Technology Futures From Passive Crowdsourcing
Erica Briscoe, Scott Appling, Joel Schlosser · IEEE Transactions on Computational Social Systems · 2016
Efforts to predict emerging, new, or disruptive technologies use various analyses and data sources to derive indicators and subsequent forecasts about technological innovations, including quantitative (such as bibliometric analysis) and qualitative methods (such as expert elicitation). We describe a novel approach for harnessing a collective (crowdsourced) predictive ability available through publicly made technology-related statements by automatically determining significant convergences on technology forecasts. We evaluate our approach using a corpus of science-related articles and demonstrate that passive crowdsourcing may be a powerful source of technology-related predictive intelligence.