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Session Overview
Session
Online Incivility and Contextual Factors: Data-Driven Detection and Analysis - hosted by SIG-SM
Time:
Sunday, 29/Oct/2023:
2:00pm - 3:30pm

Location: Bouzy, 1st Floor, Novotel


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Presentations
ID: 169 / [Single Presentation of ID 169]: 1
Panels
90 minutes
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies
Topics: Social Media and Social Computing (social media & analytics; information gatekeeping on social media; network theories & visualization; community informatics; online communities; digital youth; social informatics & computing; socio-technical design)
Keywords: social media, social media analysis, data analysis, data visualization, data collection

Online Incivility and Contextual Factors: Data-Driven Detection and Analysis - hosted by SIG-SM

Catherine Dumas1, Souvick Ghosh2, Lingzi Hong3, Amir Karami4, Priya Vaidya5

1State University of New York at Albany, USA; 2San Jose State University, USA; 3University of North Texas, USA; 4University of Alabama at Birmingham, USA; 5Aligarh Muslim University, India

Uncivil behaviors like rude or hate speech have been a persistent problem on social media, which could lead to negative user experience or even affect the psychological well-being of users. Automatic detection and moderation of such behaviors are critical to creating a supportive online community for effective user communication and positive user experience. In this tutorial, we propose methods to study online incivility, which includes data collection from a social media platform, i.e., Reddit, automatic detection of incivility with pretrained deep learning classifiers, and statistical and visual analytical methods to investigate the combination of community characteristics and users’ interactive patterns that relate to the occurrences of incivility. Similar methods can be applied to understand other information misbehaviors online, such as misinformation, dissemination of rumors, and cyberstalking. Hosted by SIG-SM.



 
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