Zeini, Sam, et al. "The impact of measurement time on subgroup detection in online communities." State of the art applications of social network analysis (2014): 249-268.

As internet-based services become increasingly integral to communication and collaboration within communities, the digital traces they leave behind offer valuable real-world data for research. Social Network Analysis (SNA) techniques, particularly community detection methods like the Clique Percolation Method (CPM) and Link Community detection (LC), are commonly used to analyze these data. In this study, data from open source developer communities (such as mailing lists and log files) were analyzed using these methods, with a focus on detecting overlapping clusters. The influence of varying time windows for data measurement on subgroup detection was examined, akin to adjusting photography settings for optimal clarity. Factors affecting resolution of subgroup structures were identified, with implications for tailoring analysis techniques to different community types.