• Title/Summary/Keyword: Instagram, Emotions Classification of Users

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A Study on the Emotion Analysis of Instagram Using Images and Hashtags (이미지와 해시태그를 이용한 인스타그램의 감정 분석 연구)

  • Jeong, Dahye;Gim, Jangwon
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.9
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    • pp.123-131
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    • 2019
  • 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.

A User Sentiment Classification Using Instagram image and text Analysis (인스타그램 이미지와 텍스트 분석을 통한 사용자 감정 분류)

  • Hong, Taekeun;Kim, Jeongin;Shin, Juhyun
    • Smart Media Journal
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    • v.5 no.1
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    • pp.61-68
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    • 2016
  • According to increasing SNS users and developing smart devices like smart phone and tablet PC recently, many techniques to classify user emotions with social network information are researching briskly. The use emotion classification stands for distinguishing its emotion with text and images listed on his/her SNS. This paper suggests a method to classify user emotions through sampling a value of a representative figure on a trigonometrical function, a representative adjective on text, and a canny algorithm on images. The sampling representative adjective on text is selected as one of high frequency in the samplings and measured values of positive-negative by SentiWordNet. Figures sampled on images are selected as the representative in figures; triangle, quadrangle, and circle as well as classified user emotions by measuring pleasure-unpleased values as a type of figures and inclines. Finally, this is re-defined as x-y graph that represents pleasure-unpleased and positive-negative values with wheel of emotions by Plutchik. Also, we are anticipating for applying user-customized service through classifying user emotions on wheel of emotions by Plutchik that is redefined the representative adjectives and figures.