Toxic friend detector

Lai, Xuan Ying (2022) Toxic friend detector. Final Year Project, UTAR.

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Abstract

This project is an AI design project for sentiment analysis purpose. Sentiment Analysis is the mathematically and computational study on behalf of individual attitudes, opinions and emotions expressed in written language. This research areas in natural processing, sentiment analysis and some related topic model can be measured to handle some challenging tasks like automatic personality recognition. Influence to execute he Big Five Factors Dimensions personality facets brings incremental clause in prediction the content outcomes. Several methods of natural language processing will deploy for text processing such as tokenization, POS, stemming and so on based on the input data context given. Beginning from fundamental elements of natural language processing, the outlines will keep leading o the sentiment analysis of classification. Relative to the sentiment analysis-based approach, the Lexicon-based method and machine learning: Logistic Regression, is implemented throughout the project. For some precious studies, the diversity of effects and social colorations are measured and the relationship between the personality and emotions model and the personality trait will be analysed and executed. The outcomes results will demonstrate the personality tracking that prediction and identification of the people based on the following techniques and methods which are mentioned in this project. The platform is a web-based application to retrieve the data and show the emotions or the personality of an individual as a result of prediction a toxic people.

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