EmoWei : Emotion-Oriented Personalized Weight Management System Based on Sentiment Analysis

Jihyeon Kim, Uran Oh
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引用次数: 1

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.
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EmoWei:基于情感分析的面向情感的个性化体重管理系统
许多在线社区和商业应用程序都可以帮助人们控制体重。然而,这些系统仅限于记录和跟踪饮食或锻炼,而没有考虑到一个人的情绪状态,这对健康有很大的影响(例如,与压力有关的饮食)。为了证实从个人日志(如在线帖子)中监测情绪的可行性,我们首先对17735条与减肥相关的推文和200条来自一个名为FatSecret的在线体重管理社区的推文进行了基于循环神经网络(RNN)的情绪分析,并将其与普通推文进行了比较。研究结果表明,我们可以根据一个人写的文字和体重管理的进展来推断他的情绪。基于研究结果,我们提出了EmoWei,一个新的体重管理系统,整合用户的情绪,为用户提供个性化的帮助,以最小的压力实现减肥目标。
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