Measuring public acceptance with opinion mining: The case of the energy industry with long-term coal R&D investment projects

Kalle Nuortimo

Abstract


New Web 2.0-based technologies have emerged in the field of competitor/market
intelligence. This paper discusses the factors influencing long-term product development,
namely coal combustion long-term R&D/Carbon Capture and Storage (CCS) technology, and
presents a new method application for studying it via opinion mining. The technology market
deployment has been challenged by public acceptance. The media images/opinions of coal power
and CCS are studied through the opinion mining approach with a global machine learning based
media analysis using M-Adaptive software. This is a big data-based learning machine media
sentiment analysis focusing on both editorial and social media, including both structured data
from payable sources and unstructured data from social media. If the public acceptance is
ignored, it can at its worst cause delayed or abandoned market deployment of long-term energy
production technologies, accompanied by techno-economic issues. The results are threefold:
firstly, it is suggested that this type of methodology can be applied to this type of research
problem. Secondly, from the case study, it is apparent that CCS is unknown also based on this
type of approach. Finally, poor media exposure may have influenced technology market
deployment in the case of CCS.


Keywords


Carbon Capture and Storage, CCS, greenhouse gas control, market deployment, opinion mining, public acceptance, web-intelligence

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