Sentiment Analysis for Twitter : Going Beyond Tweet Text
November 29, 2016 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Lahari Poddar, Kishaloy Halder, Xianyan Jia
arXiv ID
1611.09441
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
2
Venue
arXiv.org
Last Checked
5 months ago
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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