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Detecting discussion communities on vaccination in twitter

Bello, Gema, Hernandez-Castro, Julio, Camacho, David (2016) Detecting discussion communities on vaccination in twitter. Future Generation Computer Systems, 66 . pp. 125-136. ISSN 0167-739X. (doi:10.1016/j.future.2016.06.032) (KAR id:58380)

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http://dx.doi.org/10.1016/j.future.2016.06.032

Abstract

Vaccines have contributed to dramatically decrease mortality from infectious diseases in the 20th century.

the population about vaccination for the past 20 years. These communities discussing on vaccines have

of preventable diseases such as measles, polio, or influenza, have shown the effect of a decrease in

Twitter generates over 400 million tweets every day. Data mining provides the necessary algorithms

these techniques to detect and track discussion communities on vaccination arising from Social Networks.

showing how vaccine opinions of Twitter users can influence over vaccination decision-making. Then,

experimental results show that these techniques can be used to discover social discussion communities

try to use the detection and tracking of these social communities to avoid or mitigate new outbreaks of

eradicated diseases

Item Type: Article
DOI/Identification number: 10.1016/j.future.2016.06.032
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Sciences > School of Computing > Security Group
Depositing User: Julio Hernandez-Castro
Date Deposited: 03 Nov 2016 16:21 UTC
Last Modified: 03 Mar 2020 04:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58380 (The current URI for this page, for reference purposes)
Hernandez-Castro, Julio: https://orcid.org/0000-0002-6432-5328
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