An approach to measuring influence and cognitive similarity in computer-mediated communication
While many explanations of influence have been proposed there is still debate over which is correct even though most are supported by empirical evidence. This uncertainty has been attributed to there being too little evidence of real-world influence networks, and an inability to separate influence from cognitive similarity, that is, a pre-existing like-mindedness, attitude or way of thinking shared among participants. This paper proposes theme resonance, a new metric for measuring both influence and cognitive similarity between and among participants in the same online conversation. Theme resonance is derived from two textual content analysis systems: Centering Resonance Analysis and qualitative thematic modeling. The use of theme resonance is demonstrated by constructing influence networks using online conversations in ten weblogs, allowing the propagation of new conversational themes to be traced from initiator though subsequent propagators. A method of separating influence from like-mindedness is also demonstrated. Depending on the metric chosen influence and its susceptibility were found both to be opposite ends of the same spectrum, and distinct attributes. In either case the majority of blog participants are close to the low end of each characteristic. However, those at the higher ends are shown to be easily and distinctly identified.
influence cognitive similarity discourse analysis language similarity