Lexicons in sentiment analytics
With the increasing amount of text data, sentiment analytics (SA) is becoming an important tool for text miners. 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 lexic...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2017
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9409 https://ink.library.smu.edu.sg/context/sis_research/article/10409/viewcontent/Lexicons_in_Sentiment_Analytics.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | With the increasing amount of text data, sentiment analytics (SA) is becoming an important tool for text miners. 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, we study the effect of coupling a general lexicon with a specialized lexicon (for a specific domain) and its impact on sentiment analysis. Two special domains and one general domain were used. The two special domains are the petroleum domain and the biology domain. The general domain is the social network domain. 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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