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Cited by 67Geographic Information Systems StudiesHuman Mobility and Location-Based AnalysisMobile Crowdsensing and Crowdsourcing

The Geography and Importance of Localness in Geotagged Social Media

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Johnson, Isaac L., Sengupta, Subhasree, Schöning, Johannes, Hecht, Brent·2016·Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
DOI 10.1145/2858036.2858122
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Abstract

Geotagged tweets and other forms of social media volunteered geographic information (VGI) are becoming increasingly critical to many applications and scientific studies. An important assumption underlying much of this research is that social media VGI is "local", or that its geotags correspond closely with the general home locations of its contributors. We demonstrate through a study on three separate social media communities (Twitter, Flickr, Swarm) that this localness assumption holds in only about 75% of cases. In addition, we show that the geographic contours of localness follow important sociodemographic trends, with social media in, for instance, rural areas and older areas, being substantially less local in character (when controlling for other demographics). We demonstrate through a case study that failure to account for non-local social media VGI can lead to misrepresentative results in social media VGI-based studies. Finally, we compare the methods for determining localness, finding substantial disagreement in certain cases, and highlight new best practices for social media VGI-based studies and systems.

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  • Studies relying on geo-tagged tweets often assume that geo-tags correspond closely with the general home locations of its contributors; this assumption holds only in about 75% of cases in a study of three social platforms.

    “Studies relying on geo-tagged tweets often assume that geo-tags “correspond closely with the general home locations of its contributors;” yet, Johnson et al. (2016) found this assumption holds only in about 75% of cases in a study of three social platforms.”

    From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Johnson et al., 2016

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Cited by

Sorted by citations

Authors
Johnson, I. L., Sengupta, S., Schöning, J., & Hecht, B.
Affiliations
  • University of Minnesota (US)
  • Hasselt University (BE)
ORCID
Venue
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2016-05-07
Pages
515-526
DOI
10.1145/2858036.2858122
OpenAlex
W2297902541
Cited by
67
References
2
Citations by year
2026: 4 · 2025: 7 · 2024: 4 · 2023: 6 · 2022: 2 · 2021: 6 · 2020: 5 · 2019: 6 · 2018: 14 · 2017: 12 · 2016: 1
FWCI
51.32
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor, 365 d)
Locations
  • CHI Conference on Human Factors in Computing Systems (publishedVersion)
  • Document Server@UHasselt (UHasselt) (submittedVersion)
Funders
National Science Foundation (IIS-1526988, IIS-1421655)
Topics
  • Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
  • Social Sciences › Transportation › Human Mobility and Location-Based Analysis
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
Keywords
localness, geotagged social media, volunteered geographic information, geotags, place of residence, sociodemographic factors, rural areas, Twitter, Flickr, swarms

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