CityMe - dataset with mapped regionsdoi:10.82210/E5LK1YRepositório Polen QTY2024-05-071Costa, Elvira, 2024, "CityMe - dataset with mapped regions", https://doi.org/10.82210/E5LK1Y, Repositório Polen QTY, V1CityMe - dataset with mapped regionsdoi:10.82210/E5LK1YCosta, ElviraLeonardo Vanneschi2024-05-07EXPL/GES-URB/1429/2021Repositório Polen QTYCosta, ElviraCosta, Elvira2024-05-07Social Sciences - Economic and Social Geography - Urban StudiesThe main components of the framework include: setting the aggregated textual data from Twitter and place-based sources (Google and OSM); employing the BERTopic transformer-based topic modeling for each source; comparing topics emerged from each source using the cosine similarity metric; carrying out Getis-Ord G∗i hotspot analysis for retrieving statistically representative topic-based cells; applying the Jaccard similarity index aimed at ultimately comparing thematic and spatial similarities that support the discussion on content-location relationships for the case study.<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>Tang, V., & Painho, M. (2023). Content-location relationships: a framework to explore correlations between space-based and place-based user-generated content. International Journal of Geographical Information Science, 37(8), 1840–1871. https://doi.org/10.1080/13658816.2023.221386910.1080/13658816.2023.2213869Tang, V., & Painho, M. (2023). Content-location relationships: a framework to explore correlations between space-based and place-based user-generated content. International Journal of Geographical Information Science, 37(8), 1840–1871. https://doi.org/10.1080/13658816.2023.2213869Pure research outputs - 70524.xlsapplication/vnd.ms-excel