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Sentiment Analysis for Twitter : Going Beyond Tweet Text (1611.09441v1)

Published 29 Nov 2016 in cs.CL and cs.SI

Abstract: Analysing sentiment of tweets is important as it helps to determine the users' opinion. Knowing people's opinion is crucial for several purposes starting from gathering knowledge about customer base, e-governance, campaigning and many more. In this report, we aim to develop a system to detect the sentiment from tweets. We employ several linguistic features along with some other external sources of information to detect the sentiment of a tweet. We show that augmenting the 140 character-long tweet with information harvested from external urls shared in the tweet as well as Social Media features enhances the sentiment prediction accuracy significantly.

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Authors (3)
  1. Lahari Poddar (10 papers)
  2. Kishaloy Halder (13 papers)
  3. Xianyan Jia (11 papers)
Citations (2)

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