Sustainability and Social Responsibility

Analysis of Research Trends on Body Image Using Text Mining

Authors
  • Su Jin Yang (Sungshin Women's University)
  • Sunwoo Kim (Seoul National University)
  • Seungwoo Seo (Korea University Graduate School of Computer & Information Technology)

Abstract

Body image is a complex and multidimensional notion that includes people's opinions, assessments, and feelings about their physical appearance. It has a significant impact on how people build their sense of self. This work aims to review body image-related research published within the past 20 years using a topic modeling methodology based on Python and LDAvis. 1) Adolescence and women's perceptions, 2) emotional distress and eating disordered behavior, 3) pervasive double standards according to cultural, ethnic, and sexual groups, 4) psychological symptoms that patients may experience after surgery, 5) ideal thin appearance and a positive body image, 6) obesity and weight gain/loss, etc. were among the eleven topics about body image that were covered. Our findings can improve our comprehension of fashion industry consumers and offer insightful information that can steer future study paths.

Keywords: body image, topic modeling, LSAvis, adolescence, eating disorder, ideal appearance

How to Cite:

Yang, S., Kim, S. & Seo, S., (2024) “Analysis of Research Trends on Body Image Using Text Mining”, International Textile and Apparel Association Annual Conference Proceedings 80(1). doi: https://doi.org/10.31274/itaa.17309

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Published on
24 Jan 2024
Peer Reviewed
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