Describing place through user generated content

Authors

  • Ross Purves University of Zurich
  • Alistair Edwardes Department of Communities and Local Government, UK
  • Jo Wood School of Information Science at City University, London.

DOI:

https://doi.org/10.5210/fm.v16i9.3710

Abstract

Geographically referenced user generated content provides us with an opportunity to, for the first time, gather perspectives on place over large areas by exploring how very many people describe information. We present a framework for analysing large collections of user generated content. This involves classification of descriptive terms attached by users to photographs into facets of elements, qualities, and activities. We apply this framework to two contrasting photographic archives — Flickr and Geograph, representing weakly and strongly moderated content respectively. We propose a method for removing user-generated bias from such collections though the user of term profiles that can assess the effect of the most and least prolific contributors to a collection. Analysis and visualization of co–occurrence between terms suggests clear differences in the description of place between the two collections, both in terms of the facets used and their geographical footprints. This is attributed to the role of moderation/editorialising of content; to the role tags and free–text has on descriptive behaviour and on the geographic footprint of content supplied to the two collections.

Author Biographies

Ross Purves, University of Zurich

Lecturer in GIScience at the University of Zurich, Switzerland.

Alistair Edwardes, Department of Communities and Local Government, UK

geographical analyst for the Department of Communities and Local Government in the U.K.

Jo Wood, School of Information Science at City University, London.

Reader in GIScience at the School of Information Science at City University, London, U.K.

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Published

2011-08-13

How to Cite

Purves, R., Edwardes, A., & Wood, J. (2011). Describing place through user generated content. First Monday, 16(9). https://doi.org/10.5210/fm.v16i9.3710