Classification of terms on a positive-negative feelings polarity scale based on emoticons
Abstract
The goal of this paper is to draw attention to the possibility of using emoticon-riddled text on the web in language-neutral sentiment analysis. It introduces several innovations in the existing framework of research and tests their effectiveness. It also presents a software tool especially made for that purpose, explains how it builds a database with sentimental value of terms and offers the user manual. Finally, it presents a software tool that tests the new database and gives some examples of the analysis of the obtained results.References
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Go, Alec and Lei Bhayani, Richa nad Huang, "Twitter Sentiment Classifcation using Distant Supervision", , 2009, processing
Mishne, Gilad, "Experiments with mood classi cation in blog posts", In Proceedings of ACM SIGIR 2005 workshop on stylistic analysis of text for information access, Vol. 19, Citeseer, 2005, 321-327
Neviarouskaya, Alena, Helmut Prendinger and Mitsuru Ishizuka, "Compositionality Principle in Recognition of Fine-Grained Emotions from Text", In Proceedings of the Third International ICWSM Conferenc, The AAAI Press, 2009, 278-281
Ptaszynski, Michael, Rafal Rzepka, Kenji Araki and Yoshio Momouchi, "Research on Emoticons: Review of the Field and Proposal of Research Framework", In The Seventeenth Annual Meeting of The Association for Natural Language Processing, The Association for Natural Language Processing, 2011, 1159-1162
Published
2017-07-19
How to Cite
ŠKORIC, Mihailo.
Classification of terms on a positive-negative feelings polarity scale based on emoticons.
Infotheca - Journal for Digital Humanities, [S.l.], v. 17, n. 1, july 2017.
ISSN 2217-9461.
Available at: <https://infoteka.bg.ac.rs/ojs/index.php/Infoteka/article/view/2017.17.1.4_en>. Date accessed: 23 apr. 2024.
doi: https://doi.org/10.18485/infotheca.2017.17.1.4.
Section
Articles
Keywords
data mining, information extraction, emotions, text on the web
