Sentiment Analysis of Twitter Data using Statistical Methods

Jahiruddin

Abstract

Social media today has becomes a very popular tool in society. Millions of users share their opinions on different topics like politics, technologies, product and many more. Therefore social media is a rich source of data for opinion mining and sentiment analysis. In this paper we use the twitter data for sentiment analysis. First we use the Latent Dirichlet Allocation (LDA) to identify the key terms. These key terms are used to represent each tweet in n dimensional vector. Using this tweet vectors, we build a sentiment classifier, which is able to determine positive, negative, and neutral sentiment of each tweet. Experimental result show that our proposed method is efficient and out performs.

Keywords

Twitter, Latent Dirichlet allocation, Opinion mining, Sentiment analysis, Key term identification.

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Cites this article as

J. "Sentiment Analysis of Twitter Data using Statistical Methods", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-2, Issue-4, Page No-30-34, 2015. Available from: