File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.landurbplan.2020.103977
- Scopus: eid_2-s2.0-85096182610
- WOS: WOS:000597161200001
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland
Title | The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland |
---|---|
Authors | |
Keywords | Kevin Lynch City image Social media analytics Tri-City Poland |
Issue Date | 2021 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/landurbplan |
Citation | Landscape and Urban Planning, 2021, v. 206, p. article no. 103977 How to Cite? |
Abstract | “The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does it hold for urban planners? This paper describes a study on the perception of city images using a combination of “big data” and “small data” methods in the Tri-City Region in Poland. The aims were to 1) test the hypothesis whether social media analytics can elicit Lynchian elements of city image in consistency with conventional methods, and 2) develop and evaluate social media-based indicators of Imageability for planning practice. Geo-tagged images and texts were collected from Instagram and Twitter, two popular social media platforms in Poland. Text-Mining, Image Processing, Clustering Analysis, Kernel Density Estimation, and Sentiment Analysis were used. Results were compared with benchmarks constructed from official GIS database, questionnaire responses and sketch maps. “District”, “landmark”, and “path” identified on social media were in good agreements with benchmarks, less so for “edge” and “node”. Two social media-based indicators have influenced the perception of a place: Instagramability, the frequency of a place captured on Instagram, was linked to its perception as an architectural landmark and tourist attraction, while Twitterability, the frequency of a place mentioned on Twitter by name, was linked to its perceived niceness and relevance to everyday life of communities. Methods developed in this study have theoretical and practical implications for urban planners. |
Persistent Identifier | http://hdl.handle.net/10722/293515 |
ISSN | 2023 Impact Factor: 7.9 2023 SCImago Journal Rankings: 2.358 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Huang, J | - |
dc.contributor.author | Obracht-Prondzynska, H | - |
dc.contributor.author | Kamrowska-Zaluska, D | - |
dc.contributor.author | Sun, Y | - |
dc.contributor.author | Li, L | - |
dc.date.accessioned | 2020-11-23T08:17:53Z | - |
dc.date.available | 2020-11-23T08:17:53Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Landscape and Urban Planning, 2021, v. 206, p. article no. 103977 | - |
dc.identifier.issn | 0169-2046 | - |
dc.identifier.uri | http://hdl.handle.net/10722/293515 | - |
dc.description.abstract | “The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does it hold for urban planners? This paper describes a study on the perception of city images using a combination of “big data” and “small data” methods in the Tri-City Region in Poland. The aims were to 1) test the hypothesis whether social media analytics can elicit Lynchian elements of city image in consistency with conventional methods, and 2) develop and evaluate social media-based indicators of Imageability for planning practice. Geo-tagged images and texts were collected from Instagram and Twitter, two popular social media platforms in Poland. Text-Mining, Image Processing, Clustering Analysis, Kernel Density Estimation, and Sentiment Analysis were used. Results were compared with benchmarks constructed from official GIS database, questionnaire responses and sketch maps. “District”, “landmark”, and “path” identified on social media were in good agreements with benchmarks, less so for “edge” and “node”. Two social media-based indicators have influenced the perception of a place: Instagramability, the frequency of a place captured on Instagram, was linked to its perception as an architectural landmark and tourist attraction, while Twitterability, the frequency of a place mentioned on Twitter by name, was linked to its perceived niceness and relevance to everyday life of communities. Methods developed in this study have theoretical and practical implications for urban planners. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/landurbplan | - |
dc.relation.ispartof | Landscape and Urban Planning | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Kevin Lynch | - |
dc.subject | City image | - |
dc.subject | Social media analytics | - |
dc.subject | Tri-City Poland | - |
dc.title | The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland | - |
dc.type | Article | - |
dc.identifier.email | Huang, J: jxhuang@hku.hk | - |
dc.identifier.email | Sun, Y: sunyim@hku.hk | - |
dc.identifier.authority | Huang, J=rp01758 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1016/j.landurbplan.2020.103977 | - |
dc.identifier.scopus | eid_2-s2.0-85096182610 | - |
dc.identifier.hkuros | 318744 | - |
dc.identifier.volume | 206 | - |
dc.identifier.spage | article no. 103977 | - |
dc.identifier.epage | article no. 103977 | - |
dc.identifier.isi | WOS:000597161200001 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 0169-2046 | - |