Application of text mining in smart lighting literature - an analysis of existing literature and a research agenda

There has always been a gap between research and engineering practices across almost all disciplines. The nature of these gaps are not identified; However, in order to be able to bridge these gaps a comprehensive understanding is required. In this study, in order to provide research agenda, we examine existing literature and users perception in smart lighting business. We consider two sources of data for this analysis 1-lighting research literature that reflects the research phase and 2-Amazon reviews about two smart lighting products that represent customers’ perceptions reflecting the development phase. We use text mining and analyze both data sources by topic modeling and sentiment analysis. We conducted a probabilistic aspect based sentiment analysis. One of the results of this analysis showed that while the research community is drastically concerned about energy consumption, the end users were excited about color changing ability in smart lighting products.