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dc.contributor.author | Aguado-Sarrió, Guillem | es_ES |
dc.contributor.author | Julian Inglada, Vicente Javier | es_ES |
dc.contributor.author | García-Fornes, A | es_ES |
dc.contributor.author | Espinosa Minguet, Agustín Rafael | es_ES |
dc.date.accessioned | 2021-05-20T03:34:16Z | |
dc.date.available | 2021-05-20T03:34:16Z | |
dc.date.issued | 2020-06 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/166534 | |
dc.description.abstract | [EN] Nowadays there is a strong integration of online social platforms and applications with our daily life. Such interactions can make risks arise and compromise the information we share, thereby leading to privacy issues. In this work, a proposal that makes use of a software agent that performs sentiment analysis and another performing stress analysis on keystroke dynamics data has been designed and implemented. The proposal consists of a set of new agents that have been integrated into a multi-agent system (MAS) for guiding users interacting in online social environments, which has agents for sentiment and stress analysis on text. We propose a combined analysis using the different agents. The MAS analyzes the states of the users when they are interacting, and warns them if the messages they write are deemed negative. In this way, we aim to prevent potential negative outcomes on social network sites (SNSs). We performed experiments in the laboratory with our private SNS Pesedia over a period of one month, so we gathered data about text messages and keystroke dynamics data, and used the datasets to train the artificial neural networks (ANNs) of the agents. A set of experiments was performed for discovering which analysis is able to detect a state of the user that propagates more in the SNS, so it may be more informative for the MAS. Our study will help develop future intelligent systems that utilize user data in online social environments for guiding or helping them in their social experience. | es_ES |
dc.description.sponsorship | This work was funded by the project TIN2017-89156-R of the Spanish government. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Applied Sciences | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Multi-agent system | es_ES |
dc.subject | Social networks | es_ES |
dc.subject | Sentiment analysis | es_ES |
dc.subject | Stress analysis | es_ES |
dc.subject | Keystroke dynamics | es_ES |
dc.subject.classification | LENGUAJES Y SISTEMAS INFORMATICOS | es_ES |
dc.title | Using Keystroke Dynamics in a Multi-Agent System for User Guiding in Online Social Networks | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/app10113754 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89156-R/ES/AGENTES INTELIGENTES PARA ASESORAR EN PRIVACIDAD EN REDES SOCIALES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació | es_ES |
dc.description.bibliographicCitation | Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A.; Espinosa Minguet, AR. (2020). Using Keystroke Dynamics in a Multi-Agent System for User Guiding in Online Social Networks. Applied Sciences. 10(11):1-20. https://doi.org/10.3390/app10113754 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/app10113754 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 20 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 10 | es_ES |
dc.description.issue | 11 | es_ES |
dc.identifier.eissn | 2076-3417 | es_ES |
dc.relation.pasarela | S\417995 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
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