Abstract
The rapid development of technology has changed the way people get informed from traditional media to online ones. Governmental accounts emerged on Twitter for rapid broadcasting of information related to real-time events and incidents. However, the accurate definition of locations of those events is a difficult task given the fact that their description is provided in free text with no predefined format for the efficient resolving of geolocation. This paper proposes the EventMapping framework that aims at identifying and extracting geographic information directly from official Greek governmental Twitter accounts and visualizing it on an interactive map. For the purposes of this work, two methodologies are implemented and evaluated. The best approach reached the level of 0.93 in terms of F1-score as far as the geographical term detection is concerned, as well as 93.5% in terms of accuracy on the resolved coordinates. The source-code of our framework is publicly available in open-source format on GitHub.
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Acknowledgments
We acknowledge support of this work by the project “Par-ICT CENG: Enhancing ICT research infrastructure in Central Greece to enable processing of Big data from sensor stream, multimedia content, and complex mathematical modeling and simulations” (MIS 5047244) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund).
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Razis, G., Maroufidis, I., Anagnostopoulos, I. (2023). EventMapping: Geoparsing and Geocoding of Twitter Messages in the Greek Language. In: Maglogiannis, I., Iliadis, L., Papaleonidas, A., Chochliouros, I. (eds) Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops. AIAI 2023. IFIP Advances in Information and Communication Technology, vol 677. Springer, Cham. https://doi.org/10.1007/978-3-031-34171-7_25
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DOI: https://doi.org/10.1007/978-3-031-34171-7_25
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