A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset

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Bahmanyar Razieh; Khanjari Miyaneh Eynolla

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2024 | Issue:10

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Title

A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset

Author(s)

Bahmanyar Razieh | Khanjari Miyaneh Eynolla

Keywords

Fake news

Transformer

Sentiment analysis

Topic modeling

Hate speech

Abstract

According to the number of users on social media platforms and the number of followers of published content, Fake news in social media could adversely affect society and governments. In this paper, a new approach to Fake news detection is presented. Our approach is to provide a hybrid model in order to incorporate different types of features each of which is extracted by the corresponding component in the model. A Transformer model generates the input of each component, namely Sentiment analysis, Hate speech detection, and Topic modeling. Thereafter, a combination of hidden layers is performed through concatenation, which is then fed into the final classifier used for Fake news prediction. We evaluated the proposed model by collecting 2500 Persian data (related to COVID-19) from the social networks complemented by various preprocessing tasks. The results demonstrate a higher accuracy (87%) for the proposed approach compared to the standard baselines.

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APA: Copy

Bahmanyar, Razieh, & Khanjari Miyaneh, Eynolla. (2024). A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147359/en

Vancouver: Copy

Bahmanyar Razieh, Khanjari Miyaneh Eynolla. A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset. 2024. Available from: https://sid.ir/paper/1147359/en

IEEE: Copy

Razieh Bahmanyar, and Eynolla Khanjari Miyaneh, “A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147359/en

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