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Giovanni Luca Ciampaglia

Biographic Data

ID310337
NAMEGiovanni Luca Ciampaglia
GIVEN NAMESGiovanni Luca
FAMILY NAMECiampaglia
SIGNATURECIAMPAGLIA G L
AFFILIATIONSUniversity of South Florida
ORCID0000-0001-5354-9257
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS12
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2022
H-INDEX2
  • Political audience diversity and news reliability in algorithmic ranking

    Open Access•Saumya Bhadani, Shun Yamaya et al.•ARTICLE•Nature Human Behaviour•2022•Cited by: 5•References: 51

  • Social influence and unfollowing accelerate the emergence of echo chambers

    Open Access•Kazutoshi Sasahara, Wen Chen et al.•ARTICLE•Journal of Computational Social…•2020•Cited by: 7•References: 31

    While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “echo chambers.” Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their…

  • Fashion informatics and the network of fashion knockoffs

    Open Access•Lauren Copeland, Giovanni Luca Ciampaglia et al.•ARTICLE•First Monday•2019

    Knowledge discovery techniques have a long history of application to fields of practice such as marketing and business intelligence. Fashion and other manufacturing compartments have comparably enjoyed little attention from computer scientists. With the increasing availability of multimedia data from the Web and social media, our understanding of the fashion apparel industry could be significantly enhanced through the use of knowledge discovery m…

  • Social influence and unfollowing accelerate the emergence of echo chambers

    Open Access•Kazutoshi Sasahara, Wen Chen et al.•ARTICLE•Journal of Computational Social…•2020•Cited by: 7•References: 31

    While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “echo chambers.” Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their…

  • Political audience diversity and news reliability in algorithmic ranking

    Open Access•Saumya Bhadani, Shun Yamaya et al.•ARTICLE•Nature Human Behaviour•2022•Cited by: 5•References: 51

  • Fashion informatics and the network of fashion knockoffs

    Open Access•Lauren Copeland, Giovanni Luca Ciampaglia et al.•ARTICLE•First Monday•2019

    Knowledge discovery techniques have a long history of application to fields of practice such as marketing and business intelligence. Fashion and other manufacturing compartments have comparably enjoyed little attention from computer scientists. With the increasing availability of multimedia data from the Web and social media, our understanding of the fashion apparel industry could be significantly enhanced through the use of knowledge discovery m…

  • Social influence and unfollowing accelerate the emergence of echo chambers

    Open Access•Kazutoshi Sasahara, Wen Chen et al.•ARTICLE•Journal of Computational Social…•2020•Cited by: 7•References: 31

    While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “echo chambers.” Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their…

  • Political audience diversity and news reliability in algorithmic ranking

    Open Access•Saumya Bhadani, Shun Yamaya et al.•ARTICLE•Nature Human Behaviour•2022•Cited by: 5•References: 51

Computer Science (2 works) · Data science (2 works) · Misinformation and Its Impacts (2 works) · Opinion Dynamics and Social Influence (2 works) · Political science (2 works) · Social media (2 works) · Clothing (1 works) · Consumer Behavior in Brand Consumption and Identification (1 works) · Diversity (politics (1 works) · Dynamics (music (1 works)

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