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Brands And Chatbots: An Overview Using Machine Learning

Camilo R. Contreras () and Pierre Valette-Florence ()
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Camilo R. Contreras: UGA INP IAE - Grenoble Institut d'Administration des Entreprises - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes
Pierre Valette-Florence: UGA INP IAE - Grenoble Institut d'Administration des Entreprises - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes

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Abstract: As artificial intelligence (AI) and machine learning techniques have evolved to improve Natural Language Processing, human language understanding has enabled human-machine communication tools to be increasingly deployed by brands. Conversational agents or chatbots are among the most widely positioned in recent years of technological evolution, with unprecedented social skills. They have become a cornerstone for supporting brands' interactions with consumers in both digital and physical spaces. Due to the chatbots' massive scientific boom and the relevance, they are gaining for brand management, its practitioners and scholars wake a growing interest in understanding the epistemological map on which this topic is embedded. To discover the main cross-cutting issues, the current and emerging research topics pragmatically. This study proposes using Machine Learning techniques in the scientific production body of this fruitful branch of marketing. Our instruments are twofold; first, we applied Latent Dirichlet Allocation (LDA) to identify eight thematic groups. Second, Dynamic Topic Models (DTM) reveals that the current research streams are oriented to technological advancement. In addition, research on chatbots and brand management is also emerging in two possible directions.

Keywords: Brand Management; Conversational Agents; Literature Review; Machine Learning (search for similar items in EconPapers)
Date: 2021-11-03
New Economics Papers: this item is included in nep-ain, nep-big and nep-cmp
Note: View the original document on HAL open archive server: https://hal.science/hal-04153038v1
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Published in Society for Marketing Advances, 2021, Nov 2021, Orlando, FL, United States

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