Talking To Me? Creating Networks From Online Community Logs

R.W. Helms, W Ai, J. Cranefield

Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review


Online communities offer many potential sources of value to individuals and organisations. However, the effectiveness of online communities in delivering benefits such as knowledge sharing depends on the network of social relations within a community. Research in this area aims to understand and op-timize such networks. Researchers in this area employ diverse network creation methods, with little focus on the selection process, the fit of the selected method, or its relative accuracy. In this study we evaluate and compare the performance of four network creation methods. First we review the literature to identify four network creation methods (algorithms) and their underlying assumptions. Using several data sets from an online community we test and compare the accuracy of each method against a baseline (‘actual’) network determined by content analysis. We use visual inspection, network cor-relation analysis and sensitivity analysis to highlight similarities and differences between the methods, and find some differences significant enough to impact study results. Based on our observations we argue for more careful selection of network creation methods. We propose two key guidelines for re-search into social networks that uses unstructured data from online communities. The study contributes to the rigour of methodological decisions underpinning research in this area.
Original languageEnglish
Title of host publicationProceedings of the 24th European Conference on Information Systems, Instanbul, Turkey.
Subtitle of host publicationResearch Papers
PublisherAIS Electronic Library
Publication statusPublished - 2016
Event24th European Conference on Information Systems - Istanbul, Turkey
Duration: 12 Jun 201615 Jun 2016


Conference24th European Conference on Information Systems
Abbreviated titleECIS 2016


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