Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Diogo Pacheco"'
Autor:
Bibandhan Poudyal, Diogo Pacheco, Marcos Oliveira, Zexun Chen, Hugo S. Barbosa, Ronaldo Menezes, Gourab Ghoshal
Publikováno v:
Royal Society Open Science, Vol 11, Iss 9 (2024)
Human travelling behaviours are markedly regular, to a large extent predictable, and mostly driven by biological necessities and social constructs. Not surprisingly, such predictability is influenced by an array of factors ranging in scale from indiv
Externí odkaz:
https://doaj.org/article/665ef478642d4893a64edae30e380573
Publikováno v:
PLoS ONE, Vol 19, Iss 5, p e0302201 (2024)
The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportionate amount of low-credibility content-so-called superspreaders-are at t
Externí odkaz:
https://doaj.org/article/9beff4b963724d039ad723f4e83e8f16
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Social media platforms moderating misinformation have been accused of political bias. Here, the authors use neutral social bots to show that, while there is no strong evidence for such a bias, the content to which Twitter users are exposed depends st
Externí odkaz:
https://doaj.org/article/8e1dad961559419599c3fff50e7f2abf
Autor:
John Bollenbacher, Diogo Pacheco, Pik-Mai Hui, Yong-Yeol Ahn, Alessandro Flammini, Filippo Menczer
Publikováno v:
Applied Network Science, Vol 6, Iss 1, Pp 1-21 (2021)
Abstract To what extent can we predict the structure of online conversation trees? We present a generative model to predict the size and evolution of threaded conversations on social media by combining machine learning algorithms. The model is evalua
Externí odkaz:
https://doaj.org/article/3569e8dfde274cbab9e9cfa3b32cb3ae
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/c8ac109f8fce46b9bcb779b9c1584900
Publikováno v:
Innovations in Bio-Inspired Computing and Applications ISBN: 9783031274985
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fa0166eb357bb452242e70391e5d767
https://doi.org/10.1007/978-3-031-27499-2_80
https://doi.org/10.1007/978-3-031-27499-2_80
Publikováno v:
Complex Networks XIV ISBN: 9783031282751
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::215ed9de6cb709a41a9b8de824e94b92
https://doi.org/10.1007/978-3-031-28276-8_12
https://doi.org/10.1007/978-3-031-28276-8_12
Publikováno v:
Cadernos da Escola do Legislativo. 24:81-120
Autor:
Alessandro Flammini, John Bollenbacher, Pik-Mai Hui, Diogo Pacheco, Filippo Menczer, Yong-Yeol Ahn
Publikováno v:
Applied Network Science, Vol 6, Iss 1, Pp 1-21 (2021)
To what extent can we predict the structure of online conversation trees? We present a generative model to predict the size and evolution of threaded conversations on social media by combining machine learning algorithms. The model is evaluated using
Publikováno v:
Cadernos do IME - Série Matemática. :65-68
Objetivando fornecer um melhor entendimento na construção do raciocínio sistêmico de resolução de problemas em geometria, compartilhamos algumas experiências oriundas do esforço empregado na busca de soluções para problemas desafiadores, be