Getting insights from news data mining: a case of BBC's counter-terrorism news text analysis

Jia Li; Miaoyutian Jia; Qian Liu; Yong Fu; Qiuyi Chen

doi:10.1117/12.2653824

8 December 2022 Getting insights from news data mining: a case of BBC's counter-terrorism news text analysis

Jia Li, Miaoyutian Jia, Qian Liu, Yong Fu, Qiuyi Chen

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124740I (2022) https://doi.org/10.1117/12.2653824
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Data mining plays an important role in getting insights from news text. This study collected 695,051 English-language news reports on terrorism and counter-terrorism from March 2017 to March 2018 in BBC news and conducted a text analysis with LDA topic modeling. 20 topics and five themes were classified, and it was disclosed that major themes include that: (1) BBC focused on constructing local discourse structure, (2) Comparing the news reports at home and abroad, and (3) Historical origins, the development in ancient and modern times and a trial of strength between different countries.

Citation Download Citation

Jia Li, Miaoyutian Jia, Qian Liu, Yong Fu, and Qiuyi Chen "Getting insights from news data mining: a case of BBC's counter-terrorism news text analysis", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124740I (8 December 2022); https://doi.org/10.1117/12.2653824

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