A spatial analysis of non‐English Twitter activity in Houston, TX. Issue 4 (11th April 2018)

• Record Type: Journal Article
• Authors: Haffner, Matthew
• Is Part Of: Transactions in GIS. Volume 22:Issue 4(2018)
• Page Start: 913
• Page End: 929
• Publication Date: 2018-04-11
• Subjects: Geographic information systems -- Periodicals; 910.285
• DOI: 10.1111/tgis.12335
• Languages: English
• ISSNs: 1361-1682

Abstract

Abstract: The use of social media data in geographic studies has become common, yet the question of social media's validity in such contexts is often overlooked. Social media data suffers from a variety of biases and limitations; nevertheless, with a proper understanding of the drawbacks, these data can be powerful. As cities seek to become "smarter, " they can potentially use social media data to creatively address the needs of their most vulnerable groups, such as ethnic minorities. However, questions remain unanswered regarding who uses these social networking platforms, how people use these platforms, and how representative social media data is of users' everyday lives. Using several forms of regression, I explore the relationships between a conventional data source (the U.S. Census) and a subset of Twitter data potentially representative of minority groups: tweets created by users with an account language other than English. A considerable amount of non‐stationarity is uncovered, which should serve as a warning against sweeping statements regarding the demographics of users and where people prefer to post. Further, I find that precisely located Twitter data informs us more about the digital status of places and less about users' day‐to‐day travel patterns.