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Using Sentiment Analysis on Diet Patterns and Food to Avoid Negative Impacts on Mood and Health

IP.com Disclosure Number: IPCOM000248754D
Publication Date: 2017-Jan-06
Document File: 3 page(s) / 78K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a method and system to use sentiment analysis on diet patterns and food, track negative impacts of food on the user, and then make recommendations about how to balance meals and have a positive impact on emotional states.

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Using Sentiment Analysis on Diet Patterns and Food to Avoid Negative Impacts on Mood and Health

Food impacts how people feel, both emotionally and physically. The way in which foods affect a person varies. For example, consuming some foods can result in a person’s low performance in work or exercise activities, may cause damage to the body, or increase the risk certain diseases. Depending on each person's anatomy or metabolism, certain foods or meals may cause negative effects in the sense of mood. For example, some ingredients (e.g., carbohydrates) or meals may cause a person to feel tired, weary, bad humor, depression, etc. Even when these effects usually do not show long-term signs, people can feel some temporary symptoms; however, people tend to ignore temporary discomfort until the effect has passed or is a serious problem and symptoms are constant.

People must consider which foods are better options to promote good emotional and physical health . For most people, because of busy schedules, hectic lives, or lack or information, planning healthy and beneficial diets is a challenge. In addition, people do not usually consult a doctor or analyze how mood and feeling well/unwell are associated with diet. People do not perform a root cause analysis and modify diet patterns based on results that show correlations between certain foods and emotional and physical changes.

The novel solution is a method and system to use sentiment analysis on diet patterns and food and then make recommendations about how to balance meals and have a positive impact on emotional states .

The core idea is to use sentiment analysis methods to track the impact that food has on a person . Based on the information obtained and related statistics in conjunction with online information about the known effects of certain foods on mood , the system generates recommendations for a balanced diet . The system indicates to the user which foods to avoid or consume under certain conditions (e.g., activities).

The method and system can use data from different sources . Using existing technologies for sentiment analysis* in wearable devices, the system can track how a particular food makes the user feel and track that information in a central repository . If the user does not have a wearable device, then the user can directly provide the sentiment analysis by, for example, logging into the system and providing the information about how a food affected a mood . The system can also use information available online or from localized data sources about the effects that certain food can cause in people .

During implementation, the system receives as a parameter the food that a person will eat , and then performs an analysis of the effects that it could cause in the person based on previous experience with a similar food or available information . The system

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then indicates to the user the expected mood based on the food the user plans to eat .

The method and system provide a feedback...