Exploring the applications of artificial intelligence in marketing: A topic modelling analysis
Main Author: | |
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Publication Date: | 2025 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10071/32950 |
Summary: | Integrating Artificial Intelligence (AI) into marketing has revolutionised this field, offering new avenues of innovation and efficacy. This study aims to unveil the prevailing trends and patterns within the current academic literature about AI applications in Marketing and propose future research directions. The study conducted a comprehensive review by analysing 2,255 articles from the Scopus database from 1980 to 2022, employing a Text Mining approach and Latent Dirichlet Allocation (LDA) topic modelling. The findings suggest trends in research topics of Learning Models, Expert Systems, Natural Language Processing, Social Media, and Consumer Centricity. Outlier topics related to Health, Market Forecast, and Technology Impact on Youth have caught the researchers’ attention. The associated challenges and risks, ethical considerations, and practical implications were presented for each topic. This study develops literature on AI-driven marketing by unearthing the trend topics and suggesting a research agenda. At the same time, it offers actionable insights for businesses to enhance consumer engagement and ethical AI adoption in marketing practices. |
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Exploring the applications of artificial intelligence in marketing: A topic modelling analysisArtificial intelligenceMarketingLiterature analysisText miningTopic modellingIntegrating Artificial Intelligence (AI) into marketing has revolutionised this field, offering new avenues of innovation and efficacy. This study aims to unveil the prevailing trends and patterns within the current academic literature about AI applications in Marketing and propose future research directions. The study conducted a comprehensive review by analysing 2,255 articles from the Scopus database from 1980 to 2022, employing a Text Mining approach and Latent Dirichlet Allocation (LDA) topic modelling. The findings suggest trends in research topics of Learning Models, Expert Systems, Natural Language Processing, Social Media, and Consumer Centricity. Outlier topics related to Health, Market Forecast, and Technology Impact on Youth have caught the researchers’ attention. The associated challenges and risks, ethical considerations, and practical implications were presented for each topic. This study develops literature on AI-driven marketing by unearthing the trend topics and suggesting a research agenda. At the same time, it offers actionable insights for businesses to enhance consumer engagement and ethical AI adoption in marketing practices.Universidade do Algarve2025-01-08T12:39:25Z2025-01-01T00:00:00Z20252025-01-08T13:07:55Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/32950eng2182-845810.18089/tms.20250103Rita, P.Omran, W.Ramos, R. F.Costa, T.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-01-19T01:17:20Zoai:repositorio.iscte-iul.pt:10071/32950Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:38:54.968421Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
title |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
spellingShingle |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis Rita, P. Artificial intelligence Marketing Literature analysis Text mining Topic modelling |
title_short |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
title_full |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
title_fullStr |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
title_full_unstemmed |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
title_sort |
Exploring the applications of artificial intelligence in marketing: A topic modelling analysis |
author |
Rita, P. |
author_facet |
Rita, P. Omran, W. Ramos, R. F. Costa, T. |
author_role |
author |
author2 |
Omran, W. Ramos, R. F. Costa, T. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Rita, P. Omran, W. Ramos, R. F. Costa, T. |
dc.subject.por.fl_str_mv |
Artificial intelligence Marketing Literature analysis Text mining Topic modelling |
topic |
Artificial intelligence Marketing Literature analysis Text mining Topic modelling |
description |
Integrating Artificial Intelligence (AI) into marketing has revolutionised this field, offering new avenues of innovation and efficacy. This study aims to unveil the prevailing trends and patterns within the current academic literature about AI applications in Marketing and propose future research directions. The study conducted a comprehensive review by analysing 2,255 articles from the Scopus database from 1980 to 2022, employing a Text Mining approach and Latent Dirichlet Allocation (LDA) topic modelling. The findings suggest trends in research topics of Learning Models, Expert Systems, Natural Language Processing, Social Media, and Consumer Centricity. Outlier topics related to Health, Market Forecast, and Technology Impact on Youth have caught the researchers’ attention. The associated challenges and risks, ethical considerations, and practical implications were presented for each topic. This study develops literature on AI-driven marketing by unearthing the trend topics and suggesting a research agenda. At the same time, it offers actionable insights for businesses to enhance consumer engagement and ethical AI adoption in marketing practices. |
publishDate |
2025 |
dc.date.none.fl_str_mv |
2025-01-08T12:39:25Z 2025-01-01T00:00:00Z 2025 2025-01-08T13:07:55Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/32950 |
url |
http://hdl.handle.net/10071/32950 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2182-8458 10.18089/tms.20250103 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidade do Algarve |
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Universidade do Algarve |
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