| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 552284 | Decision Support Systems | 2012 | 12 Pages |
Abstract
In this paper, we show how sentiment analysis can be used in tandem with effective visualizations to quantify and track emotions in mail and books. We study a number of specific datasets and show, among other things, how collections of texts can be organized for affect-based search and how books portray different entities through co-occurring emotion words. Analysis of the Enron Email Corpus reveals that there are marked differences across genders in how they use emotion words in work-place email. Finally, we show that fairy tales have more extreme emotion densities than novels.
Related Topics
Physical Sciences and Engineering
Computer Science
Information Systems
Authors
Saif M. Mohammad,