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Ballparking the Urban Placeness: A Case Study of Analyzing Starbucks Posts on Instagram

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Social Informatics (SocInfo 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11185))

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Abstract

Placeness or the “sense of a place” plays a vital role in urban design and planning. Research on placeness in the past has been conducted via conventional methods like surveys to reveal essential insights for urban planners and architects. For taking a glimpse into placeness by analyzing common factors across geographies, we choose Instagram posts from Starbucks as a case study, owing to its the-next-door coffee shop psychological construct. We conduct our research by first adopting a flexible ontological framework to organize the concepts governing placeness. Next, we curate a dataset of community generated Instagram posts from Starbucks in three major metropolitan cities of the world: New York, Seoul, and Tokyo. The curated dataset is then automatically enriched with contextual attributes such as activity, visitor demographics, and time via machine learning techniques. We finally analyze and validate the quantitative variations in contextual information with findings from well-accepted cross-cultural case studies. Our results show that placeness mined from Starbucks, a prominent urban third-place, can be reliably utilized to discover surrounding urban placeness.

M. Yu—Co-primary author, order chosen alphabetically.

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Acknowledgments

Minsang Yu and Dongman Lee were supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. 2017-0-00537, Development of Autonomous IoT Collaboration Framework for Space Intelligence). Gaurav Kalra and Daeyoung Kim were supported by International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning of Korea (2016K1A3A7A03952054). Meeyoung Cha was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. NRF-2017R1E1A1A01076400). The authors are grateful to Byoungheon Shin, Joowon Yoon, and Zhantore Orynbassarov for their help.

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Authors and Affiliations

  1. Auto-ID Labs and School of Computing, KAIST, Daejeon, South Korea

    Gaurav Kalra & Daeyoung Kim

  2. School of Computing, KAIST, Daejeon, South Korea

    Gaurav Kalra, Minsang Yu, Dongman Lee, Meeyoung Cha & Daeyoung Kim

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  1. Gaurav Kalra
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  3. Dongman Lee
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Corresponding author

Correspondence to Dongman Lee .

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Editors and Affiliations

  1. University of Koblenz, Koblenz, Germany

    Steffen Staab

  2. National Research University Higher School of Economics, St. Petersburg, Russia

    Olessia Koltsova

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

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Kalra, G., Yu, M., Lee, D., Cha, M., Kim, D. (2018). Ballparking the Urban Placeness: A Case Study of Analyzing Starbucks Posts on Instagram. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11185. Springer, Cham. https://doi.org/10.1007/978-3-030-01129-1_18

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  • DOI: https://doi.org/10.1007/978-3-030-01129-1_18

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