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Characterizing and modeling crisis-related conversations in twitter

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dc.contributor.author Torres, Johnny
dc.contributor.author Abad, Cristina, Director
dc.contributor.author Vaca, Carmen, Co-Director
dc.date.accessioned 2022-06-15T16:31:57Z
dc.date.available 2022-06-15T16:31:57Z
dc.date.issued 2020
dc.identifier.citation Torres, J. (202). Characterizing and modeling crisis-related conversations in twitter. (Doctoral Thesis). Escuela Superior Politécnica del Litoral. Guayaquil. es_EC
dc.identifier.uri http://www.dspace.espol.edu.ec/handle/123456789/54426
dc.description.abstract In this doctoral thesis, text data extracted from Twitter conversations regarding a natural disasteris analyzed and modelled. In doing so, contributions in different areas emerge: novel Twitterconversation datasets, new tasks scenarios, machine learning models to automatically label thedata. The main goal is to develop a conversational model to help NGOs to cope with the overwhelmingamount of data in the form of conversations, enabling citizens to contribute more efficiently duringnatural disasters. es_EC
dc.language.iso en es_EC
dc.publisher ESPOL. FIEC. es_EC
dc.subject Machine learning models es_EC
dc.subject automatically label thedata es_EC
dc.subject conversation on Twitter es_EC
dc.title Characterizing and modeling crisis-related conversations in twitter es_EC
dc.type Thesis es_EC


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