Content-location relationships: a framework to explore correlations between space-based and place-based user-generated content

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
44 Downloads (Pure)

Abstract

The use of social media and location-based networks through GPS-enabled devices provides geospatial data for a plethora of applications in urban studies. However, the extent to which information found in geo-tagged social media activity corresponds to the spatial context is still a topic of debate. In this article, we developed a framework aimed at retrieving the thematic and spatial relationships between content originated from space-based (Twitter) and place-based (Google Places and OSM) sources of geographic user-generated content based on topics identified by the embedding-based BERTopic model. The contribution of the framework lies on the combination of methods that were selected to improve previous works focused on content-location relationships. Using the city of Lisbon (Portugal) to test our methodology, we first applied the embedding-based topic model to aggregated textual data coming from each source. Results of the analysis evidenced the complexity of content-location relationships, which are mostly based on thematic profiles. Nonetheless, the framework can be employed in other cities and extended with other metrics to enrich the research aimed at exploring the correlation between online discourse and geography.
Original languageEnglish
Pages (from-to)1840–1871
Number of pages32
JournalInternational Journal Of Geographical Information Science
Volume37
Issue number8
Early online date27 Jun 2023
DOIs
Publication statusPublished - 3 Aug 2023

Keywords

  • Content-location relationships
  • UGC
  • geo-tagged activity
  • topic modeling

Fingerprint

Dive into the research topics of 'Content-location relationships: a framework to explore correlations between space-based and place-based user-generated content'. Together they form a unique fingerprint.

Cite this