TwiVisual: A Forensics Visualization Tool for Twitter with Link and Timeline Analysis

Abstract

The substantial volume of Twitter data generation poses challenges for digital forensics. Due to the huge amount of Twitter data, Twitter platform occurs the increasing cybercrime rate has led investigators to perform extensive manual analysis on Twitter. Therefore, this study proposed TwiVisual, a forensic visualization tool which integrating with link and timeline analysis to enhance the effectiveness of analysing massive volume of Twitter data then provide comprehensive insights for digital forensic investigations. The modules of TwiVisual involves create case module, visualization analysis module and reporting module. Visualization analysis module involves 4 submodules which are file importation submodule, data tabulation submodule, link analysis submodule and timeline analysis submodule. Functional testing results confirm TwiVisual ability to create case, title and description display, adjust size of graph, save graph image and generate report. Forensic analysis testing was conducted to identify the functions of display network graph for link analysis and display line graph for timeline analysis. The user acceptance testing shows positive feedback to confirm the TwiVisual functions and performance. In conclusion, TwiVisual has been developed to analyse Twitter data using both link and timeline analysis methods.