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T-CREo: A Twitter Credibility Analysis Framework

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dc.contributor.author Cardinale, Yudith es_PE
dc.contributor.author Dongo, Irvin es_PE
dc.contributor.author Robayo, German es_PE
dc.contributor.author Cabeza, David es_PE
dc.contributor.author Aguilera, Ana es_PE
dc.contributor.author Medina, Sergio es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2021
dc.description This research was supported by the FONDO NACIONAL DE DESARROLLO CIENTIFICO, TECNOLOGICO Y DE INNOVACION TECNOLOGICA ~ FONDECYT as an executing entity of CONSEJO NACIONAL DE CIENCIA, TECNOLOGIA E INNOVACION TECNOLOGICA - CONCYTEC under grant agreement No. 01-2019-FONDECYT-BM-INC.INV in the project RUTAS: Robots for Urban Tourism centers, Autonomous and Semantic-based.
dc.description.abstract Social media and other platforms on Internet are commonly used to communicate and generate information. In many cases, this information is not validated, which makes it difficult to use and analyze. Although there exist studies focused on information validation, most of them are limited to specific scenarios. Thus, a more general and flexible architecture is needed, that can be adapted to user/developer requirements and be independent of the social media platform. We propose a framework to automatically and in real-time perform credibility analysis of posts on social media, based on three levels of credibility: Text, User, and Social. The general architecture of our framework is composed of a front-end, a light client proposed as a web plug-in for any browser; a back-end that implements the logic of the credibility model; and a third-party services module. We develop a first version of the proposed system, called T-CREo (Twitter CREdibility analysis framework) and evaluate its performance and scalability. In summary, the main contributions of this work are: the general framework design; a credibility model adaptable to various social networks, integrated into the framework; and T-CREo as a proof of concept that demonstrates the framework applicability and allows evaluating its performance for unstructured information sources; results show that T-CREo qualifies as a highly scalable real-time service. The future work includes the improvement of T-CREo implementation, to provide a robust architecture for the development of third-party applications, as well as the extension of the credibility model for considering bots detection, semantic analysis and multimedia analysis.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1109/ACCESS.2021.3060623
dc.identifier.uri https://hdl.handle.net/20.500.12390/2948
dc.language.iso eng
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof IEEE ACCESS
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject web scraping
dc.subject Social networking (online) es_PE
dc.subject Blogs es_PE
dc.subject Real-time systems es_PE
dc.subject Computer architecture es_PE
dc.subject Analytical models es_PE
dc.subject Adaptation models es_PE
dc.subject Service-oriented architecture es_PE
dc.subject API es_PE
dc.subject credibilty es_PE
dc.subject fake news es_PE
dc.subject information sources es_PE
dc.subject twitter es_PE
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#2.02.04
dc.title T-CREo: A Twitter Credibility Analysis Framework
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
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