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  • nldb-2016

    Rights statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-41754-7_48

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Reversing the polarity with emoticons

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Publication date17/06/2016
Host publicationNatural Language Processing and Information Systems: 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings
EditorsElizabeth Metais, Farid Meziane, Mohamad Saraee, Vijayan Sugumaran, Sunil Vadera
PublisherSpringer
Pages453-458
Number of pages6
ISBN (Electronic)9783319417547
ISBN (Print)9783319417530
<mark>Original language</mark>English
Event21st International Conference on Applications of Natural Language to Information Systems - MediaCityUK Campus, University of Salford, Manchester, United Kingdom
Duration: 22/06/201624/06/2016
http://www.salford.ac.uk/conferencing-at-salford/conference-management/current-conference/nldb-conference

Conference

Conference21st International Conference on Applications of Natural Language to Information Systems
Abbreviated titleNLDB2016
Country/TerritoryUnited Kingdom
CityManchester
Period22/06/1624/06/16
Internet address

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9612
ISSN (Print)0302-9743

Conference

Conference21st International Conference on Applications of Natural Language to Information Systems
Abbreviated titleNLDB2016
Country/TerritoryUnited Kingdom
CityManchester
Period22/06/1624/06/16
Internet address

Abstract

Technology advancement in social media software allows users to include elements of visual communication in textual settings. Emoticons are widely used as visual representations of emotion and body expressions. However, the assignment of values to the “emoticons” in current sentiment analysis tools is still at a very early stage. This paper presents our experiments in which we study the impact of positive and negative emoticons on the classifications by fifteen different sentiment tools. The “smiley” :) and the “sad” emoticon :( and raw-text are compared to verify the degrees of sentiment polarity levels. Questionnaires were used to collect human ratings of the positive and negative values of a set of sample comments that end with these emoticons. Our results show that emoticons used in sentences are able to reverse the polarity of their true sentiment values.

Bibliographic note

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-41754-7_48