A Study of Tweet Veracity to Separate Rumours from Counter-Rumours

Rumours are known to propagate easily through computer-mediated communication channels such as Twitter. Their outbreak is often followed by the spread of 'counter-rumours', which are messages that debunk rumours. The probability of a tweet to be a counter-rumour is referred to as 'twe...

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Main Authors: Chua, Alton Yeow Kuan, Banerjee, Snehasish
Other Authors: Wee Kim Wee School of Communication and Information
Format: Conference or Workshop Item
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/87087
http://hdl.handle.net/10220/44319
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-870872020-03-07T12:15:48Z A Study of Tweet Veracity to Separate Rumours from Counter-Rumours Chua, Alton Yeow Kuan Banerjee, Snehasish Wee Kim Wee School of Communication and Information Proceedings of the 8th International Conference on Social Media & Society (SMSociety17) Information Quality Counter-rumor Rumours are known to propagate easily through computer-mediated communication channels such as Twitter. Their outbreak is often followed by the spread of 'counter-rumours', which are messages that debunk rumours. The probability of a tweet to be a counter-rumour is referred to as 'tweet veracity' in this paper. Since both rumours and counter-rumours are expected to contain claims of truth, the two might not be easily distinguishable. If Internet users fail to separate rumours from counter-rumours, the latter will not serve its purpose. Hence, this paper investigates the extent to which tweet veracity could be predicted by content as well as contributors' profile. The investigation focuses on the death hoax case of Singapore's first Prime Minister Lee Kuan Yew on Twitter. A total of 1,000 tweets (500 rumours + 500 counter-rumours) are analyzed using binomial logistic regression. Results indicate that tweet veracity could be predicted by clarity, proper nouns, visual cues, references to credible sources, as well as contributors' duration of membership, and number of followers. The significance of these findings are highlighted. MOE (Min. of Education, S’pore) Accepted version 2018-01-16T04:43:09Z 2019-12-06T16:34:52Z 2018-01-16T04:43:09Z 2019-12-06T16:34:52Z 2017 Conference Paper Chua, A. Y. K., & Banerjee, S. (2017). A Study of Tweet Veracity to Separate Rumours from Counter-Rumours. Proceedings of the 8th International Conference on Social Media & Society (SMSociety17), 4-. https://hdl.handle.net/10356/87087 http://hdl.handle.net/10220/44319 10.1145/3097286.3097290 en © 2017 Association for Computing Machinery (ACM). This is the author created version of a work that has been peer reviewed and accepted for publication by Proceedings of the 8th International Conference on Social Media & Society, Association for Computing Machinery. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1145/3097286.3097290]. 17 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Information Quality
Counter-rumor
spellingShingle Information Quality
Counter-rumor
Chua, Alton Yeow Kuan
Banerjee, Snehasish
A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
description Rumours are known to propagate easily through computer-mediated communication channels such as Twitter. Their outbreak is often followed by the spread of 'counter-rumours', which are messages that debunk rumours. The probability of a tweet to be a counter-rumour is referred to as 'tweet veracity' in this paper. Since both rumours and counter-rumours are expected to contain claims of truth, the two might not be easily distinguishable. If Internet users fail to separate rumours from counter-rumours, the latter will not serve its purpose. Hence, this paper investigates the extent to which tweet veracity could be predicted by content as well as contributors' profile. The investigation focuses on the death hoax case of Singapore's first Prime Minister Lee Kuan Yew on Twitter. A total of 1,000 tweets (500 rumours + 500 counter-rumours) are analyzed using binomial logistic regression. Results indicate that tweet veracity could be predicted by clarity, proper nouns, visual cues, references to credible sources, as well as contributors' duration of membership, and number of followers. The significance of these findings are highlighted.
author2 Wee Kim Wee School of Communication and Information
author_facet Wee Kim Wee School of Communication and Information
Chua, Alton Yeow Kuan
Banerjee, Snehasish
format Conference or Workshop Item
author Chua, Alton Yeow Kuan
Banerjee, Snehasish
author_sort Chua, Alton Yeow Kuan
title A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
title_short A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
title_full A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
title_fullStr A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
title_full_unstemmed A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
title_sort study of tweet veracity to separate rumours from counter-rumours
publishDate 2018
url https://hdl.handle.net/10356/87087
http://hdl.handle.net/10220/44319
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