Flickr Photos Analysis for Beach Tourism Management in Bantul Regency, Indonesia: Popularity and Tourist Attractions

Arief Wicaksono, Nur Mohammad Farda, Nurul Khakhim, Totok Wahyu Wibowo

DOI: https://doi.org/10.23917/forgeo.v35i1.13007

Abstract

Photos shared by social media users act as an approach in identifying tourist activity. Popular tourist attractions are judged based on the large number of photos or high photo density. In Bantul Regency, Indonesia, beaches have diverse attractions which tourists can enjoy and immortalize through photos. Analyzing the contents of photos on Flickr provides information on the type(s) of beaches or coastal attractions preferred by tourists. This study examined the availability of geotagged Flickr photos to assist in making relevant beach tourism management policies. It employed pattern analysis with the average nearest neighbor, density analysis with kernel density estimation, image content analysis with tourist attraction as the variable, and overlay analysis to formulate recommendations for beach tourism management based on the popularity level of the attractions. The results indicate that each of the local beaches offers different attractions with varying popularity levels and that natural beauty is the main feature attracting tourists to visit all beaches, except Baros. Based on the pattern analysis, the Flickr photos are clustered on several beaches of high popularity, such as Parangtritis, Baros, Depok, and Cemara Sewu. By using geotagged Flickr photo data and refers to the concept of tourism supply and demand, recommendations for developing the attractive features on these beaches have been compiled according to their respective themes and popularity levels to target specific tourist market segments and design integrated tour or travel packages.

Keywords

Popularity; Beach Attraction; Image Content Analysis; Flickr; Bantul

Full Text:

HTML PDF

References

Alonso-Almeida, M. del M., Borrajo-Millán, F., & Yi, L. (2019). Are social media data pushing overtourism? The case of Barcelona and Chinese Tourists. Sustainability, 11(12), 1–17. https://doi.org/10.3390/SU11123356

Angus, E., Stuart, D., & Thelwall, M. (2010). Flickr’s potential as an academic image resource: An exploratory study. Journal of Librarianship and Information Science, 42(4), 268–278. https://doi.org/10.1177/0961000610384656

Bae, S. H., & Yun, H. J. (2017). Spatiotemporal Distribution of Visitors’ Geotagged Landscape Photos in Rural Areas. Tourism Planning and Development, 14(2), 167–180. https://doi.org/10.1080/21568316.2016.1204356

Briassoulis, H. (2002). Sustainable tourism and the question of the commons. Annals of Tourism Research, 29(4), 1065–1085. https://doi.org/10.1016/S0160-7383(02)00021-X

BPS Kabupaten Bantul. (2016). Kabupaten Bantul Dalam Angka 2016. Bantul: BPS Kabupaten Bantul.

BPS Kabupaten Bantul. (2020). Kabupaten Bantul Dalam Angka 2020. Bantul: BPS Kabupaten Bantul.

Camprubí, R., Guia, J., & Comas, J. (2013). The new role of tourists in destination image formation. Current Issues in Tourism, 16(2), 203–209. https://doi.org/10.1080/13683500.2012.733358

Carrion, D., Migliaccio, F., & Pagliari, D. (2017). Exploring geolocation issues in social media analytics : A case study with Tweet messages. Sixth International Virtual Scientific Conference on Informatics and Management Sciences, 100–103.

Castro, C. B., Martín Armario, E., & Martín Ruiz, D. (2007). The influence of market heterogeneity on the relationship between a destination’s image and tourists’ future behaviour. Tourism Management, 28(1), 175–187. https://doi.org/10.1016/j.tourman.2005.11.013

Chung, J. Y., & Buhalis, D. (2008). Web 2.0: A Study of Online Travel Community. In P. O’Connor, W. Hopken, & U. Gretzel (Eds.), Information and Communication Technologies in Tourism 2008 (pp. 70–81). https://doi.org/10.1017/CBO9781107415324.004

Dinas Pariwisata DIY. (2018). Arahan Pengembangan Kawasan Pariwisata D.I. Yogyakarta. Yogyakarta.

