Wioletta Soko?owska, Tymoteusz Hossa, Karol Fabisz, Witold Abramowicz, Mateusz Kubaczyk. Sentiment Analysis as a Source of Gaining Competitive Advantage on the Electricity Markets[J]. Journal of Electronic Science and Technology, 2015, 13(3): 229-236. DOI: 10.11989/JEST.1674-862X.505261
Citation: Wioletta Soko?owska, Tymoteusz Hossa, Karol Fabisz, Witold Abramowicz, Mateusz Kubaczyk. Sentiment Analysis as a Source of Gaining Competitive Advantage on the Electricity Markets[J]. Journal of Electronic Science and Technology, 2015, 13(3): 229-236. DOI: 10.11989/JEST.1674-862X.505261

Sentiment Analysis as a Source of Gaining Competitive Advantage on the Electricity Markets

doi: 10.11989/JEST.1674-862X.505261
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  • Author Bio:

    Wioletta Sokołowska research interests include energy system, big data, energy forecasting, future energy markets, energy market modeling, sentiment analysis, business process modelling, and simulation;
    Witold Abramowicz areas of interest cover information acquisition and filtering, w.abramowicz@gmail.com

  • Authors’ information: Witold Abramowicz
  • Received Date: 2015-05-25
  • Rev Recd Date: 2015-07-09
  • Publish Date: 2015-09-24
  • The electricity retail markets are evolving toward more competitive and customer-oriented. The deployment of smart meters and a wealth of new technologies create customers' eagerness for taking control of their electricity consumption. By being better-informed about the energy usage, people are encouraged to switch deals among existing suppliers or move to a new energy provider. Moreover, as customers are more socially interconnected, the Internet portals and social media become a place for discussion, comparison, and evaluation of the available offers. Unfortunately, in case of the energy sector there is a lack of understanding that such information, when taken into account and properly analyzed, can be a completely new and a powerful source of competitive advantage.In the paper, we introduce a solution that the use of quasi real-time automated sentiment analysis on the energy suppliers and the relevant aspects of their offers may enable energy companies to adapt quickly to changing circumstances, prevent potential customer churn, and harness new business opportunities.
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    Periodical cited type(2)

    1. Hernes, M.. Consensus Theory for Cognitive Agents’ Unstructured Knowledge Conflicts Resolving in Management Information Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019. DOI:10.1007/978-3-662-58611-2_1
    2. Pan, Q., Zheng, X., Chen, G. A Mix-model based Deep Learning for Text Sentiment Analysis. 2018. DOI:10.1109/ICCBB.2018.8756420

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