Sentiment Analysis on the News to Improve Mental Health

• URL: http://arxiv.org/abs/2108.07706v1
• Date: Thu, 5 Aug 2021 18:07:24 GMT
• Title: Sentiment Analysis on the News to Improve Mental Health
• Authors: Saurav Kumar, Rushil Jayant, Nihaar Charagulla
• Abstract summary: With monetization driven by clicks, journalists have reprioritized their content for the highly competitive atmosphere of online news. We utilized a pipeline of 4 sentiment analysis models trained on various datasets - using Sequential, LSTM, BERT, and SVM models. When combined, the application, a mobile app, solely displays uplifting and inspiring stories for users to read. Results have been successful - 1,300 users rate the app at 4.9 stars, and 85% report improved mental health by using it.
• Score: 2.062593640149623
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The popularization of the internet created a revitalized digital media. With monetization driven by clicks, journalists have reprioritized their content for the highly competitive atmosphere of online news. The resulting negativity bias is harmful and can lead to anxiety and mood disturbance. We utilized a pipeline of 4 sentiment analysis models trained on various datasets - using Sequential, LSTM, BERT, and SVM models. When combined, the application, a mobile app, solely displays uplifting and inspiring stories for users to read. Results have been successful - 1,300 users rate the app at 4.9 stars, and 85% report improved mental health by using it.

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