Please use this identifier to cite or link to this item: http://www.dspace.espol.edu.ec/handle/123456789/54426
Title: Characterizing and modeling crisis-related conversations in twitter
Authors: Torres, Johnny
Abad, Cristina, Principal Co-Advisor
Vaca, Carmen, Principal Co-Advisor
Keywords: Machine learning models
automatically label thedata
conversation on Twitter
Issue Date: 2020
Publisher: ESPOL. FIEC.
Citation: Torres, J. (202). Characterizing and modeling crisis-related conversations in twitter. (Doctoral Thesis). Escuela Superior Politécnica del Litoral. Guayaquil.
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.
URI: http://www.dspace.espol.edu.ec/handle/123456789/54426
Appears in Collections:Tesis de Doctorado en Ciencias Computacionales Aplicadas

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