Rumors and rumor corrections on Twitter: Studying message characteristics and opinion leadership

Abstract

As rumors often ripple across the cyberspace, posting rumor corrections on social media can bring about social good by spreading the truth. However, rumors and rumor corrections are not easily distinguishable from one another. Therefore, this paper investigates how three message characteristics, namely, the use of emotions, clarity and credible source attribution, can predict message veracity on social media. Message veracity denotes whether a message is a rumor or a rumor correction. In addition, the paper further examines the extent to which opinion leadership moderates the relation between message characteristics and message veracity. Set against the context of the death hoax of Singapore's first Prime Minister Lee Kuan Yew in March 2015, data for this paper came from Twitter. Analysis involved binary logistic regression. All the three message characteristics predicted veracity. Rumor corrections were characterized by lower use of emotions, higher clarity, and higher credible source attribution compared with rumors. Furthermore, opinion leadership moderated the relation between the use of emotions and message veracity as well as that between credible source attribution and message veracity.

Analysis of User-Generated Comments on Rumor Correction YouTube Videos

“…This research makes the following contributions. On the theoretical front, it extends the limited literature on rumor corrections [3,12,14] by providing insights into the effectiveness of video rumor corrections on social media. One of the few works on online rumors and corrections to be conducted in the context of Indonesia, it also examines users' responses in terms of online aggression.…”

“…Social media channels are also used to spread rumor corrections. For this research, rumor corrections refer to messages that debunk false rumors and provide explanations to strengthen the truthiness of the rebuttals [12,14,15].…”

“…Although rumor corrections are intended to debunk rumors [14,15], they might not always work effectively [16,17]. Rumor corrections sometimes even backfire, which is explained by what is known as the backfire effect-the phenomenon whereby corrective evidence contradicts individuals' prior beliefs and hence ironically strengthens the truthiness of rumors rather than that of rumor corrections [18].…”

Rumor Detection in Social Media with User Information Protection

“…In [1], Rumor is defined as stimulating information or news which is not officially confirmed yet by any mainstream news media or relevant stakeholder but already got attention by people and has spread quickly from person to person. Rumor can also be defined as unverified but contextually relevant online messages which propagate fast and wide when ambiguity rises [2]. From the above two definitions, two characteristics of the rumor are visible to us.…”

“…Not only that, sudden rumor may create public anxiety and make the state unrest. For example, the death hoax of Singapore's first Prime Minister Lee Kuan Yew in March 2015 put the whole nation in deep sadness and increased public anxiety [2]. Even we have witnessed the impact of using social media by a huge community and spreading rumored news in US President Election 2016 [7].…”