Big Data in Criminal Cases – Digital Evidence Analysis with QDA Miner and WordStat by Dr. Uwe Ewald
The presentation will show that QDA Miner and WordStat is well suited to a) manage and analyse big data electronic evidence in criminal proceedings, and b) that “practical analysts” (i.e. including defence attorneys or private investigators and analysts) can efficiently apply QDA Miner and WordStat – if supported in learning to use these tools for their specific purposes and a certain methodology is applied.
Yet, if there is so much IT-forensic software on the market, what is the special benefit using Provalis Software to process and analyse electronic evidence?
The short answer is: QDA Miner and WordStat, applying the mixed method approach, fit in a particular way the unique challenge in analysing mass digital evidence in criminal cases, this to close the gap between “crime relevant patterns” within evidentiary data and finding the “smoking gun” using interactive functionality (e.g. heatmaps).
QDA Miner in combination with WordStat offers a variety of analytical powers which allow to go beyond the functionality of most IT-forensic software in particular when it comes to detailed textual content analysis e.g. of witness statements.
The presentation follows the agenda below to show how QDA Miner and WordStat answer these challenges:
• Defining relevant analytical questions – Operating Model (OM) Prosecution Theory
• Turning the Prosecution Theory OM into Data Structure Model – Variable and Coding Structure
• (Incremental) Inclusion of Raw Data (digitized and digital data) – Appending Cases, Merging Projects (witness statements + other textual data)
• (Reiterative) Analytical Process – Analytical Functions/MM in QDA Miner and WordStat
• Presentation/Visualization of Findings – Visualization Tools