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A natural language processing technique to identify exaggerated news titles

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dc.contributor.author Sefara, Tshephisho J
dc.contributor.author Rangata, Mapitsi R
dc.date.accessioned 2023-10-13T10:10:15Z
dc.date.available 2023-10-13T10:10:15Z
dc.date.issued 2023-10
dc.identifier.citation Sefara, T.J. & Rangata, M.R. 2023. A natural language processing technique to identify exaggerated news titles. http://hdl.handle.net/10204/13147 . en_ZA
dc.identifier.issn 2367-3370
dc.identifier.uri https://doi.org/10.1007/978-981-99-5166-6_64
dc.identifier.uri http://hdl.handle.net/10204/13147
dc.description.abstract Exaggerated news titles are used to deceive news readers and spread misleading information. This paper presents a new natural language processing (NLP) technique that identifies exaggerated news titles. The technique uses Jaccard similarity as a pre-processing step to filter out unrelated articles. The technique then applies text summarisation on the content of the news article to create a new title. Lastly, the technique applies cosine similarity to compare similar articles between the article title and the newly generated titles. The output is the classification of the news articles using the output of cosine similarity. This technique performed well in major South African news articles. en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri https://link.springer.com/chapter/10.1007/978-981-99-5166-6_64 en_US
dc.source Lecture Notes in Networks and Systems, 757 (paper presented at ICICCT 2023: Inventive Communication and Computational Technologies) en_US
dc.subject Text similarity en_US
dc.subject Text summarisation en_US
dc.subject Natural Language Processing en_US
dc.subject Cosine similarity en_US
dc.subject Jaccard similarity en_US
dc.title A natural language processing technique to identify exaggerated news titles en_US
dc.type Conference Presentation en_US
dc.description.pages 12 en_US
dc.description.note Paper presented at the ICICCT 2023: Inventive Communication and Computational Technologies. This is the preprint version of the published item. en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea Data Science en_US
dc.identifier.apacitation Sefara, T. J., & Rangata, M. R. (2023). A natural language processing technique to identify exaggerated news titles. http://hdl.handle.net/10204/13147 en_ZA
dc.identifier.chicagocitation Sefara, Tshephisho J, and Mapitsi R Rangata. "A natural language processing technique to identify exaggerated news titles." <i>Lecture Notes in Networks and Systems, 757 (paper presented at ICICCT 2023: Inventive Communication and Computational Technologies)</i> (2023): http://hdl.handle.net/10204/13147 en_ZA
dc.identifier.vancouvercitation Sefara TJ, Rangata MR, A natural language processing technique to identify exaggerated news titles; 2023. http://hdl.handle.net/10204/13147 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Sefara, Tshephisho J AU - Rangata, Mapitsi R AB - Exaggerated news titles are used to deceive news readers and spread misleading information. This paper presents a new natural language processing (NLP) technique that identifies exaggerated news titles. The technique uses Jaccard similarity as a pre-processing step to filter out unrelated articles. The technique then applies text summarisation on the content of the news article to create a new title. Lastly, the technique applies cosine similarity to compare similar articles between the article title and the newly generated titles. The output is the classification of the news articles using the output of cosine similarity. This technique performed well in major South African news articles. DA - 2023-10 DB - ResearchSpace DP - CSIR J1 - Lecture Notes in Networks and Systems, 757 (paper presented at ICICCT 2023: Inventive Communication and Computational Technologies) KW - Text similarity KW - Text summarisation KW - Natural Language Processing KW - Cosine similarity KW - Jaccard similarity LK - https://researchspace.csir.co.za PY - 2023 SM - 2367-3370 T1 - A natural language processing technique to identify exaggerated news titles TI - A natural language processing technique to identify exaggerated news titles UR - http://hdl.handle.net/10204/13147 ER - en_ZA
dc.identifier.worklist 27163 en_US


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