#4708. Rumor conversations detection in twitter through extraction of structural features

August 2026publication date
Proposal available till 23-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Communication;
Business, Management and Accounting (miscellaneous);
Information Systems;
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Abstract:
Twitter is one of the most popular and renowned online social networks spreading information which although dependable could lead to spreading improbable and misleading rumours causing irreversible damage to individuals and society. In the present paper, a novel approach for detecting rumour-based conversations of various world events such as real-world emergencies and breaking news on Twitter is investigated. In this study, three aspects of information dissemination including linguistic style used to express rumours, characteristics of people involved in propagating information and structural features are studied. Structural features include features of reply tree and user graph. These features provide valuable clues on how a source tweet is transmitted and responds over time. Experimental results indicate that the new features are effective in detecting rumours and that the proposed method is better than other methods as F1-score increased by 4%. Implementation of the proposed method was carried out on Twitter datasets collected during five breaking news stories.
Keywords:
Reply tree; Rumor detection; Twitter; User graph

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