Dinas Pariwisata DIY. (2019). Statistik Kepariwisataan 2018. Yogyakarta: Dinas Pariwisata DIY.

Ding, X., & Fan, H. (2019). Exploring the distribution patterns of Flickr photos. ISPRS International Journal of Geo-Information, 8(418), 1–15.

Donaire, J. A., Camprubí, R., & Galí, N. (2014). Tourist clusters from Flickr travel photography. Tourism Management Perspectives, 11, 26–33. https://doi.org/10.1016/j.tmp.2014.02.003

Esri. (2016). ArcGIS 10.5 Help. Redlands: Environmental System Research Institute.

Floris, R., & Campagna, M. (2014). Social media data in tourism planning: analysing tourist’s satisfaction in space and time. Proceedings Real Corp, 8(May), 997–1003.

Garrod, B. (2009). Understanding the relationship between tourism destination imagery and tourist photography. Journal of Travel Research, 47(3), 346–358. https://doi.org/10.1177/0047287508322785

Ghermandi, A., & Sinclair, M. (2019). Passive crowdsourcing of social media in environmental research : A systematic map. Global Environmental Change, 55(September 2018), 36–47. https://doi.org/10.1016/j.gloenvcha.2019.02.003

Hall, C M, & Valentin, A. (2005). Content Analysis. In B. W. Ritchie, P. Burns, & C. Palmer (Eds.), Tourism Research Methods: Integrating Theory with Practice (pp. 191–209). Oxfordshire: CABI Publishing.

Hall, C Michael, & Page, S. J. (2006). The Geography of Tourism and Recreation: Environment, Place and Space. In (Geography of tourism). (3rd ed.). New York: Routledge.

Hardjowigeno, S., & Widiatmaka. (2017). Evaluasi Kesesuaian Lahan dan Perencanaan Tataguna Lahan. Yogyakarta: Gadjah Mada University Press.

Kisilevich, S., Krstajic, M., Keim, D., Andrienko, N., & Andrienko, G. (2010). Event-based analysis of people’s activities and behavior using Flickr and Panoramio geotagged photo collections. 14th International Conference Information Visualisation, 289–296. https://doi.org/10.1109/IV.2010.94

Kolbe, R. H., & Burnett, M. S. (1991). Content-Analysis Research: An Examination of Applications with Directives for Improving Research Reliability and Objectivity. Journal of Consumer Research, 18(2), 243–250.

Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research : A literature review. Tourism Management, 68, 301–323. https://doi.org/10.1016/j.tourman.2018.03.009

Lo, I. S., McKercher, B., Lo, A., Cheung, C., & Law, R. (2011). Tourism and online photography. Tourism Management, 32(4), 725–731. https://doi.org/10.1016/j.tourman.2010.06.001

MacKay, K. J., & Couldwell, C. M. (2004). Using visitor-employed photography to investigate destination image. Journal of Travel Research, 42(4), 390–396. https://doi.org/10.1177/0047287504263035

Majid, A., Chen, L., Mirza, H. T., Hussain, I., & Chen, G. (2015). A system for mining interesting tourist locations and travel sequences from public geo-tagged photos. Data & Knowledge Engineering, 95, 66–86. https://doi.org/10.1016/j.datak.2014.11.001

Manepalli, U. R. R., Bham, G. H., & Kandada, S. (2011). Evaluation of hotspot identification using kernel density estimation (K) and getis-ord (Gi*) on I-630. 3rd International Conference on Road Safety and Simulation, 1750, 1–17. Indianapolis Indiana.

Mancosu, M., & Vegetti, F. (2020). What you can scrape and what is right to scrape: A proposal for a tool to collect public Facebook data. Social Media + Society, July-September 2020: 1–11. https://doi.org/10.1177/2056305120940703

Parra-Lopez, E., Gutierrez-Tano, D., Diaz-Armas, R. J., & Bulchand-Gidumal, J. (2012). Travellers 2.0: Motivation, Opportunity and Ability to Use Social Media. In M. Sigala, E. Christou, & U. Gretzel (Eds.), Social Media in Travel, Tourism and Hospitality : Theory, Practice and Cases (p. 339). Farnham: Ashgate Publishing.

