Influencing & measuring word of mouth on Twitter


The interest for writing this paper started as a quest for measuring identifying digital influencers. During the process I increasingly stumbled upon the difficulties & complications when identifying influencers. Instead the research increasingly focussed on measuring the return on digital activities. This was mainly fueled by the gap between the great availability of data and other other hand the lack of measurement.

Both the professional and academic field have a strong desire to understand and measure influence. Historically it used to be problematic to measure the influence a brand has on consumers. The open ecosystem of Twitter however, allows for investigation of the word of mouth between consumers. Inspired by the challenge, and considering the gap in literature and its practical relevance, I chose to investigate prediction and measurement of influence over word of mouth networks. The paper thereby plays upon the transition between traditional (sender-receiver) communication to the web 2.0 media landscape in which consumers increasingly disseminate their knowledge, experiences, and opinions with fellow consumers. While the paper focuses on the social medium Twitter, its findings may be applied to other social media as well.

I'm looking forward to the future work of professors dr. J.M.M. Bloemer and dr. M.J.H. van Birgelen, who have shown interest in the work and data of this paper. For me their interest in this paper is an acknowledgement for the energy and time I have invested in this study.

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