Innovative Methods for Business Education using Isotope Linking on Anonymous Readers’ Comments

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Abstract

The paper presents the importance of analysis isotopes on anonymous readers’ comments as an important part of deep interpretation of texts. Furthermore, we describe a classification methodology of the anonymous readers’ comments on online articles, through the overlapping of isotopes, which completed the traditional analytical methods. Automatic recognition of isotopes is an important topic in Natural Language Processing (NLP), especially in the semantic disambiguation. The aim of this article is the automatic comparative analysis of the identified isotopes in articles and comments, which reveals an important part of online behavior. Moreover, we present a new tool that classifies the online commentators based on existing resources, open-source or freely available for research purposes. This study is intend to help direct beneficiaries (journalists, business, education, managers, PR specialists), but also specialists and researchers in the field of natural language processing, linguists, psychologists, etc.

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