Big data analysis; Machine learning; Tourist' mobility; Tourist' trends; Transport planning; Transportation; General Medicine
Abstract :
[en] This paper aims at analysing tourist satisfaction towards transport systems of the touristic destination using online reviews from TripAdvisor, the most well-known online review platform used in the tourism sector for researchers and customers. First, a web scraping method was used to retrieve online reviews available on TripAdvisor related to transport systems, then the Latent Dirichlet Allocation method was implemented to extract the topics of the online reviews, and finally an analysis was performed to find similarities and differences among positive and negative reviews for each topic in order to identify tourist trends towards transport systems. To test the methodology, the case of Mount Etna has been considered, one of the main tourist destinations in Sicily (Italy), located on the east coast of the island. According to the results of our case study, the reviews can be clustered in positive and negative predicted feelings, and, for each of them 2 topics (Topic 0 and Topic 1) are linked. Topics are related to specific tourist experience characteristics and the differences between positive and negative reviews can be ascribed to a different relationship between transport and tourism concepts. Main results show a positive attitude of tourists towards the of transport as an integrated experience of the visit of the touristic location. The proposed approach is able to provide useful information to decision-makers by identifying the possible criticalities and intervention priorities considering user judgment. Besides, this methodology can be easily applied to other tourist venues and can be used by decision-makers to provide better services with the aim of improving the engagement of tourists with the city and increasing profits.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Pineda-Jaramillo, Juan; Department of Engineering, University of Luxembourg, Esch-sur-Alzette, Luxembourg
FAZIO, Martina ; University of Luxembourg ; University of Catania, Department of Physics and Astronomy, Catania, Italy
Le Pira, Michela; University of Catania, Department of Civil Engineering and Architecture, Catania, Italy
Giuffrida, Nadia; Polytechnic University od Bari, Bari, Italy
Inturri, Giuseppe; University of Catania, Department of Electrical, Electronic and Computer Engineering, Catania, Italy
VITI, Francesco ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Ignaccolo, Matteo; University of Catania, Department of Civil Engineering and Architecture, Catania, Italy
External co-authors :
yes
Language :
English
Title :
A sentiment analysis approach to investigate tourist satisfaction towards transport systems: the case of Mount Etna
Publication date :
2023
Event name :
AIIT 3rd International Conference on Transport Infrastructure and Systems,TIS ROMA 2022
Event place :
Rome, Ita
Event date :
15-09-2022 => 16-09-2022
Audience :
International
Main work title :
AIIT 3rd International Conference on Transport Infrastructure and Systems,TIS ROMA 2022 - Conference Proceedings
The work was partially supported by the project “WEAKI -TRANSIT: WEAK-demand areas Innovative TRANsport Shared services for Italian Towns” (unique project code: E44I17000050001) under the programme P“ RIN 2017”, by the project of M. Le Pira A“ IM Linea di Attività 3 – Mobilità sostenibile: Trasporti” (unique project CODE CUP E66C180013890007) under the programme P“ ON Ricerca e Innovazione 2014 -2020– Fondo Sociale Europeo”, Azione 1.2 A‘ ttrazione e mobilità internazion ale dei ricercatori’, and by the project A“ DDRESS” under the University of Catania programme P“ IACERI Linea 2”.
Adhinugroho, Y., Putra, A. P., Luqman, M., Ermawan, G. Y., Mariyah, S., & Pramana, S. (2020). Development of online travel Web scraping for tourism statistics in Indonesia.
Albalate, D., & Bel, G. (2010). Tourism and urban public transport: Holding demand pressure under supply constraints. Tourism Management, 31(3), 425-433.
Bordagaray, M.; dell'Olio, L.; Ibeas, A.; Cecín, P. 2014. Modelling user perception of bus transit quality considering user and service heterogeneity, Transportmetrica A: Transport Science, 10(8): 705-721.
Budeanu, A. (2007). Sustainable tourist behaviour-a discussion of opportunities for change. International Journal of Consumer Studies, 31(5), 499-508.
Fazio, M., Le Pira, M., Inturri, G., & Ignaccolo, M. (2020). Bus Rapid Transit vs. Metro. Monitoring on-board comfort of competing transit services via sensors. In 2020 forum on integrated and sustainable transportation systems (FISTS) (pp. 292-297). IEEE.
Giuffrida, N., Fajardo-Calderin, J., Masegosa, A. D., Werner, F., Steudter, M., & Pilla, F. (2022). Optimization and Machine Learning Applied to Last-Mile Logistics: A Review. Sustainability, 14(9), 5329.
Hall, C. M., & Ram, Y. (2019). Measuring the relationship between tourism and walkability? Walk Score and English tourist attractions. Journal of Sustainable Tourism, 27(2), 223-240.
Inturri, G., Giuffrida, N., Le Pira, M., Fazio, M., & Ignaccolo, M. (2021). Linking public transport user satisfaction with service accessibility for sustainable mobility planning. ISPRS International Journal of Geo-Information, 10(4), 235.
Kanakaraj, M., & Guddeti, R. M. R. (2015, February). Performance analysis of Ensemble methods on Twitter sentiment analysis using NLP techniques. In Proceedings of the 2015 IEEE 9th international conference on semantic computing (IEEE ICSC 2015) (pp. 169-170). IEEE.
Le Pira, M., Marcucci, E., & Gatta, V. (2021). Roman holiday: Tourist heterogeneous preferences for walking path elements. Research in Transportation Economics, 90, 101106.
Le Pira, M.; Inturri, G.; Ignaccolo, M. (2018). Public transport and proactive real‐time information: A survey on users' preferences and attitudes toward multimodal traveler information services. In Proceedings of the International Conference on Traffic and Transport Engineering (ICTTE 2018), Belgrade, Serbia, 27-28 September 2018; ISBN 978‐86‐916153‐4‐5.
Page, S. (2004). Transport and tourism: Global perspectives. 2nd edition. Pearson Education.
Pineda-Jaramillo, J. D. (2019). A review of Machine Learning (ML) algorithms used for modeling travel mode choice. Dyna, 86(211), 32-41.
Pineda-Jaramillo, J., & Pineda-Jaramillo, D. (2021). Analysing travel satisfaction of tourists towards a metro system from unstructured data. Research in Transportation Business & Management, 100746.
Rossetti, S., & Tiboni, M. (2020). In Field Assessment of Safety, Security, Comfort and Accessibility of Bus Stops: A Planning Perspective. Eur. Transp./Trasporti Europei, 80, paper 8, https://doi.org/10.48295/ET.2020.80.8
Rossetti, S., Tiboni, M., Vetturi, D., Zazzi, M., & Caselli, B. (2020). Measuring pedestrian accessibility to public transport in urban areas: A GIS-based discretisation approach. Eur. Transp. Trasp. Eur, 76, paper 2.
Simeon, M. I., Buonincontri, P., Cinquegrani, F., & Martone, A. (2017). Exploring tourists' cultural experiences in Naples through online reviews. Journal of Hospitality and Tourism Technology.
Solangi, Y. A., Solangi, Z. A., Aarain, S., Abro, A., Mallah, G. A., & Shah, A. (2018, November). Review on natural language processing (NLP) and its toolkits for opinion mining and sentiment analysis. In 2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences (ICETAS) (pp. 1-4). IEEE.
Taecharungroj, V., & Mathayomchan, B. (2019). Analysing TripAdvisor reviews of tourist attractions in Phuket, Thailand. Tourism Management, 75, 550-568.
Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65. https://doi.org/10.1016/j.tourman.2016.10.001
