From reviews to reflections: Understanding tourist sentiments and satisfaction in African destinations through user-generated content

Esi Akyere Mensah; Doreen Nyarko Anyamesem Odame; Isaac Ankrah; Theresa Obuobisa-Darko; Robert Ebo Hinson

doi:10.1016/j.annale.2025.100174

From reviews to reflections: Understanding tourist sentiments and satisfaction in African destinations through user-generated content

Esi Akyere Mensah
, Doreen Nyarko Anyamesem Odame
, Isaac Ankrah
, Theresa Obuobisa-Darko
, Robert Ebo Hinson

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

User-generated content continues to shape global tourism trends, yet Africa's growing tourism sector has received limited attention. This study addresses this gap by investigating tourist sentiments and satisfaction across ten African destinations from 2018 to 2023. Employing a mixed method approach with advanced machine learning techniques, the results reveal generally positive sentiment, with both well-trodden and less-travelled destinations offering distinct experience and satisfaction. Among others, this study contributes to tourism research by expanding the focus to African destinations to capture evolving tourist sentiments.

Original language	English
Article number	100174
Journal	Annals of Tourism Research Empirical Insights
Volume	6
Issue number	1
DOIs	https://doi.org/10.1016/j.annale.2025.100174
Publication status	Published - May 2025
Externally published	Yes

Keywords

Africa
Destination popularity
Sentiment analysis
Tourist satisfaction
Tripadvisor review

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10.1016/j.annale.2025.100174

Cite this

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title = "From reviews to reflections: Understanding tourist sentiments and satisfaction in African destinations through user-generated content",

abstract = "User-generated content continues to shape global tourism trends, yet Africa's growing tourism sector has received limited attention. This study addresses this gap by investigating tourist sentiments and satisfaction across ten African destinations from 2018 to 2023. Employing a mixed method approach with advanced machine learning techniques, the results reveal generally positive sentiment, with both well-trodden and less-travelled destinations offering distinct experience and satisfaction. Among others, this study contributes to tourism research by expanding the focus to African destinations to capture evolving tourist sentiments.",

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AU - Mensah, Esi Akyere

AU - Odame, Doreen Nyarko Anyamesem

AU - Ankrah, Isaac

AU - Obuobisa-Darko, Theresa

AU - Hinson, Robert Ebo

PY - 2025/5

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AB - User-generated content continues to shape global tourism trends, yet Africa's growing tourism sector has received limited attention. This study addresses this gap by investigating tourist sentiments and satisfaction across ten African destinations from 2018 to 2023. Employing a mixed method approach with advanced machine learning techniques, the results reveal generally positive sentiment, with both well-trodden and less-travelled destinations offering distinct experience and satisfaction. Among others, this study contributes to tourism research by expanding the focus to African destinations to capture evolving tourist sentiments.

KW - Africa

KW - Destination popularity

KW - Sentiment analysis

KW - Tourist satisfaction

KW - Tripadvisor review

UR - https://www.scopus.com/pages/publications/105001815203

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JF - Annals of Tourism Research Empirical Insights

IS - 1

M1 - 100174

ER -

From reviews to reflections: Understanding tourist sentiments and satisfaction in African destinations through user-generated content

Abstract

Keywords

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