A Description of the Sentiment Analysis Task and Their Application for the Analysis of Tweets

Flora Pincock 2

Abstract


In this paper we introduce the main fundamentals of sentiment analysis and the benefits of using the popular micro-blogging site, Twitter, as a source of texts for sentiment analysis. We review some of the most recent papers published on sentiment analysis and describe the most relevant methods and approaches. We have used the conclusions of current research in the field to decide which methods or techniques to use in our own experimentation of sentiment analysis. We identify the methods of evaluating the performance of classifiers, and the open source tools available for carrying out the analysis. For our research, we have used Twitter data from the Sentiment140 database. We have explored various combinations of feature selection methods and machine learning techniques to build and evaluate 20 classifiers using this data.


Keywords


sentiment analysis; classification functions; feature selection; twitter.

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DOI: http://dx.doi.org/10.24294/csma.v0i0.860

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