Understanding gendered spaces using social media data

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Abstract

In Saudi Arabia, gender shapes cities in a way that is not commonly found in other cities due to Saudi Arabia’s imposed gender segregation. This segregation policy drives both genders to different areas of the city in different ways, influencing the emergence of gendered spaces. In this paper, we utilize social media data to better understand gendered spaces throughout the city of Riyadh. For our analysis, we developed an algorithm to perform gender annotation based on users’ first names. The method, optimized for English and Arabic language names, was applied to a sample of over 120,000 geotagged tweets between November 2016 and January 2017. The customer demographics of Foursquare venues were estimated based on the gender ratio of reviewers. Areas with a high degree of gender concentration in these datasets were used to identify gendered spaces. The correlation between gendered space identified from tweets and Foursquare venues was used to examine the link between amenities and gender-specific mobility habits in Riyadh. Throughout our analysis, we aim to identify ways in which government policies and the organization of businesses and services with similar customer demographics impact the mobility patterns of women and men and lead to the emergence of gendered spaces in Riyadh.

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APA

Alfayez, A., Awwad, Z., Kerr, C., Alrashed, N., Williams, S., & Al-Wabil, A. (2017). Understanding gendered spaces using social media data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10283 LNCS, pp. 338–356). Springer Verlag. https://doi.org/10.1007/978-3-319-58562-8_26

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