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Artificial Intelligence in Marketing: a text mining and topic modeling approach
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Autores
Resumo(s)
This research uses a Text Mining approach to analyze the literature. This methodology creates Artificial Intelligence
(AI) dimensions and clusters in literature to find patterns and trends about its application in Marketing, resulting in
a dataset of 2,255 articles on the AI and marketing topic by the leading publishers up to 2023. Since textual sources
take big data format, this paper's techniques present several scalable advantages compared to other
methodologies. This approach uses two methods to overcome the limitations: an API, a visual pictorial
representation that summarizes the topics discovered. The results show that Data Modeling systems are the three
most frequent terms in all the abstract tokens showing more than 2,000 occurrences. Trends such as Natural
Language processing (sentiment, analysis, text, image, video, and language), Machine Learning, Algorithms,
Expert Systems, and Social Media, particularly Twitter, have been unveiled from the data analysis. However, a
clear description of AI in Marketing is still needed. Overall, this paper presents an approach with several scalability advantages compared to previous methods, a crucial aspect of dealing with big data.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
The results of this research have been published in the journal Tourism & Management Studies: https://doi.org/10.18089/tms.20250103
The results of this research have been published in the journal Tourism & Management Studies: https://doi.org/10.18089/tms.20250103
Palavras-chave
Artificial Intelligence Marketing Literature analysis Literature dimensions Text mining Topic modeling SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 10 - Reduced inequalities SDG 11 - Sustainable cities and communities SDG 12 - Responsible production and consumption SDG 17 - Partnerships for the goals