The analysis of architectural discourse in the context of computational public opinion: Data mining of Google map reviews

The analysis of architectural discourse in the context of computational public opinion: Data mining of Google map reviews

Taşdelen, Hanife Sümeyye; Gül, Leman Figen

Full Article:

New media platforms and mapping tools are created by digital communities, and their representations influence public opinion. Crowdsourcing platforms such as Twitter, Instagram, Google search engines and Maps have no such limitations or boundaries as in the physical space, these platforms are creating new virtual public places. To assess and forecast the accessibility and aesthetic issues of urban spaces in Istanbul, text and image data from Google Maps were employed. In this study, we searched at the reviews of certain public/semi-public places by using text mining and image analytics tools. Recently designed or renovated 11 public buildings and open places were chosen. The main findings of this exploratory study are that; 1) the level of being public can be understood from the crowdsourcing, 2) image analytics of crowdsourced visual data can assist to identify the aesthetic quality, and 3) the accessibility capacity of public spaces can be identified.

New media platforms and mapping tools are created by digital communities, and their representations influence public opinion. Crowdsourcing platforms such as Twitter, Instagram, Google search engines and Maps have no such limitations or boundaries as in the physical space, these platforms are creating new virtual public places. To assess and forecast the accessibility and aesthetic issues of urban spaces in Istanbul, text and image data from Google Maps were employed. In this study, we searched at the reviews of certain public/semi-public places by using text mining and image analytics tools. Recently designed or renovated 11 public buildings and open places were chosen. The main findings of this exploratory study are that; 1) the level of being public can be understood from the crowdsourcing, 2) image analytics of crowdsourced visual data can assist to identify the aesthetic quality, and 3) the accessibility capacity of public spaces can be identified.

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DOI: 10.5151/sigradi2022-sigradi2022_258

Referências bibliográficas

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Como citar:

Taşdelen, Hanife Sümeyye; Leman Figen Gül; "The analysis of architectural discourse in the context of computational public opinion: Data mining of Google map reviews", p-101-112. In: XXVI International Conference of the Iberoamerican Society of Digital Graphics. São Paulo: Blucher, 2023.
ISSN 23186968, DOI 10.5151/sigradi2022-sigradi2022_258