EmoWei: Emotion-oriented personalized weight management system based on sentiment analysis

Jihyeon Kim, Uran Oh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A number of online communities and commercial apps exist to assist people with weight management. However, these systems are limited to logging and tracking meals or workouts without considering one's emotional state, which is known to have a strong impact on health (e.g., stress-related eating). To confirm the feasibility of monitoring emotion from personal logs such as online posts, we first conducted a Recurrent Neural Network (RNN) based sentiment analysis on 17,735 weight loss-related tweets and 200 posts from an online weight management community called FatSecret in comparisons to general tweets. The results suggest that we can infer one's emotion based on their written text and their progress in managing weight. Based on the findings, we propose EmoWei, a new weight management system that integrates users' emotions to provide personalized assistance to achieve their weight loss goals with minimum stress.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science, IRI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages342-349
Number of pages8
ISBN (Electronic)9781728113371
DOIs
StatePublished - Jul 2019
Event20th IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2019 - Los Angeles, United States
Duration: 30 Jul 20191 Aug 2019

Publication series

NameProceedings - 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science, IRI 2019

Conference

Conference20th IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2019
Country/TerritoryUnited States
CityLos Angeles
Period30/07/191/08/19

Keywords

  • Diet
  • Emotion
  • Healthcare
  • Mental health
  • Sentiment analysis
  • Social media
  • Weight loss
  • Weight management

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