Web Data Mining To Detect Online Spread Of Terrorism

Project Code :TCMAPY1535

Objective

The purpose of this research is to utilize web mining methods to efficiently identify and examine the propagation of terrorism on the internet. By gathering and analyzing information from diverse online platforms, the goal is to detect patterns, tendencies, and prominent individuals engaged in terrorist activities online. This approach aims to enable proactive measures to counter the spread of terrorism on the web.

Abstract

In recent years, there has been a concerning rise in terrorism in specific global regions, demanding immediate action to curb its proliferation and safeguard human lives and assets. The rapid growth of terrorist activities has been facilitated by the advancement of technology, particularly the internet, which has become a powerful tool for disseminating terrorist speeches and videos. Terrorist groups exploit this digital platform to inflict harm on individuals, tarnish reputations, and recruit new members to execute criminal acts on their behalf. To address this pressing issue, web mining techniques are being explored as a means to tackle online terrorism effectively and data mining techniques are being employed in tandem to develop efficient systems. Web mining plays a crucial role, especially in dealing with unstructured data available on the web. Systems for data mining and web mining work together to mine information from diverse sources, including textual data on websites with varying data structures. However, the diverse nature of websites built on different platforms presents challenges in developing a single algorithm to read them all.   KEYWORDS: KNN.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Hardware:

Operating system                    :  Windows 7 or 7+

RAM                                       :  8 GB

Hard disc or SSD                    :  More than 500 GB  

Processor                                 :  Intel 3rd generation or high or Ryzen with 8 GB Ram

Software:

Software’s                               :  Python 3.6 or high version

IDE                                         :  Jupyter Notebook 

Demo Video

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