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Detalhes

Detalhes

  • Nome

    Nuno Ricardo Guimarães
  • Cluster

    Informática
  • Cargo

    Assistente de Investigação
  • Desde

    01 dezembro 2015
001
Publicações

2021

Towards a pragmatic detection of unreliable accounts on social networks

Autores
Guimarães, N; Figueira, A; Torgo, L;

Publicação
Online Social Networks and Media

Abstract

2020

Identifying journalistically relevant social media texts using human and automatic methodologies

Autores
Guimaraes, N; Miranda, F; Figueira, A;

Publicação
INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING

Abstract
Social networks have provided the means for constant connectivity and fast information dissemination. In addition, real-time posting allows a new form of citizen journalism, where users can report events from a witness perspective. Therefore, information propagates through the network at a faster pace than traditional media reports it. However, relevant information is a small percentage of all the content shared. Our goal is to develop and evaluate models that can automatically detect journalistic relevance. To do it, we need solid and reliable ground truth data with a significantly large quantity of annotated posts, so that the models can learn to detect relevance over all the spectrum. In this article, we present and confront two different methodologies: an automatic and a human approach. Results on a test data set labelled by experts' show that the models trained with automatic methodology tend to perform better in contrast to the ones trained using human annotated data.

2020

Analysis and Detection of Unreliable Users in Twitter: Two Case Studies

Autores
Guimaraes, N; Figueira, A; Torgo, L;

Publicação
Communications in Computer and Information Science - Knowledge Discovery, Knowledge Engineering and Knowledge Management

Abstract

2020

Knowledge-based Reliability Metrics for Social Media Accounts

Autores
Guimarães, N; Figueira, A; Torgo, L;

Publicação
Proceedings of the 16th International Conference on Web Information Systems and Technologies

Abstract

2019

A Brief Overview on the Strategies to Fight Back the Spread of False Information

Autores
Figueira, A; Guirnaraes, N; Torgo, L;

Publicação
JOURNAL OF WEB ENGINEERING

Abstract
The proliferation of false information on social networks is one of the hardest challenges in today's society, with implications capable of changing users perception on what is a fact or rumor. Due to its complexity, there has been an overwhelming number of contributions from the research community like the analysis of specific events where rumors are spread, analysis of the propagation of false content on the network, or machine learning algorithms to distinguish what is a fact and what is "fake news". In this paper, we identify and summarize some of the most prevalent works on the different categories studied. Finally, we also discuss the methods applied to deceive users and what are the next main challenges of this area.