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Twitter is the most popular social media platform in Japan for social interactions and real-time information exchanges during disasters; however, almost all information is in Japanese. This paper describes the data collection and analysis process associated with the planned construction of a real-time disaster-related information providing system for foreign tourists. To this end, characteristics of the tweets during the 2018 Osaka North Earthquake were analyzed. Despite there being thousands of tweets during the earthquake, information was hardly transmitted to foreign tourists. In this study, a data set of more than 9,000,000 tweets was used to analyze the information being shared and identify the most frequently used terms.
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Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.