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Sentiment Analytics: Lexicons Constr...
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Yuan, Bo.
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Sentiment Analytics: Lexicons Construction and Analysis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Sentiment Analytics: Lexicons Construction and Analysis./
作者:
Yuan, Bo.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
42 p.
附註:
Source: Masters Abstracts International, Volume: 56-05.
Contained By:
Masters Abstracts International56-05(E).
標題:
Information technology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10266606
ISBN:
9780355088687
Sentiment Analytics: Lexicons Construction and Analysis.
Yuan, Bo.
Sentiment Analytics: Lexicons Construction and Analysis.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 42 p.
Source: Masters Abstracts International, Volume: 56-05.
Thesis (M.S.)--Missouri University of Science and Technology, 2017.
With the increasing amount of text data, sentiment analysis (SA) is becoming more and more important. An automated approach is needed to parse the online reviews and comments, and analyze their sentiments. Since lexicon is the most important component in SA, enhancing the quality of lexicons will improve the efficiency and accuracy of sentiment analysis. In this research, the effect of coupling a general lexicon with a specialized lexicon (for a specific domain) and its impact on sentiment analysis was presented. Two special domains and one general domain were studied. The two special domains are the petroleum domain and the biology domain. The general domain is the social network domain. The specialized lexicon for the petroleum domain was created as part of this research. The results, as expected, show that coupling a general lexicon with a specialized lexicon improves the sentiment analysis. However, coupling a general lexicon with another general lexicon does not improve the sentiment analysis.
ISBN: 9780355088687Subjects--Topical Terms:
532993
Information technology.
Sentiment Analytics: Lexicons Construction and Analysis.
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With the increasing amount of text data, sentiment analysis (SA) is becoming more and more important. An automated approach is needed to parse the online reviews and comments, and analyze their sentiments. Since lexicon is the most important component in SA, enhancing the quality of lexicons will improve the efficiency and accuracy of sentiment analysis. In this research, the effect of coupling a general lexicon with a specialized lexicon (for a specific domain) and its impact on sentiment analysis was presented. Two special domains and one general domain were studied. The two special domains are the petroleum domain and the biology domain. The general domain is the social network domain. The specialized lexicon for the petroleum domain was created as part of this research. The results, as expected, show that coupling a general lexicon with a specialized lexicon improves the sentiment analysis. However, coupling a general lexicon with another general lexicon does not improve the sentiment analysis.
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