Evaluating Criminal Networks with PEVNET
Amer Rasheed, Uffe Kock Wiil · 2015
Evaluation of network visualization tools in software engineering is a tricky task. There are a number of factors, contradictions, and preferences of investigative analysts that are to be kept in consideration while designing the experiment. Complexity in data, computational overhead to reach the targeted information and scarcity of a standard platform may slow down the investigation process. In this research paper, we have made the evaluation of some of the new features of our proposed framework, PEVNET, by conducting an experiment. There were twenty four participants who had evaluated the system. The experiment was performed in two phases. In the first phase, a usability evaluation and qualitative feedback was carried out to check whether the PEVNET framework provided adequate results to the users. The qualitative feedback was performed by considering two aspects: the ease of use and the functionality. We have conducted an evaluation of the newly inducted features into PEVNET. These include the 'Pie-chart feature', 'Trend analysis Feature', 'Graphical trend analysis feature', and 'Encircle feature'. In the second phase, the comparison of the PEVNET had been performed against some other state-of-the-art tools. These tasks were to be performed in the groups of participants. We found that the participants of the PEVNET group performed the tasks faster, in respect to the respective features, as compared to the other techniques used in the experiment. Further, we have found that the network visualization of the PEVNET framework, based on the experimental results, had gotten satisfactory feedback from the majority of the participants. The case study of Chicago Narcotics datasets was used. We believe that by evaluating the PEVNET in this research paper, we will be able to check the effectiveness of our proposed features.