,
pages 179-195
Personality and Susceptibility to (Targeted and Tailored) Advertising for Green Products: A Machine-Learning Approach Based on Online Reviews
2
Amsterdam, the Netherlands
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Publication type: Book Chapter
Publication date: 2023-04-10
SJR: —
CiteScore: —
Impact factor: —
ISSN: 26260328, 26260336
Abstract
In recent years, we have witnessed a sharp increase in consumers’ use of various digital devices. This has revealed large amounts of digital trace data, i.e., data on consumers’ online activities, contributions, interactions and communications. Concurrent with the ubiquity of digital devices, technological advances in computing and data analytics such as Natural Language Processing (NLP) and the application of Machine Learning (ML) have arisen, making it possible to discover patterns in the massive quantities of digital data available for marketing purposes.
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Citations from 2024:
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GOST
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Zarouali B., Schreuder J. Personality and Susceptibility to (Targeted and Tailored) Advertising for Green Products: A Machine-Learning Approach Based on Online Reviews // European Advertising Academy. 2023. pp. 179-195.
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Zarouali B., Schreuder J. Personality and Susceptibility to (Targeted and Tailored) Advertising for Green Products: A Machine-Learning Approach Based on Online Reviews // European Advertising Academy. 2023. pp. 179-195.
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RIS
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TY - GENERIC
DO - 10.1007/978-3-658-40429-1_13
UR - https://doi.org/10.1007/978-3-658-40429-1_13
TI - Personality and Susceptibility to (Targeted and Tailored) Advertising for Green Products: A Machine-Learning Approach Based on Online Reviews
T2 - European Advertising Academy
AU - Zarouali, Brahim
AU - Schreuder, Jurrian
PY - 2023
DA - 2023/04/10
PB - Springer Nature
SP - 179-195
SN - 2626-0328
SN - 2626-0336
ER -
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BibTex (up to 50 authors)
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@incollection{2023_Zarouali,
author = {Brahim Zarouali and Jurrian Schreuder},
title = {Personality and Susceptibility to (Targeted and Tailored) Advertising for Green Products: A Machine-Learning Approach Based on Online Reviews},
publisher = {Springer Nature},
year = {2023},
pages = {179--195},
month = {apr}
}