Automated Terms and Condition Analyser using Natural Language Processing

The widespread disregard for website terms and conditions poses a significant threat to personal privacy and security in today's fast-paced world. To combat this problem, we propose a system that utilizes natural language processing to analyse website policies and agreements. Our system starts by identifying terms and conditions pages through web scraping with the Beautiful Soup library[1]. Then, it employs NLP techniques such as Tokenization, Stemming, and keyword extraction to summarize and categorize content into three risk levels: high, medium, and low[2]. A user interface presents these categories and concise terms and conditions, enabling users to make informed decisions about acceptance. A crucial component of our system is the TextRank algorithm, which streamlines lengthy legal documents, making them more accessible and efficient while retaining essential information[3]. Our approach not only advances NLP but also underscores the importance of transparent, user-friendly online policies.