The Journal of Korean Institute of Information Technology (한국정보기술학회논문지)

Korean Institute of Information Technology (한국정보기술학회)
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A Study on the Emotion Analysis of Instagram Using Images and Hashtags

이미지와 해시태그를 이용한 인스타그램의 감정 분석 연구

  • 정다혜 (군산대학교 소프트웨어융합공학과) ;
  • 김장원 (군산대학교 소프트웨어융합공학과)
  • Received : 2019.08.01
  • Accepted : 2019.09.09
  • Published : 2019.09.30
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Abstract

Social network service users actively express and share their feelings about social issues and content of interest through postings. As a result, the sharing of emotions among individuals and community members in social network is spreading rapidly. Therefore, resulting in active research of emotion analysis on posting of users. However, There is insufficient research on emotion analysis for postings containing various emotions. In this paper, we propose a method that analyzes the emotions of an Instagram posts using hashtags and images. This method extracts representative emotion from user posts containing multiple emotions with 66.4% accuracy and 81.7% recall, which improves the emotion classification performance compared to the previous method.

최근 소셜 네트워크 서비스 사용자들은 게시글을 통해 사회적 이슈 및 관심 콘텐츠들에 대한 자신의 감정을 적극적으로 표현하고 공유한다. 그 결과 소셜 네트워크에서의 개인 및 특정 집단의 감정 공유는 빠르게 확산된다. 그러므로 사용자들의 게시글에 대한 감정 분석 연구가 활발히 진행되고 있다. 그렇지만 다양한 감정이 포함된 게시글에 대한 감정 분석 연구가 미흡하다. 따라서 본 논문에서는 해시태그와 이미지를 이용한 인스타그램 게시글의 대표 감정 분석 방법을 제안한다. 이를 통해 사용자 게시글에 포함된 다종의 리소스를 활용하여 다중의 감정으로부터 대표 감정을 추출할 수 있으며 66.4%의 정확도와 81.7%의 재현율로 기존 방법보다 감정 분류 성능 향상을 보인다.

Keywords

References

  1. A. DI. Kramer, "The spread of emotion via Facebook", Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, Texas, USA, pp. 767-770, May 2012.
  2. Y. J. Jung, W. J. Seo, Y. R. Byeon, and T. W. Kang, "Classification of the suicidal signs in SNS using naive bayesian classifier", Proceedings of KIISE Conference, pp. 2129-2131, Jun. 2015.
  3. 96 Instagram Statistics for Social Media Marketing Gurus, https://99firms.com/blog/instagram-marketing-statistics. [accessed: Jul. 30, 2019]
  4. N. H. Chung, T. H. Um, and C. M. Koo, "Factors Influencing Photo Sharing for Creating Social Relationships on Instagram", Knowledge Management Research, Vol. 17, No. 4, pp. 129-145, Dec. 2016. https://doi.org/10.15813/kmr.2016.17.4.006
  5. M. J. Kim, B. M. Kim, H. Y. Kim, S. Y. Baek, H. S. Shin, I. S. Lee, and J. W. Kim, "The Effect of Emotion Sharing with Hashtag on Perceived Attention Seeking and Social Interactivity", Proceedings of HCI Korea Conference, Jeongseon, Korea, pp. 460-467, Jan. 2016.
  6. Star Tag, https://startag.io. [accessed: Jul. 30, 2019]
  7. P. H. Oh and B. Y. Hwang, "Real-time Spatial Recommendation System based on Sentiment Analysis of Twitter", Journal of SEBS, Vol. 21, No. 3, pp. 15-28, Feb. 2016.
  8. S. M. Kwon and J. H. Lee, "Feasibility of Hashtag of Former Posts on Instagram for using Contextual Information of Sentiment Analysis", Proceedings of KIISE Conference, pp. 649-651, Jun. 2018.
  9. M. J. Nam, E. J. Lee, and J. H. Shin, "A Method for User Sentiment Classification using Instagram Hashtags", Journal of KMMS, Vol. 18, No. 11, pp. 1391-1399, Aug. 2015.
  10. X. Wang, F. Wei, X. Liu, M. Zhou, and M. Zhang, "Topic Sentiment Analysis in Twitter: A Graph-based Hashtag Sentiment Classification Approach", Proceedings of the 20th ACM international conference on Information and Knowledge management(CIKM), Glasgow, United Kingdom,, pp. 1031-1040, Oct. 2011.
  11. R. E. Thayer, "The Biopsychology of Mood and Arousal", Oxford University Press, 1989.
  12. Rachman, F. Hastarita, R. Sarno, and C. Fatichah, "Music emotion classification based on lyrics-audio using corpus based emotion" International Journal of ECE, Vol. 8, No. 3, pp. 1720-1730, Jun. 2018.
  13. B. J. Kim and J. W. Lee, "A deep-learning based model for emotional evaluation of video clips", International Journal of Fuzzy Logic and Intelligent Systems, Vol. 18, No. 4, pp. 245-253, Dec. 2018. https://doi.org/10.5391/ijfis.2018.18.4.245
  14. S. B. Ki, J. W. Park, J. M. Park, G. Y. Lee, H. C Lee, T. Saputri, and S. W. Lee, "Using Ontological Approach for Music Recommendation Based on Emotion Analysis on Instagram", Proceedings of KIISE Conference, pp. 1926-1928, Dec. 2017.
  15. M. J. Nam, J. I. Kim, and J. H. Shin, "A User Emotion Information Measurement Using Image and Text on Instagram-Based", Journal of KMMS, Vol. 17, No. 9, pp. 1125-1133, Sep. 2014.
  16. D. H. Jeong, S. B. Kim, C. R. Jeong, and J. W. Gim, "An Emotion Analysis Method Using Hash Tags and Images in Instagram", Proceedings of KIIT Conference, pp. 302-304, Nov. 2018.
  17. ALT text on Instagram Photos, https://thepreviewapp.com/alt-text-instagram-photos-use-like-professional/. [accessed: Jul. 30, 2019]
  18. Google cloud vision API, https://cloud.google.com/vision/ [accessed: Jul. 30, 2019]
  19. Z. Othman, N. A. Abullah, K. Y. Chin, F. F. W. Shahrin, S.S. Syed Ahmad, and F. Kasmin, "Comparison on Cloud Image Classification for Thrash Collecting LEGO Mindstorms EV3 Robot", International Journal of HaTI, Vol. 2, No. 1, pp. 29-34, Apr. 2018.