#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data
The dynamic nature of cities, understood as complex systems with a variety of concurring factors, poses significant challenges to urban analysis for supporting planning processes. This particularly applies to large urban events because their characteristics often contradict daily planning routines....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Cogitatio
2018-03-01
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| Series: | Urban Planning |
| Subjects: | |
| Online Access: | https://www.cogitatiopress.com/urbanplanning/article/view/1287 |
| _version_ | 1818284157251354624 |
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| author | Anna Kovacs-Gyori Alina Ristea Clemens Havas Bernd Resch Pablo Cabrera-Barona |
| author_facet | Anna Kovacs-Gyori Alina Ristea Clemens Havas Bernd Resch Pablo Cabrera-Barona |
| author_sort | Anna Kovacs-Gyori |
| collection | DOAJ |
| description | The dynamic nature of cities, understood as complex systems with a variety of concurring factors, poses significant challenges to urban analysis for supporting planning processes. This particularly applies to large urban events because their characteristics often contradict daily planning routines. Due to the availability of large amounts of data, social media offer the possibility for fine-scale spatial and temporal analysis in this context, especially regarding public emotions related to varied topics. Thus, this article proposes a combined approach for analyzing large sports events considering event days vs comparison days (before or after the event) and different user groups (residents vs visitors), as well as integrating sentiment analysis and topic extraction. Our results based on various analyses of tweets demonstrate that different spatial and temporal patterns can be identified, clearly distinguishing both residents and visitors, along with positive or negative sentiment. Furthermore, we could assign tweets to specific urban events or extract topics related to the transportation infrastructure. Although the results are potentially able to support urban planning processes of large events, the approach still shows some limitations including well-known biases in social media or shortcomings in identifying the user groups and in the topic modeling approach. |
| first_indexed | 2024-12-13T00:48:20Z |
| format | Article |
| id | doaj.art-f824e6eedc654db59179ecee5eb1a242 |
| institution | Directory Open Access Journal |
| issn | 2183-7635 |
| language | English |
| last_indexed | 2024-12-13T00:48:20Z |
| publishDate | 2018-03-01 |
| publisher | Cogitatio |
| record_format | Article |
| series | Urban Planning |
| spelling | doaj.art-f824e6eedc654db59179ecee5eb1a2422022-12-22T00:04:59ZengCogitatioUrban Planning2183-76352018-03-0131759910.17645/up.v3i1.1287691#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter DataAnna Kovacs-Gyori0Alina Ristea1Clemens Havas2Bernd Resch3Pablo Cabrera-Barona4Department of Geoinformatics—Z_GIS, University of Salzburg, AustriaDepartment of Geoinformatics—Z_GIS, University of Salzburg, AustriaDepartment of Geoinformatics—Z_GIS, University of Salzburg, AustriaDepartment of Geoinformatics—Z_GIS, University of Salzburg, Austria / Center for Geographic Analysis, Harvard University, USAInstitute of Higher National Studies—IAEN, Ecuador / Latin American Social Sciences Institute—FLACSO, EcuadorThe dynamic nature of cities, understood as complex systems with a variety of concurring factors, poses significant challenges to urban analysis for supporting planning processes. This particularly applies to large urban events because their characteristics often contradict daily planning routines. Due to the availability of large amounts of data, social media offer the possibility for fine-scale spatial and temporal analysis in this context, especially regarding public emotions related to varied topics. Thus, this article proposes a combined approach for analyzing large sports events considering event days vs comparison days (before or after the event) and different user groups (residents vs visitors), as well as integrating sentiment analysis and topic extraction. Our results based on various analyses of tweets demonstrate that different spatial and temporal patterns can be identified, clearly distinguishing both residents and visitors, along with positive or negative sentiment. Furthermore, we could assign tweets to specific urban events or extract topics related to the transportation infrastructure. Although the results are potentially able to support urban planning processes of large events, the approach still shows some limitations including well-known biases in social media or shortcomings in identifying the user groups and in the topic modeling approach.https://www.cogitatiopress.com/urbanplanning/article/view/1287geographic informationGISOlympic Gamesplanned eventssentiment analysissocial mediaspatiotemporal analysistopic extraction |
| spellingShingle | Anna Kovacs-Gyori Alina Ristea Clemens Havas Bernd Resch Pablo Cabrera-Barona #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data Urban Planning geographic information GIS Olympic Games planned events sentiment analysis social media spatiotemporal analysis topic extraction |
| title | #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data |
| title_full | #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data |
| title_fullStr | #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data |
| title_full_unstemmed | #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data |
| title_short | #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data |
| title_sort | london2012 towards citizen contributed urban planning through sentiment analysis of twitter data |
| topic | geographic information GIS Olympic Games planned events sentiment analysis social media spatiotemporal analysis topic extraction |
| url | https://www.cogitatiopress.com/urbanplanning/article/view/1287 |
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