Paper: Detecting Event-Related Links and Sentiments from Social Media Texts

ACL ID P13-4005
Title Detecting Event-Related Links and Sentiments from Social Media Texts
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2013
Authors

Nowadays, the importance of Social Me- dia is constantly growing, as people often use such platforms to share mainstream media news and comment on the events that they relate to. As such, people no loger remain mere spectators to the events that happen in the world, but become part of them, commenting on their develop- ments and the entities involved, sharing their opinions and distributing related con- tent. This paper describes a system that links the main events detected from clus- ters of newspaper articles to tweets related to them, detects complementary informa- tion sources from the links they contain and subsequently applies sentiment analy- sis to classify them into positive, negative and neutral. In this manner, readers can follow the main events happening in the world, both from...