SENTIMENT ANALYSIS AND CLASSIFICATION OF TWEETS BASED ON IDEOLOGIES

Rajani (), Pankaj Sambyal () and Shalini Sharma ()
Additional contact information
Rajani: Kalindi College
Pankaj Sambyal: Kalindi College`
Shalini Sharma: Kalindi College

No 7010170, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

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 (search for similar items in EconPapers)
Pages: 8 pages
Date: 2018-10
New Economics Papers: this item is included in nep-big
References: Add references at CitEc
Citations:

Published in Proceedings of the Proceedings of the 42nd International Academic Conference, Rome, Oct 2018, pages 340-347

Downloads: (external link)
https://iises.net/proceedings/42nd-international-a ... 70&iid=041&rid=10170 First version, 2018

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:7010170

Access Statistics for this paper

More papers in Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences
Bibliographic data for series maintained by Klara Cermakova ().