Opinion Mining on Twitter Data using Unsupervised Learning Technique

International Journal of Computer ApplicationsPublished 16 August 2016Open access

Muqtar Unnisa, Ayesha Ameen, Syed Raziuddin

DOI10.5120/ijca2016911317

Citations23

TL;DR

The proposed work is able to collect information from social networking sites like Twitter and the same is used for sentiment analysis, and the processed meaningful tweets are cluster into two different clusters positive and negative using unsupervised machine learning technique such as spectral clustering.

Abstract

Social media is one of the biggest forums to express opinions. Sentiment analysis is the procedure by which information is extracted from the opinions, appraisal and emotions of people in regards to entities, events and their attributes. Sentiment analysis is also known as opinion mining. Opinion mining is to analyze and cluster the user generated data like reviews, blogs, comments, articles etc. These data find its way on social networking sites like twitter, facebook etc. Twitter has provided a very gigantic space for prediction of consumer brands, movie reviews, democratic electoral events, stock market, and popularity of celebrities.

Keywords

Computer Science

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