Mining sentiment words from microblogs for predicting writer-reader emotion transition
Journal
8th International Conference on Language Resources and Evaluation
Pages
1226-1229
ISBN
9782951740877
Date Issued
2012
Author(s)
Tang Y.-J.
Abstract
The conversations between posters and repliers in microblogs form a valuable writer-reader emotion corpus. In a microblog conversation, the writer of the initial post and the reader who replies to the initial post can both express their emotions. The process of changing from writer emotion to reader emotion is called a writer-reader emotion transition in this paper. Log relative frequency ratio is adopted to investigate the linguistic features that affect emotion transitions, and the results are used to predict writers' and readers' emotions. A 4-class emotion transition predictor, a 2-class writer emotion predictor, and a 2- class reader emotion predictor are proposed and compared.
Subjects
Emotion mining
Microblogging
Microtext classification
Sentiment analysis
Type
conference paper