Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/1947
Title: Data Mining the City: User Demands through Social Media
Authors: Soydaş Çakır, Hülya
Levent, Vecdi Emre
Keywords: Architecture
city
data mining
design
social media
Issue Date: 2021
Publisher: Konya Technical University Faculty of Architecture and Design
Abstract: Purpose Information technologies are commonly used in architectural and urban design. The use of these technologies providing support at every stage of the design opens up different perspectives for designers and users. The aim of the study is to obtain user demands for green spaces of a specific district by mining data through social media and to detect the actual green spaces of the same district using applications developed for this purpose. User demands for design decisions and applications of green spaces and the current situation of the study area are evaluated. Design/Methodology/Approach The research is firstly realized through social media, and data obtained from Twitter is analysed in order to evaluate user demands for parks and green spaces of Ataşehir district in İstanbul City. Secondly, all green areas in the same district are detected by using digital maps. Two applications are specifically designed for this research; Tweet Grabber is used for user sentiment analysis on social media and Map Grabber is processed for extraction of green spaces via maps. The total area of the green spaces is compared with the desired area of open and green spaces per user. Findings The user demands and thoughts obtained in the study about the green spaces of the district are compatible with the actual situation of green spaces. It is observed that the users are mostly dissatisfied with the adequacy of green spaces. Designers, politicians, municipalities and all stakeholders can benefit from the obtained user expectations and feedback. Interpreting user demands by mining data through social media enables user participation in design decisions. This research method can be supportive and adaptive in related issues of design for the cities, enabling user participation in architectural and urban design. Research Limitations/Implications Parks and green spaces of Ataşehir district of İstanbul are taken as a case study. Twitter is chosen for mining of data in social media based on parameters such as keywords and location. Social/Practical Implications The impact and support of users in design decisions can be clearly demonstrated by advanced information technologies. Mining data through social media and developed applications will contribute to design decisions and policies for architectural and urban spaces. Originality/Value Tweet Grabber and Map Grabber applications are developed for this research in order to get text based and image based data. The research includes a unique case study for mining data through social media on a specific design issue and target location.
Description: iconarpID: 606
iconarp:ART
URI: https://doi.org/10.15320/ICONARP.2021.181
https://iconarp.ktun.edu.tr/index.php/iconarp/article/view/606
https://iconarp.ktun.edu.tr/index.php/iconarp/article/view/606/308
https://hdl.handle.net/20.500.13091/1947
ISSN: 2147-9380
Appears in Collections:ICONARP - International Journal of Architecture and Planning

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