Proceedings of the 42nd International Academic Conference, Rome

SENTIMENT ANALYSIS AND CLASSIFICATION OF TWEETS BASED ON IDEOLOGIES

RAJANI, PANKAJ SAMBYAL, SHALINI SHARMA

Abstract:

In this paper, we use data mining and sentiment analysis techniques to classify the tweets based on different ideologies i.e. Secularism, Liberalism, Communalism, Socialism and Casteism. To analyze our model, we used tweets from three sources namely generic Indian tweets, a specific user profile tweet and tweets of particular hashtags. The tweets are fetched using Twitter API. The fetched data is preprocessed by analyzing structure of tweets to find interesting analysis like most retweeted tweet, most favorited tweets, trending hashtags etc. Then tweets are tokenized and POS (parts of speech) tagging is done on tokens to find nouns, verbs, adverbs and adjectives which are relevant for the analysis. We apply various relevance models on the data, to find sentiment of each tweet and ideological stance of the user. The results are shown using spider graph. It was observed that the model worked with 73% accuracy.

Keywords: Multiclass, data mining, twitter, hashtag

DOI: 10.20472/IAC.2018.042.041

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