2016/11/29 by Poddar, Lahari, Halder, Kishaloy, Jia, Xianyan
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Social and Information Networks (cs.SI)
paper · doi:10.48550/arxiv.1611.09441
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.