Professional Association Networks Based on Semantic Similarity of Papers Presented in Divisions versus Formal Membership Networks

We investigated possible causal relationships between a professional association’s division network structure based on comemberships, and the division network structure based on the semantic similarity of papers presented at annual meetings. Data from the International Communication Association (ICA), a basicresearch focused organization of academic social scientists with 21 divisions, provide for an analysis at two points in time, 2007 and 2011. QAP correlations among the four networks entered into a quasi-experimental cross-lagged correlation design suggested evidence for possible causality. Compared to the no cause baseline, the time 1 co-membership network structure was a significant predictor of the time 2 semantic division network structure. The reverse relationship was not significant. As well, there is considerable reduction of the size of the synchronous correlation of the semantic and co-membership division networks from time 1 to time 2. Noteworthy was also the pattern of diachronic association of the same kind of network. The semantic division network at time 1 explained only 31% of the same network at time 2. Likewise, the co-membership network at time 1 explained only 25% of that network at time 2. This would be consistent with the basic research focus of the association. Such a focus privileges novelty. The paper uses theory to form the research questions and interpretations. Because of the limitations of the statistical model, and the case study design, these results should be taken as exploratory and suggestive. Future research may reduce these limitations.