An Analysis for the Prediction of Human Behaviour & observation level on social media Using Machine Learning Approaches

Authors

  • Luxmi Sapra, Rahul Bhatt, Gesu Thakur

DOI:

https://doi.org/10.17762/msea.v71i4.819

Abstract

Usage over Internet has been significantly increased during last few decades. Peoples sparing more time on social media services. Social media is a place where users present themselves to the world, revealing personal details and insights into their lives. We are starting to comprehend how some of this information might be employed to better the users' experiences with interfaces and with one another. In this research proposal, we are interested to predict the personality of users by evaluating their tweets. In the past, users were required to complete a personality test before their characteristics could be adequately analyzed. Because of this, doing personality analysis in many different aspects of social media became impracticable. In this research proposal, we apply neural networks by which a user's personality can be accurately predicted through the publicly available information on their Twitter profile. We will present the sort of data obtained, our methods of analysis, and the machine learning approaches that enable us to correctly predict personality. It is essential for companies to have this information in order to target potentially interested customers or to get customer feedback in the event that diversification is pursued as a business strategy. Thus, this work analyzes social media data to predict significant personality traits, i.e. qualities or characteristics specific to an individual. The widespread use of social media sites results in an increase in both the quantity and amount of data. The quantity of data that is submitted to these social networking platforms is expanding day by day. Because of this, there is a significant need to investigate the very variable behavior of consumers in relation to these services. This is a preliminary work to model the user patterns and to study the effectiveness of machine learning active modeling approaches on leading social networking service Facebook. We created a model of the user comment patterns found on Facebook Pages and used it to make a prediction about the number of comments each post is likely to receive within the next 24 hours.

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Published

2022-09-16

How to Cite

Luxmi Sapra, Rahul Bhatt, Gesu Thakur. (2022). An Analysis for the Prediction of Human Behaviour & observation level on social media Using Machine Learning Approaches. Mathematical Statistician and Engineering Applications, 71(4), 2606–2620. https://doi.org/10.17762/msea.v71i4.819

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Section

Articles