The summary of our experiences from „Innovation Signals“ are published now:
Online communities are seen as valuable knowledge source about customers’ needs and interests. Innovation research also tries to analyze content from online communities to detect signals for future innovations. Within this contribution the theory of signals for future developments, existing approaches are introduced.
Building upon this introduction, we describe the Austrian research project “Innovation Signals” that aims to develop and implement a technology-enhanced analysis of signals for future developments by analyzing user-generated content from selected online communities. Besides automatic data extraction and statistics the approach tries to make sense through structured content analysis. Therefore, the approach combined so-called qualitative research with quantitative research, as well as automatic monitoring and analysis with manual social research.
Part of this research project was the identification of innovation signals for three companies from different fields/branches (sport, energy, and mobility). Within this contribution we describe and reflect on our experiences within these settings and on additional findings based on the project. These are guidelines for social media mining and a comparison of existing approaches of technology-usages for weak signal detection. The authors also discuss practical implications derived from their experiences, as well as future opportunities for further research.
The project plan:
- Eckhoff, Robert; Frank, Jakob; Markus, Mark; Lassnig, Markus; & Schön, Sandra (2015). Detecting Innovation Signals with Technology-Enhanced Social Media Analysis –
Experiences with a hybrid approach in three branches. In: International Journal of Innovation and Scientific Research, Volume 17, Issue 1, August 2015, Pages 120–130 URL: http://ijisr.issr-journals.org/abstract.php?article=IJISR-15-065-09