Papers › A Model to Measure the Spread Power of Rumors

A Model to Measure the Spread Power of Rumors

18 Feb 2020arXiv:2002.07563archive 2025-07-28

Zoleikha Jahanbakhsh-Nagadeh, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Taymaz Akan, Meysam Asgari-Chenaghlu, Narjes Nikzad-Khasmakhi, Ali-Reza Feizi-Derakhshi, Mehrdad Ranjbar-Khadivi, Elnaz Zafarani-Moattar, Mohammad-Ali Balafar

With technologies that have democratized the production and reproduction of information, a significant portion of daily interacted posts in social media has been infected by rumors. Despite the extensive research on rumor detection and verification, so far, the problem of calculating the spread power of rumors has not been considered. To address this research gap, the present study seeks a model to calculate the Spread Power of Rumor (SPR) as the function of content-based features in two categories: False Rumor (FR) and True Rumor (TR). For this purpose, the theory of Allport and Postman will be adopted, which it claims that importance and ambiguity are the key variables in rumor-mongering and the power of rumor. Totally 42 content features in two categories "importance" (28 features) and "ambiguity" (14 features) are introduced to compute SPR. The proposed model is evaluated on two datasets, Twitter and Telegram. The results showed that (i) the spread power of False Rumor documents is rarely more than True Rumors. (ii) there is a significant difference between the SPR means of two groups False Rumor and True Rumor. (iii) SPR as a criterion can have a positive impact on distinguishing False Rumors and True Rumors.

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Rumour Detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Rumour Detection Sepehr_RumTel01 Jahanbakhsh-Nagadeh et al. F-Measure 0.828 #3 of 4 Archive leaderboard report

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