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Letizia Milli

Biographic Data

ID4974342
NAMELetizia Milli
GIVEN NAMESLetizia
FAMILY NAMEMilli
SIGNATUREMILLI L
AFFILIATIONSUniversity of Pisa
ORCID0000-0001-5283-0477
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS1
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2022
H-INDEX1
  • Modeling algorithmic bias

    Open Access•Valentina Pansanella, Giulia Rossetti et al.•ARTICLE•Applied Network Science•2022•Cited by: 1•References: 21

    Every day, people inform themselves and create their opinions on social networks. Although these platforms have promoted the access and dissemination of information, they may expose readers to manipulative, biased, and disinformative content—co-causes of polarization/radicalization. Moreover, recommendation algorithms, intended initially to enhance platform usage, are likely to augment such phenomena, generating the so-called Algorithmic Bias . I…

  • Opinion Dynamic Modeling of News Perception

    Open Access•Letizia Milli•ARTICLE•Applied Network Science•2021

    During the last decade, the advent of the Web and online social networks rapidly changed the way we were used to search, gather and discuss information of any kind. These tools have given everyone the chance to become a news medium. While promoting more democratic access to information, direct and unfiltered communication channels may increase our chances to confront malicious/misleading behavior. Fake news diffusion represents one of the most pr…

  • Active and passive diffusion processes in complex networks

    Open Access•Letizia Milli, Giulia Rossetti et al.•ARTICLE•Applied Network Science•2018•References: 11

    Ideas, information, viruses: all of them, with their mechanisms, spread over the complex social information, viruses: all tissues described by our interpersonal relations. Usually, to simulate and understand the unfolding of such complex phenomena are used general mathematical models; these models act agnostically from the object of which they simulate the diffusion, thus considering spreading of virus, ideas and innovations alike. Indeed, such d…

  • Modeling algorithmic bias

    Open Access•Valentina Pansanella, Giulia Rossetti et al.•ARTICLE•Applied Network Science•2022•Cited by: 1•References: 21

    Every day, people inform themselves and create their opinions on social networks. Although these platforms have promoted the access and dissemination of information, they may expose readers to manipulative, biased, and disinformative content—co-causes of polarization/radicalization. Moreover, recommendation algorithms, intended initially to enhance platform usage, are likely to augment such phenomena, generating the so-called Algorithmic Bias . I…

  • Active and passive diffusion processes in complex networks

    Open Access•Letizia Milli, Giulia Rossetti et al.•ARTICLE•Applied Network Science•2018•References: 11

    Ideas, information, viruses: all of them, with their mechanisms, spread over the complex social information, viruses: all tissues described by our interpersonal relations. Usually, to simulate and understand the unfolding of such complex phenomena are used general mathematical models; these models act agnostically from the object of which they simulate the diffusion, thus considering spreading of virus, ideas and innovations alike. Indeed, such d…

  • Opinion Dynamic Modeling of News Perception

    Open Access•Letizia Milli•ARTICLE•Applied Network Science•2021

    During the last decade, the advent of the Web and online social networks rapidly changed the way we were used to search, gather and discuss information of any kind. These tools have given everyone the chance to become a news medium. While promoting more democratic access to information, direct and unfiltered communication channels may increase our chances to confront malicious/misleading behavior. Fake news diffusion represents one of the most pr…

  • Modeling algorithmic bias

    Open Access•Valentina Pansanella, Giulia Rossetti et al.•ARTICLE•Applied Network Science•2022•Cited by: 1•References: 21

    Every day, people inform themselves and create their opinions on social networks. Although these platforms have promoted the access and dissemination of information, they may expose readers to manipulative, biased, and disinformative content—co-causes of polarization/radicalization. Moreover, recommendation algorithms, intended initially to enhance platform usage, are likely to augment such phenomena, generating the so-called Algorithmic Bias . I…

Complex Network Analysis Techniques (3 works) · Computer Science (3 works) · Data science (3 works) · Opinion Dynamics and Social Influence (3 works) · Epistemology (2 works) · Misinformation and Its Impacts (2 works) · Social media (2 works) · Theoretical Computer Science (2 works) · World Wide Web (2 works) · Abstraction (1 work)

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