PublisherDOI

• The Irony of Sophisticated Citizens and Misinformation: Explaining How People with High Need for Cognition Become Politically Cynical

  Digital Journalism · 2025-09-08

  article
  PublisherDOI

• Incivility in Online Discussion as a Collective Phenomenon: A Dynamic Systems Perspective Examining Sequences of Uncivil Messages

  Social Media + Society · 2025-07-01 · 2 citations

  articleOpen access

  Drawing from dynamic systems theory, we examine how incivility is collectively constructed in an online discussion community. Using secondary data consisting of comments shared over a 3-week period to an online news community, we identified three sequences that reflect collective incivility practices. Whereas the persistent incivility sequence included a large proportion of uncivil comments, incivility occurred infrequently in the sporadic incivility sequence and not at all in the no incivility sequence. Once the persistent incivility or sporadic incivility sequences appeared, discussions were more likely to return to these sequences than the no incivility sequence. Contrary to our predictions, sequences containing incivility shaped discussion processes by depressing explicit expressions of agreement and disagreement. The results of this study demonstrate how the collective behavior of online community members contributes to the production and effects of incivility.

  PublisherDOI

• Reinforcing Cycles? Empirical Reflections on the Relationship Between Media Cynicism and Political Cynicism

  Mass Communication & Society · 2025-03-04 · 1 citations

  articleSenior author
  PublisherDOI

• Examining the Dynamics of Uncivil Discourse Between Sub-National Political Officials and the Public on Twitter

  Mass Communication & Society · 2024-02-06 · 2 citations

  article

  Despite agreement about the challenges posed by incivility for democratic discourse, much remains to be learned about how incivility manifests in interactions between the public and political elites. We examine the connections between top-down and bottom-up incivility among 22 local and state elected officials and the public over an 18-month period on Twitter. Our analyses show that incivility in a tweet from an elected official significantly increases the odds of incivility in subsequent tweets made by the public that are directed at the official. Similarly, the presence of incivility in tweets by the public directed at elected officials increases the odds of incivility in subsequent tweets made by officials. We discuss the implications of these findings for scholarship on incivility and political communication more broadly.

  PublisherDOI

• Incivility in 2020 Presidential Candidate Social Media Posts and Posts That Cite Them

  2024-02-12

  book-chapter1st authorCorresponding

  This chapter explores the presence of incivility via name-calling and vulgarity in 2020 presidential primary candidate tweets and the quote tweets reacting to them. Between August 1, 2019 and August 31, 2020, four Republican and 29 Democratic presidential primary candidates made 78,149 tweets, and incivility was not uncommon. Name-calling (8.9%) took place more than often vulgarity did (2.1%) in candidate tweets. Party and candidate differences in the use of incivility were detected. Republicans were more likely to name-call and use vulgarity than Democrats were. While Trump was a notable contributor to name-calling, he was not the sole Republican contributor to it, and he rarely used language identified as vulgar. Public reactions to candidate tweets were more likely to contain incivility than candidate tweets were. The presence of incivility in quote tweets was associated with the presence of incivility in the candidate tweets, suggesting that political candidates have the power to shape how members of the public choose to express themselves.

  PublisherDOI

• Detecting Antisocial Norms in Large-Scale Online Discussions

  2024-07-22 · 4 citations

  book-chapter

  This chapter develops a theoretical framework for investigating social norms in online discussions and applies it to study antisocial commenting in two datasets ten years apart. The thesis is that antisocial commenting is promoted through at least two different social processes. First, discussion contributors mimic one another, deploying antisocial comments after other contributors have done so. Second, contributors are responsive to “votes” of approval that they have received for prior instances of antisocial commenting. These two processes map onto a distinction made in the literature on social norms between descriptive and injunctive norms, and this analysis investigates both processes at the individual and collective levels. The chapter compares human annotations of antisocial commenting with several automated classifiers and provides evidence that the classifiers are well-suited for understanding the norms associated with antisocial online commenting. The framework can be applied to online discussions at scale and makes use of both the relational and temporal aspects of the digital trace data that are generated when people use the web and social media.

  PublisherDOI

• Copyright Page

  2023-02-16

  other

  Extract Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries. Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America. © Oxford University Press 2023 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above. You must not circulate this work in any other form

  PublisherDOI

• List of IOD Collaborative Members

  2023-02-16

  other

  Extract Democracy amid Crises is the work of the Annenberg IOD (Institutions of Democracy) Collaborative. Here we provide a brief biographical sketch for each of the members. ...

  PublisherDOI

• Candidate Evaluations and Social Media Following during the 2020 Presidential Campaign

  2023-05-11

  book-chapter1st authorCorresponding

  This study investigates the relationship between presidential candidate evaluations and following the candidates on five social media (SM) platforms: Facebook, Twitter, Instagram, Snapchat, and YouTube. Analyses of national survey data collected during the 2020 presidential campaign (N = 2,120) suggest that following a candidate on SM is positively associated with feelings toward that candidate, even after gender, age, race, education, party identification, and online news media use have been taken into consideration. Specifically, individuals who followed Trump on Facebook, Twitter, and/or YouTube supported him more than did those who did not follow him. Following Biden on Facebook, Twitter, Instagram, and/or Snapchat was positively associated with his feeling thermometer ratings after demographic variables, party identification, and online news media use were controlled. Moreover, we show that these positive relationships were more pronounced among those who did not identify with one of the major political parties. Following a candidate, however, was not necessarily associated with decreased support for the opposing candidate. Overall, our results highlight the importance of politicians’ use of social media during campaigns and suggest that following candidates on different SM platforms has unique relationships with candidate evaluations.

  PublisherDOI

Frequent coauthors

• Kathleen Hall Jamieson

  University of Pennsylvania

  31 shared

• Jennifer Stromer‐Galley

  28 shared

• James Folkestad

  25 shared

• Benjamin A. Clegg

  Duquesne University

  22 shared

• Rosa Mikeal Martey

  21 shared

• Brian McKernan

  19 shared

• Patrícia Rossini

  16 shared

• Kevin Coe

  14 shared

Education

• Ph.D., Annenberg School for Communication

  University of Pennsylvania

  2006

• M.A., Annenberg School for Communication

  University of Pennsylvania

  1999

• B.A., Rhetoric & Media Studies

  Willamette University

  1995