Authors:
R. E. Loke
and
R. E. Lam-Lion
Affiliation:
Centre for Market Insights, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands
Keyword(s):
Sentiment Analysis, Corporate Reputation, Natural Language Processing, Semantic Search, Scraping.
Abstract:
Corporate reputation can be defined as the overall assessment of a company’s performance over time (Kircova & Esen, 2018). Organizations with a positive corporate reputation create a competitive advantage and are more likely to influence customer’s behaviors and attitudes (Kircova, 2018). Measuring corporate reputation from online data is an increasingly important area in business studies because the amount of opinions and comments is increasingly growing on the internet and has become very accessible to strangers (Shayaa, 2018). Traditionally, corporate reputation is measured with well-known approaches such as surveys, qualitative interviews, and sample groups (Smith, 2010). Researchers like Fombrun, Fonzy and Newburry (2015) developed instruments to measure corporate reputation and predictivily modeled its impact on stakeholder outcomes. So far, however, there has been little attention in the literature on sophisticated measurement techniques for corporate reputation that can be ap
plied to online reviews from the public web. This paper applies sentiment analysis in combination with semantic search as a suitable technique to explore how employees perceive organizations. By using our toolbox, organizations can adapt to market changes and cater to stakeholders’ needs. Also, it can be used to raise awareness for organizations that are unaware of negative reviews online.
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