Classification Techniques on Twitter Data: A Review
DOI:
https://doi.org/10.51983/ajcst-2019.8.S2.2022Keywords:
Data Mining, Sentiment Analysis, Social Media, Twitter, EmotionsAbstract
Data mining is the practice of examining unknown patterns of data according to diverse viewpoints for classification into valuable information, which is composed and gathered in collective areas, such as data warehouses.For effective analysis, data mining algorithms enabling business decision making and other information necessities to eventually cut costs and raise revenue. Sentiment analysis is the method of defining the emotional tone behind a sequence of words, used to gain an accepting of the attitudes, opinions and emotions conveyed within an online mention. Sentiment analysis is tremendously useful in social media observing as it allows us to gain a synopsis of the broader public opinion behind definite topics. The applications of sentiment analysis are extensive and influential. The ability to abstract insights from social data is a practice that is being broadly adopted by organizations across the world. In this paper, we focused on sentiment analysis on the twitter data.
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