Problem Statement
With the advances in technology about sentiment analysis and predictive analytics, it has opened many avenues for researchers and enterprises to understand human mental state better. The proposed challenge is to know the emotion/mood of a person, to help in eliminating any negative state of mind that might have adverse effect on his/her daily life
- Get a person’s social contents (e.g. tweets) for a duration (e.g. past 24 hours).
- Perform sentiment analysis using IBM Watson [2], [3] on the above content.
- Display the person name and his/her most prominent sentiment.
- Suggest measures to soothe or calm down the mood of the person by suggesting some curated playlist of songs based on his interest or something similar that you can imagine.
A person’s emotions and moods have direct bearings on his/her daily activities. It is necessary to eliminate negative emotions that our family or friends might be experiencing, to help them lead a better life. Research has shown that social networking activity is a good source to gauge a person’s state of mind [1]. Mood of a user is often reflected in his/her social content, like tweets, blogs, article, status updates, etc. Timely analysis of a user’s social media can be used to improve the feelings, and even save a person’s life in an extreme case! Hence it becomes important to regularly analyze the social-media health of our friends and family to take timely action.
Songs you might want to listen!
Team
Here below are the members of this epic team that pulled out an all-nighter to complete this project because before these everyone had their examinations going on.
Abhinandan Jha
Front-End DeveloperSecond Year student at SRM University.
Adriraj Sachan
Front-End DeveloperThird Year student at SRM University.
Prabodh Singh
AI/ML DeveloperThird Year student at SRM University.
Astitva Veer Garg
AI/ML DeveloperSecond Year student at SRM University.