{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/learning-from-barcelona-instagram-data-what","title":"Learning from #Barcelona Instagram data what Locals and Tourists post about its Neighbourhoods","arxiv_id":"1808.06369","date":"2018-08-20","proceeding":null,"authors":["Raul Gomez","Lluis Gomez","Jaume Gibert","Dimosthenis Karatzas"],"abstract":"Massive tourism is becoming a big problem for some cities, such as Barcelona,\ndue to its concentration in some neighborhoods. In this work we gather\nInstagram data related to Barcelona consisting on images-captions pairs and,\nusing the text as a supervisory signal, we learn relations between images,\nwords and neighborhoods. Our goal is to learn which visual elements appear in\nphotos when people is posting about each neighborhood. We perform a language\nseparate treatment of the data and show that it can be extrapolated to a\ntourists and locals separate analysis, and that tourism is reflected in Social\nMedia at a neighborhood level. The presented pipeline allows analyzing the\ndifferences between the images that tourists and locals associate to the\ndifferent neighborhoods. The proposed method, which can be extended to other\ncities or subjects, proves that Instagram data can be used to train multi-modal\n(image and text) machine learning models that are useful to analyze\npublications about a city at a neighborhood level. We publish the collected\ndataset, InstaBarcelona and the code used in the analysis.","url_abs":"http://arxiv.org/abs/1808.06369v1","url_pdf":"http://arxiv.org/pdf/1808.06369v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"learning-from-barcelona-instagram-data-what","repo_url":"https://github.com/gombru/insbcn","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}