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Emotional analysis system for social media using sentiment dictionary with newly-created words

  • Received : 2019.09.24
  • Accepted : 2020.04.05
  • Published : 2020.04.29

Abstract

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

감성분석은 비정형 텍스트에 나타나는 사람들의 의견이나 성향 등을 분석하는 오피니언 마이닝의 응용 분야이다. 최근에는 소셜미디어에 대한 감성분석이 주목받고 있으나 소셜미디어에는 신조어, 속어 등이 포함되어있어 기존 감성분석으로는 분석이 쉽지 않다. 본 연구에서는, 이러한 문제점을 해결하기 위해, 새로운 감성분석 시스템을 설계한다. 제안 시스템은 신조어, 속어 등이 포함된 소셜미디어에서도 긍/부정 뿐만아니라 다양한 감성분석이 가능하다. 먼저, 현재 소셜미디어에서 많이 나타나는 감성관련 신조어와 속어 등을 수집한다. 그리고 나서, 기존의 감성모델을 확장하고 이를 활용하여 감성단어에 감성정도를 수치화 한다. 또한 감성정도를 반영하여 새로운 감성단어 사전을 구축한다. 최종적으로, 신조어가 포함된 감성사전과 확장된 감성모델을 적용한 감성분석시스템을 설계한다.

Keywords

References

  1. Liu, B., "Sentiment Analysis and Opinion Mining", Morgan and Claypool Publishers, 2012. https://www.cs.uic.edu/-liub/FBS/SentimentAnalysis-and-OpinionMining.pdf
  2. "2017 Survey on the Internet Usage", KISA, https://isis.kisa.or.kr/board/index.jsp?pageId=060100&bbsId=7&itemId=821&pageIndex=1
  3. Sunkyung Kim, Panseop Shin, "Emotion Model for Semantic-Base d Retrieval of Music Content", Journal of the Korea Entertainment Industry Association, Vol. 9, No. 1, pp. 75-81, Feb. 2015
  4. Byungun Yoon, "Opinion Mining with Artificial Intelligence-What is Social Opinion Mining? ", Samsung SDS insight reports, 2017, https://www.samsungsds.com/global/ko/support/insights/1195888_2284.html
  5. Hannah Kim, Young-Seob Jeong, "Social Issue Analysis Based on Sentiment of Twitter Users", Journal of Convergence for Information Technology, Vol. 9. No. 11, pp. 81-91, 2019
  6. Russell, J., "A circumplex model of affect". Journal of Personality and Social Psychology Vol. 39, No. 6, pp 1161-1178, 1980 https://doi.org/10.1037/h0077714
  7. Thayer, R. E. "The Bio psychology of Mood and Arousal", New York: Oxford University Press, 1989.
  8. Plutchik, R.,"The Nature of Emotions", American Scientist, 2011.
  9. Soojin Lee, Sunkyung Kim, Panseop Shin, "Korean-based Emotion Model for Music Content Retrieval", Proceedings of Conference of KOEN 2016, The Korean Entertainment Industry Association(KOEN), pp. 71-74, 2016. 5.
  10. Sun Ju Sohn, Mi Sook Park, "Korean Emotion Vocabulary: Extraction and Categorization of Feeling Words", Korea Society for Emotion and Sensibility, Vol. 15, No. 1, pp. 105-120, 2012.
  11. Konlpy, http://konlpy.org
  12. Matplotlib, https://matplotlib.org

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  2. LDA 기반 사용자 감정분석을 위한 문서 토픽 추출 시스템에 대한 연구 vol.21, pp.2, 2021, https://doi.org/10.7236/jiibc.2021.21.2.195