Analysis of online social network traffic can identify a cascade as it flows through a community but, often, the reasons for its initiation are tacit. Commercial measures of online influence focus on the consequences of influence not the causes and have been criticized as lacking efficacy. This research uses social capital and personal influence theories to investigate the characteristics and behaviours that allow certain network nodes to be able to cascade ideas (or memes) through networks. The relationships between structural, relational and cognitive sources of social capital and two distinct dimensions of influence are investigated using: interviews with experts in the field, focus groups of social network users and 1,970 respondents from three large-scale online communities. Data has been analysed using Structural Equation Modelling (SEM) and allows the researcher to develop robust conclusions on the antecedents to influence. These help to explain recent contradictory findings by different researchers in studies using Social Network Analysis (SNA). The dimensions of influence measured are: respondents’ intention to propagate the message and; the extent to which the message has affected their perception of the subject. The model of influence that leads to both dimensions is strikingly similar; presenting strong support for the notion that contagion-based cascades through networks are predictors of perception change. The paper proposes a bridge between the theories of social capital and personal influence and this is considered an original contribution to these well-established theories. Techniques are suggested which can help organisations to identify opinion-leaders and, if required, subvert or redirect the nature of their influence. Other applications are considered in the fields of: Innovation (identification of lead users); Virtual Organisations (engaging with informal leaders and influencers in networks); Cyber- Defence (identification and subversion of online radicalisation).
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:665374 |
| Date | January 2013 |
| Creators | Archer-Brown, Chris |
| Contributors | Joinson, Adam ; Piercy, Niall |
| Publisher | University of Bath |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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