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Authors: Nikos Kapellas and Sarantos Kapidakis

Affiliation: Department of Archival, Library and Information Studies, University of West Attica, Ag. Spyridonos 28 12243, Athens, Greece

Keyword(s): Greek News Media, News Events, News Articles, Similarity Analysis, Cosine Similarity.

Abstract: Online news media usually cover the same news events. It would be interesting to understand, how similar are the descriptions of these events. In other words to explore how a distinct news event, is described by different news media. Can we safely conclude when two or more event descriptions refer to the same event? This research aims to investigate similarities in Greek news articles and provide new data on the field, as there is no relevant research. To do so, news article’s text is extracted, processed and analyzed with automated methods. To establish an understanding of similarity, three similarity settings are explored and special focus is given in examining the degree of similarity between news articles that cover the same event. In some cases results are inconclusive, while in others results show that groups of news media share the exact same articles with little or no modifications at all. The similarity analysis of news articles is a complex task and relies on many different factors that need to be addressed. (More)

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Paper citation in several formats:
Kapellas, N. and Kapidakis, S. (2022). A Text Similarity Study: Understanding How Differently Greek News Media Describe News Events. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD; ISBN 978-989-758-614-9; ISSN 2184-3228, SciTePress, pages 245-252. DOI: 10.5220/0011589700003335

@conference{keod22,
author={Nikos Kapellas. and Sarantos Kapidakis.},
title={A Text Similarity Study: Understanding How Differently Greek News Media Describe News Events},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD},
year={2022},
pages={245-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011589700003335},
isbn={978-989-758-614-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD
TI - A Text Similarity Study: Understanding How Differently Greek News Media Describe News Events
SN - 978-989-758-614-9
IS - 2184-3228
AU - Kapellas, N.
AU - Kapidakis, S.
PY - 2022
SP - 245
EP - 252
DO - 10.5220/0011589700003335
PB - SciTePress