In this study, blog data were collected and network parameters were captured to represent three common measurements of online Word-Of-Mouth: intensity, influence level, and dispersion. These parameters were then analyzed using a General Estimating Equation (GEE) model to test their effects on average weekly movie box office receipts. Findings indicated that all three parameters were significant in the model. The aggregated degree, representing WOM intensity, was positively significant, which was consistent with results from extant research. Further, diameter of a network, representing WOM dispersion, was observed to be positively significant, which validated the importance of spreading WOM as far as possible. Counter-intuitively, the aggregated size node, representing WOM influence level, was ascertained to be negatively significant, which might be explained by the possible negative stance from opinion leaders with high influence level. Applying network analysis methodology to blog entries, the present work differentiated itself from extant WOM literature that has focused chiefly on content analysis. The findings also provided managerial insights to companies interested in utilizing blogs as online WOM for marketing initiatives and implications for future research.
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