Rumor Detection through Trustworthy People

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Mirzaghabarpour Kamyar; MOEINI ALI

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2020 | Issue:6

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Title

Rumor Detection through Trustworthy People

Author(s)

Mirzaghabarpour Kamyar | MOEINI ALI

Keywords

Detection

Rumor

Lie

Internet

Naïve Bayes

BERT Model

Trustworthy People

Abstract

Nowadays, guiding people toward correct and real information in a world full of Internet obscurity is considered a highly important challenge and an urgent need. The present work aims to propose a validation method to those looking to discover the truth and verify the announced news using the knowledge and information of Trustworthy People. In this method, the Trustworthy People will first be identified based on the user-defined topic, then, it is discussed with them to determine if they have spoken about. Eventually, the similarity between the user-generated content (UGC) and Trustworthy People-stated words in measured using the BERT method, and then, the system determines the extent to which UGC is false or true.

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APA: Copy

Mirzaghabarpour, Kamyar, & MOEINI, ALI. (2020). Rumor Detection through Trustworthy People. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949281/en

Vancouver: Copy

Mirzaghabarpour Kamyar, MOEINI ALI. Rumor Detection through Trustworthy People. 2020. Available from: https://sid.ir/paper/949281/en

IEEE: Copy

Kamyar Mirzaghabarpour, and ALI MOEINI, “Rumor Detection through Trustworthy People,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2020, [Online]. Available: https://sid.ir/paper/949281/en

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