Monitoring Suspicious Discussions On Online Forums Using Data Mining

Monitoring Suspicious Discussions On Online Forums Using Data Mining

Abstract:

Internet use for discussion has increased legal and illegal activities. Internet forums are used to spread copyrighted content, threats, and online gambling before traditional mass media reports it. Law enforcement agencies are looking for ways to monitor discussion forums for criminal activity and collect evidence. This project proposes a data mining system that detects criminal activity and illegal postings. Our system continuously downloads postings from selected discussion forums and uses data mining to identify hot topics and cluster authors into word-based user profiles. To improve security, our system monitors and analyzes plain text sources like internet news and blogs using text data mining. Text mining and pattern recognition classify legal and illegal posts into groups. This system reduces internet crime.

Introduction:

Internet discussion has increased legal and illegal activities. Internet forums spread copyrighted content, threats, and online gambling before mainstream media does. Police want to monitor discussion forums for criminal activity and collect evidence. This project proposes data mining to detect criminal activity and illegal postings. Data mining identifies hot topics and clusters authors into word-based user profiles as our system continuously downloads postings from selected discussion forums. Our system analyzes internet news and blogs using text data mining to improve security. Text mining and pattern recognition group legal and illegal posts. It lowers internet crime.

Objectives:

This project aims to use data mining to monitor suspicious forum discussions. The data mining algorithm detects criminal activity and illegal postings. It continuously downloads postings from selected discussion forums and uses data mining to identify trending topics. Word-based user profiles also group authors. A text data mining system that analyzes internet news and blogs to improve security is the goal. The system will classify text into legal and illegal groups, reducing internet crime.

Project Details:

The proposed system will analyze forum discussions using data mining. It will continuously download postings from selected discussion forums and use data mining algorithms to identify criminal activities and illegal postings. Word-based user profiles will group authors by contributions and discussions. The system will analyze online plain text sources like news and blogs to identify illegal activity patterns and trends to improve security. The system will classify text into groups to determine legality and reduce internet crime.

Conclusion:

The proposed system effectively monitors suspicious forum discussions. Data mining detects criminal activity and illegal postings. The system uses word-based user profiles and continuous downloads from selected discussion forums to identify trending topics and group authors. The system improves security by identifying illegal activity patterns in online plain text sources. Text classification helps determine legality, reducing internet crime. This system could help solve the internet’s growing influence on legal and illegal activities.

Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.