Details
| Original language | English |
|---|---|
| Article number | 3550357 |
| Journal | ACM transactions on the web |
| Volume | 16 |
| Issue number | 4 |
| Publication status | Published - 16 Nov 2022 |
| Externally published | Yes |
Abstract
With the increasing use of Twitter for encouraging users to instigate violent behavior with hate and racial content, it becomes necessary to investigate the uniqueness in the dynamics of the spread of tweets made during violent communal incidents and the challenges they pose in early identification of potential viral content. In this article, we study the spread of the tweets made during several violent communal incidents along four major dimensions - the underlying follower network of the users, their structural and engagement characteristics, the cascades, and the cognitive aspects of the content, each of which plays a vital role in the spread of content. Using large public and collected data, we compare these features with tweets related to other subjects from several major domains, such as non-violent political events, celebrities, and technology, that contribute to a large fraction of the viral content over Twitter. We discover that while the spread of cascades and the users involved may provide strong early evidence of the viral content for several domains, the early phases of the spread of viral tweets related to violent communal incidents are characterized by cascades with protracted growth involving fringe or low-importance users, which would possibly make early prediction difficult. Our findings indicate that an interplay of certain network and cascade properties, together with the cognitive characteristics of tweets and the behavioral patterns of the engaging users, may provide stronger early indicators of the virality of this content.
Keywords
- causality analysis, communal incidents, Social media, social network analysis, Twitter, virality prediction
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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In: ACM transactions on the web, Vol. 16, No. 4, 3550357, 16.11.2022.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Spotting Flares
T2 - The Vital Signs of the Viral Spread of Tweets Made During Communal Incidents
AU - Upadhyaya, Apoorva
AU - Chandra, Joydeep
N1 - Publisher Copyright: © 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2022/11/16
Y1 - 2022/11/16
N2 - With the increasing use of Twitter for encouraging users to instigate violent behavior with hate and racial content, it becomes necessary to investigate the uniqueness in the dynamics of the spread of tweets made during violent communal incidents and the challenges they pose in early identification of potential viral content. In this article, we study the spread of the tweets made during several violent communal incidents along four major dimensions - the underlying follower network of the users, their structural and engagement characteristics, the cascades, and the cognitive aspects of the content, each of which plays a vital role in the spread of content. Using large public and collected data, we compare these features with tweets related to other subjects from several major domains, such as non-violent political events, celebrities, and technology, that contribute to a large fraction of the viral content over Twitter. We discover that while the spread of cascades and the users involved may provide strong early evidence of the viral content for several domains, the early phases of the spread of viral tweets related to violent communal incidents are characterized by cascades with protracted growth involving fringe or low-importance users, which would possibly make early prediction difficult. Our findings indicate that an interplay of certain network and cascade properties, together with the cognitive characteristics of tweets and the behavioral patterns of the engaging users, may provide stronger early indicators of the virality of this content.
AB - With the increasing use of Twitter for encouraging users to instigate violent behavior with hate and racial content, it becomes necessary to investigate the uniqueness in the dynamics of the spread of tweets made during violent communal incidents and the challenges they pose in early identification of potential viral content. In this article, we study the spread of the tweets made during several violent communal incidents along four major dimensions - the underlying follower network of the users, their structural and engagement characteristics, the cascades, and the cognitive aspects of the content, each of which plays a vital role in the spread of content. Using large public and collected data, we compare these features with tweets related to other subjects from several major domains, such as non-violent political events, celebrities, and technology, that contribute to a large fraction of the viral content over Twitter. We discover that while the spread of cascades and the users involved may provide strong early evidence of the viral content for several domains, the early phases of the spread of viral tweets related to violent communal incidents are characterized by cascades with protracted growth involving fringe or low-importance users, which would possibly make early prediction difficult. Our findings indicate that an interplay of certain network and cascade properties, together with the cognitive characteristics of tweets and the behavioral patterns of the engaging users, may provide stronger early indicators of the virality of this content.
KW - causality analysis
KW - communal incidents
KW - Social media
KW - social network analysis
KW - Twitter
KW - virality prediction
UR - http://www.scopus.com/inward/record.url?scp=85146422132&partnerID=8YFLogxK
U2 - 10.1145/3550357
DO - 10.1145/3550357
M3 - Article
AN - SCOPUS:85146422132
VL - 16
JO - ACM transactions on the web
JF - ACM transactions on the web
SN - 1559-1131
IS - 4
M1 - 3550357
ER -