Identifying Psychological Effects of Social Media using Machine learning approach
Authors/Creators
- 1. Research Scholar, College of Computer Science and Information Science Srinivas University, Mangalore, India
Description
Purpose: Social Media have been developed as a useful tool for its users to communicate with friends and share their thoughts, pictures based on their situations and sentiments. These tools have become very popular wide over the world and each tool has billions of users. Using these tools we can analyze the data to understand their sentiments and feelings and find their problems.
Approach: Identifying the psychological effects using social media data is in an established position globally; but still there are other aspects that are to be studied. We aim to scrutinize the data collected from Twitter and Instagram to investigate the psychological effects on the users of Twitter and Instagram, we are planning to use Machine learning (ML) approach for effective results.
Outcome: By implementing the proposed approach using a set of various psychological behaviors, we can have the significant improvement in the accuracy and reduce error rate. Also, we can achieve expected results using a specific algorithm which gives the highest accuracy among ML approaches to find the psychological effects.
Conclusions: Sentimental Analysis can be carried out efficiently using ML approaches.