Synews: a synergy-based rumor verification system

Online social networks (OSNs) are now implied as an important source of news and information besides establishing social connections. However, such information sharing is not always authentic because people, sometimes, also share their perceptions and fabricated information on OSNs. Thus, verificati...

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Bibliographic Details
Published in:Social network analysis and mining 2024-03, Vol.14 (1), p.57
Main Authors: Sarfraz, Amber, Ahmad, Adnan, Zeshan, Furkh, Mirza, Hamid Turab
Format: Article
Language:English
Subjects:
Acceptance
Connectedness
Crowdsourcing
Election results
Empirical analysis
False information
Gossip
Information sharing
Machine learning
Natural language processing
News
Ontology
Presidential elections
Propagation
Public relations
Reliability
Reputation management
Self-efficacy
Semantic web
Semantics
Simulation
Social networks
Synergy
Verification
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Summary:Online social networks (OSNs) are now implied as an important source of news and information besides establishing social connections. However, such information sharing is not always authentic because people, sometimes, also share their perceptions and fabricated information on OSNs. Thus, verification of online posts is important to maintain reliability over this useful communication medium. To address this concern, multiple approaches have been investigated including machine learning, natural language processing, source authentication, empirical studies, web semantics, and modeling/simulations, but the problem still persists. This research proposes an effective synergy-based rumor verification method along with a weighted-mean reputation management system to mitigate the spread of rumors over OSN. The model was formally verified through Colored Petri-Nets while its semantic behavior was analyzed through ontologies. Moreover, a third-party Facebook application was developed for proof of concept, and users’ acceptance and usability analysis was performed through Technology Acceptance Model and Self-Efficacy scale. The results indicate that the proposed approach can be used as an effective tool for the identification of rumors and it has the potential to improve the quality of users’ online experience.
ISSN:1869-5450
1869-5469
DOI:10.1007/s13278-024-01214-z