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Title |
Sentiment Analysis of Code-Mixed Text: A Comprehensive Review |
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Author |
W.A.S.C. Perera, H.A. Caldera |
| Citation |
Vol. 24 No. 11 pp. 73-84 |
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Abstract |
Sentiment Analysis is the task of identifying and extracting the opinion expressed in a text to determine the writer's perception of an entity. Most of the research works regarding Sentiment Analysis are focused on monolingual languages such as English. Classifiers are failed within the context of the code-mixed text as the text is created by mixing more than one language, and it may consist of creative writing, spelling variations, grammatical errors, and different word orders. Hence Sentiment Analysis of code-mixed text is a challenging task. This paper presents a state-of-the-art in Sentiment Analysis of code-mixed text by discussing each concept in detail. The paper also discusses and summarizes the focused areas, datasets, techniques, limitations, and performances of the literature related to code-mixing. |
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Keywords |
Code-mixed, Natural Language Processing, Sentiment Analysis |
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