Paper: OPTWIMA: Comparing Knowledge-rich and Knowledge-poor Approaches for Sentiment Analysis in Short Informal Texts

ACL ID S13-2076
Title OPTWIMA: Comparing Knowledge-rich and Knowledge-poor Approaches for Sentiment Analysis in Short Informal Texts
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

The fast development of Social Media made it possible for people to no loger remain mere spectators to the events that happen in the world, but become part of them, comment- ing on their developments and the entities in- volved, sharing their opinions and distribut- ing related content. This phenomenon is of high importance to news monitoring systems, whose aim is to obtain an informative snap- shot of media events and related comments. This paper presents the strategies employed in the OPTWIMA participation to SemEval 2013 Task 2-Sentiment Analysis in Twitter. The main goal was to evaluate the best settings for a sentiment analysis component to be added to the online news monitoring system. We describe the approaches used in the com- petition and the additional experiments per- formed com...