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Classifying COVID-19 News on Sina Weibo.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Classifying COVID-19 News on Sina Weibo./
作者:
Sen, Arunachal.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
74 p.
附註:
Source: Masters Abstracts International, Volume: 83-05.
Contained By:
Masters Abstracts International83-05.
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28721308
ISBN:
9798480643633
Classifying COVID-19 News on Sina Weibo.
Sen, Arunachal.
Classifying COVID-19 News on Sina Weibo.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 74 p.
Source: Masters Abstracts International, Volume: 83-05.
Thesis (Master's)--University of Washington, 2021.
This item must not be sold to any third party vendors.
This thesis addresses the classification of Sina Weibo news related to the COVID-19 pandemic by using sentiment analysis. The design is a comparison study, involving four different systems. The systems were chosen after extensive reading on different approaches to sentiment analysis in Mandarin Chinese. These systems are neural network, k-medoids, HMM, and SVM. The core work of this thesis was in fine-tuning these systems to work with a small dataset of less than 3,000 examples. The final results from numerous experiments showed that the SVM and HMM systems achieved the highest results, followed by the neural network and k-medoids systems. Findings of this study showed that keyword frequency within a news category is not necessarily sufficient to ensure correct classification. Also, posts with names and satire remain challenging to classify and could be investigated further.
ISBN: 9798480643633Subjects--Topical Terms:
573171
Computer science.
Subjects--Index Terms:
HMM
Classifying COVID-19 News on Sina Weibo.
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