Tweets Analyzer

Abstract

The Tweets Analyzer represents a sophisticated web application at the intersection of artificial intelligence and natural language processing, dedicated to the meticulous analysis and categorization of tweets into real or fake news categories, with a particular emphasis on those pertaining to political topics. Employing advanced machine-learning techniques, the system engages in comprehensive text data preprocessing through Natural Language Processing (NLP), extracting crucial features that include the presence of keywords indicative of fake or real news. A diverse array of machine-learning algorithms, encompassing Logistic Regression, Random Forest, Support Vector Machine (SVM), and Multinomial Naive Bayes, contributes to the system’s robustness and accuracy. In the contemporary landscape dominated by mobile technology and social media, where information dissemination occurs at an unprecedented pace, the "Tweets Analyzer" emerges as a vital tool. It addresses the pressing issue of fake news proliferation on platforms like Twitter, particularly in regions like Pakistan, influencing public opinions and potentially impacting election outcomes. This web-based application serves as a beacon of reliability, empowering users to navigate the intricate landscape of tweets and make informed distinctions between genuine and misleading information.