research-article

The Retransmission of Rumor-related Tweets: Characteristics of Source and Message

Authors:

Alton Y. K. Chua,

Cheng-Ying Tee,

Augustine Pang,

Ee-Peng LimAuthors Info & Claims

SMSociety '16: Proceedings of the 7th 2016 International Conference on Social Media & Society

Article No.: 22, Pages 1 - 10

https://doi.org/10.1145/2930971.2930994

Published: 11 July 2016 Publication History

Abstract

This paper investigates the characteristics of rumor-related tweets that would attract retransmission. Drawing on the uses and gratifications (U & G) and influential users' theories, it proposes a rumor retransmission model which comprises variables associated to the source and the message of the tweets. From a total of 5,885 rumor-related tweets about the death of the founding Prime Minister of Singapore Lee Kuan Yew collected, 800 original tweets without a "RT" prefix were selected for analysis. It was found that the experience and connectivity of the source are correlated to retransmission. The age of the account and number of followers have positive relationships with retransmission, while the number of tweets posted and number of friends have negative relationships. For characteristics of the message, attractiveness and expressions of sense of belonging are positively related to retransmission but the use of directed messages and medium-specific features, namely hashtags and URLs have negative relationships with retransmission. Messages with low level of emotions trigger more retweets than those without emotional expressions and those that are highly emotional. Results could suggest that in inauspicious contexts such as the rumored death of a political figure, Twitter users appear to favor less complex content and seem to be discerning and rational in making retransmission decisions.

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SMSociety '16: Proceedings of the 7th 2016 International Conference on Social Media & Society

July 2016

220 pages

ISBN:9781450339384

DOI:10.1145/2930971

Editors:
Anatoliy Gruzd
Ryerson University
,
Jenna Jacobson
University of Toronto
,
Philip Mai
Ryerson University
,
Evelyn Ruppert
University of London
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Dhiraj Murthy
University of London

Copyright © 2016 ACM.

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SMSociety '16: 2016 International Conference on Social Media & Society

July 11 - 13, 2016

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https://dl.acm.org/doi/10.1145/3512936
Dong WTao JXia XXu HYe LJiang PLiu Y(2020)The Relationship between Public Emotions and Rumors Spread during the COVID-19 Epidemic in China (Preprint)Journal of Medical Internet Research10.2196/21933Online publication date: 29-Jun-2020
https://doi.org/10.2196/21933
Varshney CJain STripathi V(2020)An Overview of Rumour Detection based on Social Media2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT49239.2020.9225567(1-6)Online publication date: Jul-2020
https://doi.org/10.1109/ICCCNT49239.2020.9225567
Maseri ANorman AEke CAhmad AMolok N(2020)Socio-Technical Mitigation Effort to Combat Cyber Propaganda: A Systematic Literature MappingIEEE Access10.1109/ACCESS.2020.29946588(92929-92944)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2994658
Wu PLi XShen SHe D(2020)Social media opinion summarization using emotion cognition and convolutional neural networksInternational Journal of Information Management: The Journal for Information Professionals10.1016/j.ijinfomgt.2019.07.00451:COnline publication date: 1-Jul-2020
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Jang YPark CSeo Y(2019)Fake News Analysis Modeling Using Quote RetweetElectronics10.3390/electronics81213778:12(1377)Online publication date: 20-Nov-2019
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Zubiaga AAker ABontcheva KLiakata MProcter R(2018)Detection and Resolution of Rumours in Social MediaACM Computing Surveys10.1145/316160351:2(1-36)Online publication date: 20-Feb-2018
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