Peng, X., & Huang, Z. (2017). A novel popular tourist attraction discovering approach based on geo-tagged social media big data. ISPRS International Journal of Geo-Information, 6(216), 1–16. https://doi.org/10.3390/ijgi6070216

Peraturan Daerah Kabupaten Bantul Nomor 18 Tahun 2015 tentang Rencana Induk Pembangunan Kepariwisataan Daerah Tahun 2015-2025.

Rofi, A., Wibowo, T. W., Sudaryatno, & Farda, N. M. (2019). Tourists geovisualization analysis utilizing Instagram data in Central Java Province and Special Region of Yogyakarta. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII–4(W16), 535–542. Kuala Lumpur.

Safitri, H., & Pramono, AH. (2009). Refleksi atas gerakan pemetaan partisipatif dan tantangan dimasa depan (Reflection on the Participatory Mapping Act and Future Challenges). In AH. Pramono, F. Samperante, H. Safitri, R. Achmaliadi (Eds), Menuju Demokratisasi Pemetaan: Refleksi Gerakan Pemetaan Partisipatif di Indonesia (Toward Mapping Democratisation: Reflections on the Participatory Mapping Act in Indonesia. Bogor: Jaringan Kerja Pemetaan Partisipatif (JKPP).

Stock, K. (2018). Mining location from social media: A systematic review. Computers, Environment and Urban Systems, 71, 209-240. https://doi.org/10.1016/j.compenvurbsys.2018.05.007

Stylianou-Lambert, T. (2012). Tourists with cameras: Reproducing or Producing? Annals of Tourism Research, 39(4), 1817–1838. https://doi.org/10.1016/j.annals.2012.05.004

Tenkanen, H., Di Minin, E., Heikinheimo, V., Hausmann, A., Herbst, M., Kajala, L., & Toivonen, T. (2017). Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas. Scientific Reports, 7(1), 1–11. https://doi.org/10.1038/s41598-017-18007-4

Thelwall, M. (2018). Social media analytics for YouTube comments: potential and limitations. International Journal of Social Research Methodology, 21(3), 303–316. https://doi.org/10.1080/13645579.2017.1381821

Urry, J., & Larsen, J. (2011). The tourist gaze 3.0. In Antropólogos Iberoamericanos en Red (3rd ed., Vol. 09). https://doi.org/10.11156/240

Vu, H. Q., Li, G., Law, R., & Ye, B. H. (2015). Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos. Tourism Management, 46, 222–232. https://doi.org/10.1016/j.tourman.2014.07.003

Wibowo, T W. (2017). Spatial point data analysis of geolocated Tweets in the first day of Eid Al-Fitr 2017 in Java Island. Fifth Geoinformation Science Symposium 2017, 1–10. Yogyakarta: IOP Publishing.

Wibowo, T W, Rofi, A., & Sulistyaningrum, N. A. (2019). Density analysis of Flickr data as a proxy to reveal the intensity of tourism activity in Borobudur. Sixth Geoinformation Science Symposium 2019, (11311), 1–8. https://doi.org/10.1117/12.2549040

Yan, Y., Eckle, M., Kuo, C., Herfort, B., Fan, H., & Zipf, A. (2017). Monitoring and assessing post-disaster tourism recovery using geotagged social media data. ISPRS International Journal of Geo-Information, 6(144), 1–17. https://doi.org/10.3390/ijgi6050144

Yudono, A. (2017). Towards democracy in spatial planning through spatial information built by communities: The investigation of spatial information built by citizens from participatory mapping to volunteered geographic information in Indonesia. 3rd International Conference of Planning in the Era of Uncertainty, 012002, 1-16. https://doi.org/10.1088/1755-1315/70/1/012002

Zielstra, D., & Hochmair, H. H. (2013). Positional accuracy analysis of Flickr and Panoramio images for selected world regions. Journal of Spatial Science, 58(2), 251–273. https://doi.org/10.1080/14498596.2013.801331

Article Metrics

Abstract view(s): 142 time(s)
HTML: 77 time(s) PDF: 13 time(s)

Refbacks

  • There are currently no refbacks.