Abstract
The conversations between posters and repliers in microblogs form a valuable writer-reader emotion corpus. This paper adopts a log relative frequency ratio to investigate the linguistic features which affect emotion transitions, and applies the results 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.- Anthology ID:
- L12-1007
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 1226–1229
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/117_Paper.pdf
- DOI:
- Cite (ACL):
- Yi-jie Tang and Hsin-Hsi Chen. 2012. Mining Sentiment Words from Microblogs for Predicting Writer-Reader Emotion Transition. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 1226–1229, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- Mining Sentiment Words from Microblogs for Predicting Writer-Reader Emotion Transition (Tang & Chen, LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/117_Paper.pdf