Agenda Analysis of the Covid-19 News with Latent Dirichlet Allocation [Gizli Dirichlet Ayirimi ile Covid-19 Haberlerinin Gundem Analizi]
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Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study interprets the themes obtained as a result of the analysis of the internet news published during the Covid-19 pandemic in our country with Latent Dirichlet Allocation method. Apart from topic modeling, news documents were also subjected to category-based sentiment analysis and time-lapse graphics of published positive, negative and neutral news were shared. For this purpose, 37.724 news texts published in 5 different categories were collected. The period subject to analysis is December 2019 - February 2021. Although the effect of the virus has been alleviated at the moment, the themes that were on the agenda during the period when the effect of the virus was highest could be seen and the results were interpreted. © 2022 IEEE.
Açıklama
2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 -- 7 September 2022 through 9 September 2022 -- -- 183936
Anahtar Kelimeler
analysis of public agenda, covid-19, sentiment analysis, topic modeling, Statistics, Viruses, Allocation methods, Analyse of public agenda, Covid-19, Dirichlet, Latent Dirichlet allocation, Positive/negative, Sentiment analysis, Topic Modeling, Sentiment analysis
Kaynak
Proceedings - 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022
