Affiliations: [a] Telmar Inc., New York, NY, USA | [b] Kingsborough Community College of CUNY, Brooklyn, NY, USA | [c] Vesaria, LLC, Baltimore, MD, USA
Correspondence:
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Corresponding author: I. Mandel, Telmar Inc., 470 Park av. South, New York, NY 10016, USA. E-mail: [email protected].
Abstract: Traditional statistical modeling in applied marketing is a huge area both for scientists and practitioners. Agent Based Models (ABM), on the other hand, are comparatively new field, yet gaining its weight very fast in last decade. The purpose of this article is to show some aspects of interrelations between these two types of models and address the common challenges, based on the concept of self-organized ABM. In particular, the complicated problems of semantic analysis of marketing texts and the extraction of the numerical values (a problem scarcely discussed in the literature) are considered; its importance is demonstrated on some examples from marketing texts. A Marketing Net Ontology draft version is proposed. An ABM for typical business web oriented process is designed. On its example it is shown, how problems of optimal ABM parameters tuning may be better understood using proposed statistical techniques.
Keywords: Marketing, statistical modeling, natural language processing, self-organized agent based models, sociosystemics, marketing ontology
