Troll Detection

• Tech Stack: Python, NLTK, spaCy, scikit-learn, matplotlib, seaborn
• Github URL: Project Link

Troll Detection

This project is aimed at detecting trolls from textual data. The increasing use of social media platforms has led to a surge in online trolling, which can have a negative impact on mental health and well-being. The project utilizes various natural language processing (NLP) techniques such as lemmatization and bag of words to accurately detect and classify troll comments from non-troll comments.

The project involves preprocessing the data by removing stop words, converting all text to lowercase, and applying lemmatization to obtain the root form of each word. The preprocessed data is then transformed using the bag of words technique, which converts the text data into numerical features that can be used for modeling. The project uses machine learning algorithms such as logistic regression and support vector machines (SVM) to train and classify the troll and non-troll comments.