@inproceedings{7016b6b7294a47bfa801e8aeca0a6a60,
title = "EmoWei: Emotion-oriented personalized weight management system based on sentiment analysis",
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.",
keywords = "Diet, Emotion, Healthcare, Mental health, Sentiment analysis, Social media, Weight loss, Weight management",
author = "Jihyeon Kim and Uran Oh",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 20th IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2019 ; Conference date: 30-07-2019 Through 01-08-2019",
year = "2019",
month = jul,
doi = "10.1109/IRI.2019.00060",
language = "English",
series = "Proceedings - 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science, IRI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "342--349",
booktitle = "Proceedings - 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science, IRI 2019",
}
