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Open AccessArticle

Social Emotional Opinion Decision with Newly Coined Words and Emoticon Polarity of Social Networks Services

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Department of Computer Science, Graduate School, Korea National Open University, Jongno-gu, Dongsung-Dong, Seoul 30387, Korea
2
Department of Business Administration, Bucheon University, WonMi-Gu, SimGok-Dong 25, Bucheon 14632, Korea
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper: Yang, J.S.; Chung, K.S. Newly-Coined Words and Emoticon Polarity for Social Emotional Opinion Decision. In Proceedings of the IEEE 2nd International Conference on Information and Computer Technologies, Kahului, HI, USA, 14–17 March 2019; p. 76.
Future Internet 2019, 11(8), 165; https://doi.org/10.3390/fi11080165
Received: 9 June 2019 / Revised: 19 July 2019 / Accepted: 22 July 2019 / Published: 25 July 2019
(This article belongs to the Special Issue Selected Papers from IEEE ICICT 2019)
Nowadays, based on mobile devices and internet, social network services (SNS) are common trends to everyone. Social opinions as public opinions are very important to the government, company, and a person. Analysis and decision of social polarity of SNS about social happenings, political issues and government policies, or commercial products is very critical to the government, company, and a person. Newly coined words and emoticons on SNS are created every day. Specifically, emoticons are made and sold by a person or companies. Newly coined words are mostly made and used by various kinds of communities. The SNS big data mainly consist of normal text with newly coined words and emoticons so that newly coined words and emoticons analysis is very important to understand the social and public opinions. Social big data is informally made and unstructured, and on social network services, many kinds of newly coined words and various emoticons are made anonymously and unintentionally by people and companies. In the analysis of social data, newly coined words and emoticons limit the guarantee the accuracy of analysis. The newly coined words implicitly contain the social opinions and trends of people. The emotional states of people significantly are expressed by emoticons. Although the newly coined words and emoticons are an important part of the social opinion analysis, they are excluded from the emotional dictionary and social big data analysis. In this research, newly coined words and emoticons are extracted from the raw Twitter’s twit messages and analyzed and included in a pre-built dictionary with the polarity and weight of the newly coined words and emoticons. The polarity and weight are calculated for emotional classification. The proposed emotional classification algorithm calculates the weight of polarity (positive or negative) and results in total polarity weight of social opinion. If the total polarity weight of social opinion is more than the pre-fixed threshold value, the twit message is decided as positive. If it is less than the pre-fixed threshold value, the twit message is decided as negative and the other values mean neutral opinion. The accuracy of the social big data analysis result is improved by quantifying and analyzing emoticons and newly coined words. View Full-Text
Keywords: social media opinion; social big data; social big data analysis; emoticon; newly coined words; social emotional opinion social media opinion; social big data; social big data analysis; emoticon; newly coined words; social emotional opinion
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Yang, J.S.; Ko, M.-S.; Chung, K.S. Social Emotional Opinion Decision with Newly Coined Words and Emoticon Polarity of Social Networks Services. Future Internet 2019, 11, 165.

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