Open Research for Open Data: Integration of Netnography and Text Mining for Consumer Insight Generation from Online Social Media

Abstract: The thesis aims at enhancing the understanding of netnography and text mining methods, as well as creating a mixed methods research framework that integrates the two methods for consumer insight generation from online social media in a commercial consumer research context. It relies on a qualitative and abductive approach. The thesis finds that the suitability for integration of netnography and text mining is high. The thesis also finds that the approach consists of three key participants: researcher, insight user and netizen and follows a within-and-across stage mixed-model design typology. A research model for the mixed methods research approach is further created, which consists of the following sections: (1) New research requirement; (2) Definition of research field; (3) Social media selection and data collection; (4) Netnographical and text mining analysis, interpretation and legitimation; (5) Insight; (6) Value. The information exchange dynamics between the key participants, different stages and the two methods are also analyzed. The thesis finds that each stage in the process can result in moving to the next or previous stage and that during this process the two methods interact through elements, inter-transform and holistically unite as two opposites. The thesis ends by a discussion of the results, including their managerial implications, reflection of the research as well as providing suggestions for future research.