This paper presents work in interlinking social stream information with geographical spaces through the use of Linked Data technologies. The paper focuses on filtering, enriching, structuring and interlinking microposts of localised (i.e. geo-tagged) social streams (a.k.a localised forums) to profile geographical areas (e.g., cities, countries). For this purpose, we enriched social streams extracted from Twitter1, Facebook 2 and TripAdvisor3 and structured them into well-known vocabularies and data models, such as SIOC and SKOS. To integrate this information into a location profile we introduce the linkedPOI ontology. The linkedPOI ontology captures and leverages DBpedia categories to derive concepts which profile a geographic space. We exemplify the use of social stream-based location profiling by means of a travel mashup case study. We introduce the Topica Portal, which allows users to browse geographical spaces by topic.We highlight potential impact for the future of semantic travel mashup systems. © Springer-Verlag 2013.
CITATION STYLE
Cano, A. E., Dadzie, A. S., Burel, G., & Ciravegna, F. (2013). Topica - Profiling locations through social streams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7774 LNCS, pp. 290–305). https://doi.org/10.1007/978-3-642-37996-3_20
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