Using Text Mining to Measure Diffusion of Innovation

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Publication statusPublished - 28 May 2017

Conference

TitleThe 67th Annual Conference of the International Communication Association : Interventions: Communication Research and Practice
LocationHilton San Diego Bayfront Hotel
PlaceUnited States
CitySan Diego
Period25 - 29 May 2017

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.

Citation Format(s)

Using Text Mining to Measure Diffusion of Innovation. / Zhang, Yafei; Guan, Lu; Chen, Hexin; Zhu, Jonathan.

2017. Paper presented at The 67th Annual Conference of the International Communication Association : Interventions: Communication Research and Practice, San Diego, United States.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)Not applicablepeer-review