Studying Positive Speech on Twitter

We present results of empirical studies on positive speech on Twitter. By positive speech we understand speech that works for the betterment of a given situation, in this case relations between different communities in a conflict-prone country. We worked with four Twitter data sets. Through semi-man...

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Bibliographic Details
Published in:arXiv.org 2017-02
Main Authors: Sokolova, Marina, Sazonova, Vera, Huang, Kanyi, Chakraboty, Rudraneel, Matwin, Stan
Format: Article
Language:English
Subjects:
Data mining
Empirical analysis
Freedom of speech
Libel & slander
Social networks
Speech
Statistical analysis
Online Access:Get full text
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Summary:We present results of empirical studies on positive speech on Twitter. By positive speech we understand speech that works for the betterment of a given situation, in this case relations between different communities in a conflict-prone country. We worked with four Twitter data sets. Through semi-manual opinion mining, we found that positive speech accounted for < 1% of the data . In fully automated studies, we tested two approaches: unsupervised statistical analysis, and supervised text classification based on distributed word representation. We discuss benefits and challenges of those approaches and report empirical evidence obtained in the study.
ISSN:2331-8422