Sentiment Analysis for Tourism Insights: A Machine Learning Approach
This paper explores international tourism regarding Morocco’s leading touristic city Marrakech, and, more precisely, its two prominent public spaces, Jemaa el-Fna and the Medina. Following a web-scraping process of English reviews on TripAdvisor, a machine learning technique is proposed to gather in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/2571-905X/7/4/90 |
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| author | Kenza Charfaoui Stéphane Mussard |
| author_facet | Kenza Charfaoui Stéphane Mussard |
| author_sort | Kenza Charfaoui |
| collection | DOAJ |
| description | This paper explores international tourism regarding Morocco’s leading touristic city Marrakech, and, more precisely, its two prominent public spaces, Jemaa el-Fna and the Medina. Following a web-scraping process of English reviews on TripAdvisor, a machine learning technique is proposed to gather insights into prominent topics in the data, and their corresponding sentiment with a specific voting model. This process allows decision makers to direct their focus onto certain issues, such as safety concerns, animal conditions, health, or pricing issues. In addition, the voting method outperforms Vader, a widely used sentiment prediction tool. Furthermore, an LLM (Large Language Model) is proposed, the SieBERT-Marrakech. It is a SieBERT model fine-tuned on our data. The model outlines good performance metrics, showing even better results than GPT-4o, and it may be an interesting choice for tourism sentiment predictions in the context of Marrakech. |
| format | Article |
| id | doaj-art-63c1845a1fde4b4fa3a5a65795584db7 |
| institution | DOAJ |
| issn | 2571-905X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Stats |
| spelling | doaj-art-63c1845a1fde4b4fa3a5a65795584db72025-08-20T02:50:43ZengMDPI AGStats2571-905X2024-12-01741527153910.3390/stats7040090Sentiment Analysis for Tourism Insights: A Machine Learning ApproachKenza Charfaoui0Stéphane Mussard1Faculty of Governance, Economics and Social Sciences, Mohammed VI Polytechnic University, Rabat 11100, MoroccoFaculty of Governance, Economics and Social Sciences, Mohammed VI Polytechnic University, Rabat 11100, MoroccoThis paper explores international tourism regarding Morocco’s leading touristic city Marrakech, and, more precisely, its two prominent public spaces, Jemaa el-Fna and the Medina. Following a web-scraping process of English reviews on TripAdvisor, a machine learning technique is proposed to gather insights into prominent topics in the data, and their corresponding sentiment with a specific voting model. This process allows decision makers to direct their focus onto certain issues, such as safety concerns, animal conditions, health, or pricing issues. In addition, the voting method outperforms Vader, a widely used sentiment prediction tool. Furthermore, an LLM (Large Language Model) is proposed, the SieBERT-Marrakech. It is a SieBERT model fine-tuned on our data. The model outlines good performance metrics, showing even better results than GPT-4o, and it may be an interesting choice for tourism sentiment predictions in the context of Marrakech.https://www.mdpi.com/2571-905X/7/4/90Marrakechlarge language modelsmachine learningsentiment analysisvoting model |
| spellingShingle | Kenza Charfaoui Stéphane Mussard Sentiment Analysis for Tourism Insights: A Machine Learning Approach Stats Marrakech large language models machine learning sentiment analysis voting model |
| title | Sentiment Analysis for Tourism Insights: A Machine Learning Approach |
| title_full | Sentiment Analysis for Tourism Insights: A Machine Learning Approach |
| title_fullStr | Sentiment Analysis for Tourism Insights: A Machine Learning Approach |
| title_full_unstemmed | Sentiment Analysis for Tourism Insights: A Machine Learning Approach |
| title_short | Sentiment Analysis for Tourism Insights: A Machine Learning Approach |
| title_sort | sentiment analysis for tourism insights a machine learning approach |
| topic | Marrakech large language models machine learning sentiment analysis voting model |
| url | https://www.mdpi.com/2571-905X/7/4/90 |
| work_keys_str_mv | AT kenzacharfaoui sentimentanalysisfortourisminsightsamachinelearningapproach AT stephanemussard sentimentanalysisfortourisminsightsamachinelearningapproach |