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Crowdsourcing a Collective Sense of Place
Andrew Jenkins1, Arie Croitoru1,2, Andrew T Crooks3
1Department of Geography and GeoInformation Science George Mason University, Fairfax, Virginia, United States of America.
Plos One
|April 7, 2016
Summary
Researchers computationally analyzed user-generated content to identify unique sociocultural signatures of urban places. This quantitative approach reveals how collective human experiences shape the meaning and characteristics of specific locations.
Area of Science:
- Geographic Information Science
- Computational Social Science
- Human Geography
Background:
- Place is traditionally a theoretical construct in social sciences.
- User-generated content (social media, Wikipedia) offers new data for analysis.
- Computational methods enable quantifying shared meanings of places.
Purpose of the Study:
- To computationally derive and quantify sociocultural signatures of urban places.
- To analyze shared meaning assigned to locations through human activities.
- To identify 'platial themes' from crowd-contributed content.
Main Methods:
- Utilized probabilistic topic modeling.
- Employed semantic association techniques.
- Applied spatial clustering to Twitter and Wikipedia data.
Main Results:
- Identified unique thematic characteristics ('platial themes') of different urban locations.
- Demonstrated how crowd-contributed content reflects collective sense of place.
- Quantified the transformation of locations into places through human experience.
Conclusions:
- Computational analysis of user-generated content can reveal place meaning.
- Sociocultural signatures provide a quantitative understanding of place.
- This approach offers insights into how people shape urban characteristics.
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