Using Text Mining to Measure Diffusion of Innovation

• In Event: Advances in Text Analysis Methods

Abstract

As one of the most popular lines of communication research, diffusion of innovation has been invariantly measured by survey method through face-to-face, telephone, mail/email/online questionnaire, etc. As in other uses of survey method, measurement of diffusion of innovation suffers from high labor cost, long execution time, pro-adoption biases, and other problems. In the current study, we demonstrate how text mining method is used to measure diffusion of innovation from social media data. Text mining not only is cheaper and faster to implement, but also minimizes self-reported biases. A major challenge for text mining method is the data (regardless of its size) that may not be representative of the population under study. As such, it is necessary to validate the results with representative sample(s) from an independent source.

Authors

• Yafei ZHANG, City University of Hong Kong

• Lu Guan, City U of Hong Kong

• Hexin Chen, City U of Hong Kong

• Jonathan J. H. Zhu, City U of Hong Kong