Characterizing and modeling crisis-related conversations in twitter

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