Analysing Online Social Networks from a Soft Systems Perspective

In recent years online communities have become popular as a way for dispersed members to interact and share ideas. However, there is limited research on the systemic analysis of such groups. In this paper the authors draw on systems research to suggest that one can only understand or interpret data gathered from an online group by assigning meaning to it in the context of a wider ‘system'. Here they demonstrate that conventional methods of offline group analysis are ineffective when applied within online communities. As an alternative they offer a means of importing big data from a community on social media and identifying the kinds of information that would be typically gathered during an offline systemic analysis into a problem situation. The authors offer as an aid to managers a framework that identifies appropriate Social Network Analysis (SNA) metrics (from the imported data) that corresponds to soft systems concepts. During their analysis of a community on Twitter they found that their ideas provided a way to gain a more holistic understanding of the roles and interactions in a virtual community. The authors also found examples of the use of informal power in the Twitter community under study. This information can be useful to managers when producing marketing plans, during product development and when identifying opportunities for growth.