A study of tweet veracity to separate rumours from counter-rumours

Alton Y.K. Chua; Snehasish Banerjee

A study of tweet veracity to separate rumours from counter-rumours

The York Management School

Research output: Contribution to conference › Paper › peer-review

Abstract

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 is highlighted.

Original language	English
Pages	1-8
Number of pages	9
Publication status	Published - 2017
Event	International Conference on Social Media & Society - Toronto, Canada Duration: 28 Jul 2017 → 30 Jul 2017 https://smsociety17.sched.com/

Conference

Conference	International Conference on Social Media & Society
Country/Territory	Canada
City	Toronto
Period	28/07/17 → 30/07/17
Internet address	https://smsociety17.sched.com/

Cite this

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title = "A study of tweet veracity to separate rumours from counter-rumours",

abstract = "Rumours are known to propagate easily through computer-mediated communication channels such as Twitter. Their outbreak is often followed by the spread of {\textquoteleft}counter-rumours{\textquoteright}, which are messages that debunk rumours. The probability of a tweet to be a counter-rumour is referred to as {\textquoteleft}tweet veracity{\textquoteright}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{\textquoteright} profile. The investigation focuses on the death hoax case of Singapore{\textquoteright}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{\textquoteright} duration of membership, and number of followers. The significance of these findings is highlighted.",

author = "Chua, {Alton Y.K.} and Snehasish Banerjee",

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T1 - A study of tweet veracity to separate rumours from counter-rumours

AU - Chua, Alton Y.K.

AU - Banerjee, Snehasish

PY - 2017

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N2 - 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 is highlighted.

AB - 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 is highlighted.

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