Inferring political preference from Twitter tweets

Nisha P. Shetty, Daita Ravi Teja, Tummala Srinag Vinil, Swati Kanwal, Harsh Mutha, Akshita Bhargava

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Commercial popularity of social media and free availability of vast data has enhanced the interests of the researchers in analyzing its contents. Many businesses make use of such data to harness the mindset and likes of their target audience, thereby improving their profits. Sentiment analysis of Twitter texts have proved to be an effective way of voicing the needs of large masses and is used by many prominent politicians in making better campaigning strategies. Multiple machine learning classifiers are implemented in this study to access the stance of US citizens towards Democrats/Republicans to deduce which political party a user prefers from his tweets. Performance of a stacked ensemble is compared against a deep neural network for the mentioned problem domain.

Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Inventive Computation Technologies, ICICT 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages471-475
Number of pages5
ISBN (Electronic)9781728185019
DOIs
Publication statusPublished - 20-01-2021
Event6th International Conference on Inventive Computation Technologies, ICICT 2021 - Coimbatore, India
Duration: 20-01-202122-01-2021

Publication series

NameProceedings of the 6th International Conference on Inventive Computation Technologies, ICICT 2021

Conference

Conference6th International Conference on Inventive Computation Technologies, ICICT 2021
CountryIndia
CityCoimbatore
Period20-01-2122-01-21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management

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