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Semantic and geospatial mapping of instagram images in Saint-Petersburg

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific


Original languageEnglish
Title of host publicationArtificial Intelligence and Natural Language AINL FRUCT 2016 Conference
Publication statusPublished - 2016
Externally publishedYes
Publication typeB3 Non-refereed article in conference proceedings


The availability of large urban social media data creates new opportunities for studying cities. In our paper we propose a new direction for this research: a joint analysis of geolocations of shared images and their content as determined by computer vision. To test our ideas, we use a dataset of 47,410 Instagram images shared in the city of St.Petersburg over one year. We show how a combination of semantic clustering, image recognition and geospatial analysis can detect important patterns related to both how people use a city and how they represent in social media.


  • Artificial Intelligence, urban studies, Data science, computer science

Field of science, Statistics Finland