Characterizing and modeling crisis-related conversations in twitter
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 mai...
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| Altres autors: | , |
| Format: | bachelorThesis |
| Publicat: |
2020
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| Matèries: | |
| Accés en línia: | http://www.dspace.espol.edu.ec/handle/123456789/54426 |
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| Sumari: | 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. |
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