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Companies Image Evaluation Using Social Media and Sentiment Analysis

In: Eurasian Business Perspectives

Author

Listed:
  • Liviu-Adrian Cotfas

    (Bucharest University of Economic Studies)

  • Camelia Delcea

    (Bucharest University of Economic Studies)

  • Ramona-Mihaela Păun

    (Webster University)

Abstract

While the literature contains many slightly different definitions for the image of a company, they all put great emphasis on its importance. Many of the messages posted on social media networks nowadays contain strong sentiment and emotion indications regarding almost any topic, therefore turning them into a rich and almost real-time data source for analyzing the public’s opinion on various subjects, including many of the factors that can influence the image of companies. Thus, in this chapter we propose a natural language processing (NLP) approach for monitoring and evaluating the companies’ image by extracting information from social media messages posted on Twitter. The messages are analyzed using a bag-of-words sentiment analysis approach. The results of the analysis are stored as semantically structured data, thus making it possible to fully exploit the possibilities offered by semantic web technologies, such as inference and accessing the vast amount of knowledge in Linked Open Data, for further analysis.

Suggested Citation

  • Liviu-Adrian Cotfas & Camelia Delcea & Ramona-Mihaela Păun, 2020. "Companies Image Evaluation Using Social Media and Sentiment Analysis," Eurasian Studies in Business and Economics, in: Mehmet Huseyin Bilgin & Hakan Danis & Ender Demir (ed.), Eurasian Business Perspectives, pages 277-286, Springer.
    • Handle: RePEc:spr:eurchp:978-3-030-52294-0_18
    DOI: 10.1007/978-3-030-52294-0_18
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