Companies Image Evaluation Using Social Media and Sentiment Analysis
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 reg
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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-ofwords 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. Keywords Company Image · Social Media Analysis · Sentiment Analysis · Semantic Web · Ontology
1 Introduction Accurately understanding the way in which customers perceive the image of a company has long been considered a key element for its success (Delcea et al. 2015). However, constantly monitoring the factors that could positively or L.-A. Cotfas (*) · C. Delcea Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Bucharest, Romania e-mail: [email protected]; [email protected] R.-M. Păun Webster University, Bangkok, Thailand e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 M. H. Bilgin et al. (eds.), Eurasian Business Perspectives, Eurasian Studies in Business and Economics 14/2, https://doi.org/10.1007/978-3-030-52294-0_18
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negatively influence the company image has been a daunting task, due to both their number and the difficulty in collecting up-to-date information. Analyzing the image of the company has been performed for example by employing user surveys, which are both time and effort consuming, while many times failing to capture a comprehensive overview of the company image, due to the limited number of respondents. The usage of social media networks has been constantly increasing in the last few years. Among them, one of the most popular networks is Twitter, which allows users to post messages with a maximum length of 280 characters. Many of the messages published on this social media network, also known as tweets, contain sentiment indications regarding companies and their products and services (Pak and Paroubek 2010; Kontopoulos et al. 2013). Thus, by analyzing the messages posted on social media, it becomes possible to know the opinion of a huge number of actual or potential customers in near real time. Understanding the perception expressed in social media messages requires sentiment analysis, a growing area of nat
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