Sentiment Analysis Main Tasks and Applications: A Survey

Sara Tedmori and Arafat Awajan
Volume: 15, No: 3, Page: 500 ~ 519, Year: 2019
Keywords: Feature Selection, Opinion Mining, Sentiment Analysis, Sentiment Analysis Applications, Sentiment Classification, Sentiment Visualization, Social Media Monitoring
Full Text:

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

Article Statistics
Multiple requests among the same broswer session are counted as one view (or download).
If you mouse over a chart, a box will show the data point's value.

Cite this article
IEEE Style
S. T. A. Awajan, "Sentiment Analysis Main Tasks and Applications: A Survey," Journal of Information Processing Systems, vol. 15, no. 3, pp. 500~519, 2019. DOI: 10.3745/JIPS.04.0120.

ACM Style
Sara Tedmori and Arafat Awajan. 2019. Sentiment Analysis Main Tasks and Applications: A Survey, Journal of Information Processing Systems, 15, 3, (2019), 500~519. DOI: 10.3745/JIPS.04.0120.