Tourism-Related Placeness Feature Extraction from Social Media Data Using Machine Learning Models.

Authors

DOI:

https://doi.org/10.9781/ijimai.2022.12.003

Keywords:

Inference, Machine Learning, Social, Tourism, Word2Vec
Supporting Agencies
Pilar Muñoz has received support from the Spanish ministry of Science and Research (grant PID2020-116040RB-I00). The work of Ana Larrañaga has been supported by the 2020 predoctoral grant of the University of Vigo.

Abstract

The study of placeness has been focus for researchers trying to understand the impact of locations on their surroundings and tourism, the loss of it by globalization and modernization and its effect on tourism, or the characterization of the activities that take place in them. Identifying places that have a high level of placeness can become very valuable when studying social trends and mobility in relation to the space in which the study takes place. Moreover, places can be enriched with dimensions such as the demographics of the individuals visiting such places and the activities the carry in them thanks to social media and modern machine learning and data mining methods. Such information can prove to be useful in fields such as urban planning or tourism as a base for analysis and decision-making or the discovery of new social hotspots or sites rich in cultural heritage. This manuscript will focus on the methodology to obtain such information, for which data from Instagram is used to feed a set of classification models that will mine demographics from the users based on graphic and textual data from their profiles, gain insight on what they were doing in each of their posts and try to classify that information into any of the categories discovered in this article. The goal of this methodology is to obtain, from social media data, characteristics of visitors to locations as a discovery tool for the tourism industry.

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References

J. G. Brida, S. London, M. Rojas, “El turismo como fuente de crecimiento económico: impacto de las preferencias intertemporales de los agentes,” Investigación económica, vol. 73, pp. 59–77, 09 2014.

I. Cortés-Jiménez, “Which type of tourism matters to the regional economic growth? the cases of spain and italy,” International Journal of Tourism Research, vol. 10, no. 2, pp. 127–139, 2008, doi: https://doi.org/10.1002/jtr.646

W. T. Organization, “International tourism highlights,” 2019.

U. N. W. T. Organization, “Unwto global tourism dashboard. country profile-outbound,” 2020.

W. Travel, T. Council., “Research–economic impact reports,” 2020.

A. Santana Talavera, “Patrimonios culturales y turistas: Unos leen lo que otros miran,” PASOS: Revista de Turismo y Patrimonio Cultural, vol. 1, 01 2003, doi: 10.25145/j.pasos.2003.01.001.

F. Jiménez, C. y Seño, “Patrimonio cultural inmaterial de la humanidad y turismo.,” International Journal of Scientific Management and Tourism, vol. 4, no. 2, pp. 349–366, 2018.

G. Yudice, “El recurso de la cultura.,” Gedisa. Barcelona, 2001.

UNESCO, “Convención para la salvaguarda del patrimonio cultural inmaterial de la unesco,” 2003.

J. Arévalo, “La tradición, el patrimonio y la identidad,” pp. 925–955, 2004.

M. Timón Tiemblo, M.P. y Domingo Fominaya, “Resumen del plan nacional de salvaguarda del patrimonio cultural inmaterial,” Anales del Museo Nacional de Antropología, vol. 14, pp. 29–44.

J. Nared, D. Bole, Participatory Research on Heritage- and Culture-Based Development: A Perspective from South-East Europe, pp. 107–119. Cham: Springer International Publishing, 2020.

B. A. Adie, C. M. Hall, “Who visits world heritage? a comparative analysis of three cultural sites,” Journal of Heritage Tourism, vol. 12, no. 1, pp. 67–80, 2017, doi: 10.1080/1743873X.2016.1151429.

C. Milano, M. Novelli, J. M. Cheer, “Overtourism and tourismphobia: A journey through four decades of tourism development, planning and local concerns,” Tourism Planning & Development, vol. 16, no. 4, pp. 353–357, 2019, doi: 10.1080/21568316.2019.1599604.

P. L. Winter, S. Selin, L. Cerveny, K. Bricker, “Outdoor recreation, naturebased tourism, and sustainability,” Sustainability, vol. 12, no. 1, 2020, doi: 10.3390/su12010081.

Y. Deng, C. Li, “Research progress, theories review and trend forecast on placeness of tourism destination,” in Proceedings of the 3rd International Seminar on Education Innovation and Economic Management (SEIEM 2018), 2019/01, pp. 431–434, Atlantis Press.

R. E, “Classics in human geography revisited, place and placelessness.,” Progress in Human Geography, vol. 24, no. 4, p. 613, 2000.

S. A. Bowen, D, R. E, “Tourist satisfaction and beyond: tourist migrants in mallorca.,” International journal of tourism research, vol. 10, no. 2, pp. 141–153, 2008.

A. Bowen, “War-affected children in three african short stories: Finding sanctuary within the space of placelessness.,” Commonwealth Essays and Studies, vol. 42, no. 2, 2020.

T. Wenyue, “The influence and significance of tourism development on placeness.,” Tourism Tribune, vol. 28, no. 4, pp. 9–11, 2013.

L. Leilei., “The spatial cognition process and law of tourist destination image.,” Scientia Geographica Sinica, vol. 6, pp. 563–568, 2000.

