DETECTION OF ONLINE SPREAD TERRORISM USING WEB DATA MINING

The rapid expansion of the internet and digital communication technologies has created new opportunities for information exchange, social interaction, and global connectivity.However, this digital revolution has also enabled terrorist organizations to exploit online platforms for spreading extremist ideologies, recruiting susceptible individuals, coordinating attacks, and sustaining global propaganda networks.The anonymous, fastmoving, and decentralized nature of the web makes it increasingly difficult for traditional surveillance and manual monitoring systems to identify and curb the spread of terrorism-related content.Addressing this growing challenge requires advanced, automated, and intelligent systems capable of analyzing vast web-based datasets in real time.This study presents a comprehensive framework for detecting the online spread of terrorism using web data mining, Natural Language Processing (NLP), and K-Means clustering.The proposed system begins with largescale data collection from various online platforms, including social media networks, forums, blogs, and news websites.The collected data undergoes rigorous preprocessing to remove noise, normalize text, and prepare it for computational analysis.NLP techniques such as tokenization, lemmatization, TF-IDF feature extraction, sentiment analysis, and topic modeling are applied to transform unstructured textual content into meaningful representations.These features serve as the basis for cluster formation using the K-Means algorithm, which groups similar content and identifies hidden patterns associated with extremist activities.Overall, the research demonstrates that combining web mining, NLP, and machine learning techniques provides a powerful and efficient approach to monitoring extremist content online.By uncovering patterns, relationships, and behavioral cues across diverse digital platforms, the proposed framework strengthens early detection mechanisms and plays a crucial role in mitigating the online spread of terrorism.