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Title: | Anàlisi de les dades del Dia Mundial de les Malalties Minoritàries a Twitter |
Author: | Dalmases Juanet, Joaquim Maria de |
Tutor: | Subirats, Laia Bonet-Carne, Elisenda |
Others: | Prados Carrasco, Ferran |
Abstract: | Minority diseases are a social problem that affects basic humanitarian rights such as social equality. The majority of patients who suffer from them are helpless to cope with them. To combat them, it is necessary to define support for research, drug development, the creation of networks between patient groups, to intensify the fight, awareness-raising and many other organized social actions. With the aim of reducing the impact of rare diseases on the lives of patients and their families, this paper characterizes the content of Twitter data captured around World Rare Disease Day. around World Rare Disease Day 2020 to act in this direction. This characterization of social data, will be performed from 2 points of view, structural and content analysis. Unsupervised machine learning techniques will be applied unsupervised automatic learning techniques will be applied to find the existing emerging user communities existing in this topic. Having the user communities available will allow us to give voice to and enhance all the aspects that unite them and to aspects that unite them and to have a criterion for decision making towards their current level of attention and the necessary current level of attention and the one needed in the future. |
Keywords: | social networks data analysis |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2020 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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quimdalmasesTFM0620memòria.pdf | Memòria del TFM | 11,42 MB | Adobe PDF | View/Open |
quimdalmasesTFM0620presentació.pdf | Presentació del TFM | 5,05 MB | Adobe PDF | View/Open |
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