Conference proceeding
Many Faced Hate: A Cross Platform Study of Content Framing and Information Sharing by Online Hate Groups
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp 1-329
21 Apr 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Hate groups are increasingly using multiple social media platforms to promote extremist ideologies. Yet we know little about their communication practices across platforms. How do hate groups (or "in-groups"), frame their hateful agenda against the targeted group or the "out-group?" How do they share information? Utilizing "framing" theory from social movement research and analyzing domains in the shared links, we juxtapose the Facebook and Twitter communication of 72 Southern Poverty Law Center (SPLC) designated hate groups spanning five hate ideologies. Our findings show that hate groups use Twitter for educating the audience about problems with the out-group, maintaining positive self-image by emphasizing in-group's high social status, and for demanding policy changes to negatively affect the out-group. On Facebook, they use fear appeals, call for active participation in group events (membership requests), all while portraying themselves as being oppressed by the out-group and failed by the system. Our study unravels the ecosystem of cross-platform communication by hate groups, suggesting that they use Facebook for group radicalization and recruitment, while Twitter for reaching a diverse follower base.
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Details
- Title
- Many Faced Hate: A Cross Platform Study of Content Framing and Information Sharing by Online Hate Groups
- Creators
- Shruti Phadke - Virginia TechTanushree Mitra - Virginia TechACM
- Publication Details
- Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp 1-329
- Conference
- CHI '20: CHI Conference on Human Factors in Computing Systems
- Series
- ACM Conferences
- Publisher
- ACM
- Number of pages
- 13
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000695438100128
- Scopus ID
- 2-s2.0-85087883724
- Other Identifier
- 991021985095504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods