Paper: Expanding the Range of Automatic Emotion Detection in Microblogging Text

ACL ID E14-3005
Title Expanding the Range of Automatic Emotion Detection in Microblogging Text
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Detecting emotions on microblogging sites such as Twitter is a subject of interest among researchers in behavioral studies investigating how people react to different events, topics, etc., as well as among users hoping to forge stronger and more meaningful connections with their audience through social media. However, existing automatic emotion detectors are limited to recognize only the basic emotions. I argue that the range of emotions that can be detected in microblogging text is richer than the basic emotions, and restricting automatic emotion detectors to identify only a small set of emotions limits their practicality in real world applications. Many complex emotions are ignored by current automatic emotion detectors because they are not programmed to seek out these ?un...