Social media data analysis to predict mental state of users using machine learning techniques

Abstract

BACKGROUND: Social media platforms such as Facebook, WhatsApp, and Instagram etc., are becoming very popular now not only for youth but for all walks of life. People are more often seen in busy in tweeting, chatting, or putting selfies. No one actually knows the mental state of a person in the online platform. In this article, we will be focusing on how social media is affecting issues such as road accident, murder, and suicide. The research is done by three parts. MATERIALS AND METHODS: Google Form analysis, machine learning used for prediction, and by sentimental analysis of what people think in twitter. All the datasets are based in India. From these datasets, the different machine learning algorithm is used to do the analysis. The project strives to bring the real-world solution in the matter of advancement. RESULTS: The static data analysis and dynamic data analysis shows the various sentimental analysis and predictions and the technique to predict different mental states. Thus we get clearly about the current world is getting into social issues. This research findings helps to bring social awareness among the current generation by understanding the sensitivity of the youths. CONCLUSION: Thus through this paper we get known clearly how the current world is getting into social issues like victim of murders or road accidents or committing suicide. The paper clearly helps us to understand the sensitivity of the youths. Therefore brings a social awareness among the current generation.

Keywords

• clustering
• mental state
• prediction models
• sentiment analysis