W. B, “Regional tourism plannig principles.,” China Travel and Tourism Press, 2001.

K. X. Zhou S Y, Yang H Y, “The structuralistic and humanistic mechanism of placeness: A case study of 798 and m50 art districts.,” Geographical Research, vol. 30, no. 9, pp. 1566–1576, 2011.

G. Kalra, M. Yu, D. Lee, M. Cha, D. Kim, “Ballparking the urban placeness: A case study of analyzing starbucks posts on instagram,” in International Conference on Social Informatics, 2018, pp. 291–307, Springer.

M. K.. M. F. Pfeffer, J., “War-affected children in three african short stories: Finding sanctuary within the space of placelessness,” Commonwealth Essays and Studies, vol. 7, no. 1, p. 50, 2018.

B. E. Rossi, L., A. Torsello, “Venice through the lens of instagram: A visual narrative of tourism in venice.,” Companion Proceedings of the The Web Conference 2018, pp. 1190–1197, 2018.

K. Jang, Y. Kim, “Crowd-sourced cognitive mapping: A new way of displaying people’s cognitive perception of urban space.,” PLoS ONE, vol. 14, no. 6, p. e0218590, 2019.

U. S. Hasan S, Zhan X, “Understanding urban human activity and mobility patterns using large-scale location-based data from online social media.,” PLoS ONE, vol. 14, no. 6, p. e0218590, 2003.

Z. Wang, S. Hale, D. I. Adelani, P. Grabowicz, T. Hartman, F. Flöck, D. Jurgens, “Demographic inference and representative population estimates from multilingual social media data,” in The world wide web conference, 2019, pp. 2056–2067.

Beijing Kuangshi Technology Co., Ltd., “Face++ platform.” https://www.faceplusplus.com/face-detection/, 2021. Accessed: 2021-07-22.

G. d. Q. J. B. S. Alvarez, P., “Riada: A machine-learning based infrastructure for recognising the emotions of spotify songs.” International Journal of Interactive Multimedia and Artificial Intelligence. IN PRESS, 2022.

R. Flesch, “A new readability yardstick.,” Journal of applied psychology, vol. 32, no. 3, p. 221, 1948.

G. Huang, Z. Liu, L. Van Der Maaten, K. Q. Weinberger, “Densely connected convolutional networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 4700–4708.

W. C. W. T. I. W. K. P. C. Y. H. H. K. S. Chen, S. H., “Modified yolov4-densenet algorithm for detection of ventricular septal defects in ultrasound images.,” International Journal of Interactive Multimedia and Artificial Intelligence, vol. 6, no. 7, pp. 101–108, 2022.

S. Hochreiter, J. Schmidhuber, “Long short-term memory,” Neural computation, vol. 9, no. 8, pp. 1735–1780, 1997.

I. Goodfellow, Y. Bengio, A. Courville, Deep Learning, ch. 6, pp. 180–184. MIT Press, 2016. http://www.deeplearningbook.org

I. T. Jolliffe, J. Cadima, “Principal component analysis: a review and recent developments,” vol. 374, p. 20150202, Apr. 2016, doi: 10.1098/rsta.2015.0202.

K. Pearson, “Liii. on lines and planes of closest fit to systems of points in space,” The London, Edinburgh, and Dublin philosophical magazine and journal of science, vol. 2, no. 11, pp. 559–572, 1901.

Instagram, “Vigo, spain on instagram • photos and videos.” https://www.instagram.com/explore/locations/23436873/vigo-spain/. Accessed: 2021- 07-25.

S. Bansal, C. Aggarwal, “textstat | pypi.” https://pypi.org/project/textstat/, 2021. Accessed: 2021-07-29.

Microsoft Corporation, “Computer vision | microsoft azure.” https://azure.microsoft.com/es-es/services/cognitive-services/computervision/#overview, 2021. Accessed: 2021-07-26.

C. Szegedy, A. Toshev, D. Erhan, “Deep neural networks for object detection,” 2013.

T. Mikolov, K. Chen, G. Corrado, J. Dean, “Efficient estimation of word representations in vector space,” 2013.

T. Mikolov, I. Sutskever, K. Chen, G. Corrado, J. Dean, “Distributed representations of words and phrases and their compositionality,” 2013.

L. McInnes, J. Healy, J. Melville, “Umap: Uniform manifold approximation and projection for dimension reduction,” 2020.

L. Van der Maaten, G. Hinton, “Visualizing data using t-sne.,” Journal of machine learning research, vol. 9, no. 11, 2008.

P. J. Rousseeuw, “Silhouettes: a graphical aid to the interpretation and validation of cluster analysis,” Journal of computational and applied mathematics, vol. 20, pp. 53–65, 1987.

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2023-12-01
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How to Cite

Muñoz Dueñas, P., Doñaque González, E., Larrañaga Janeiro, A., Martínez Torres, J., and Mejías, A. M. (2023). Tourism-Related Placeness Feature Extraction from Social Media Data Using Machine Learning Models. International Journal of Interactive Multimedia and Artificial Intelligence, 8(4), 176–181. https://doi.org/10.9781/ijimai.2022.12.003