Fabrizio Marozzo

Biographic Data

ID1757694
NAMEFabrizio Marozzo
GIVEN NAMESFabrizio
FAMILY NAMEMarozzo
SIGNATUREMAROZZO F
AFFILIATIONSUniversity of Calabria
ORCID0000-0001-7887-1314
VERIFIEDYes
TOTAL WORKS7
TOTAL CITATIONS13
WORKS AS AUTHOR7
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2026
H-INDEX1

  • Dynamic Hashtag Recommendation in Social Media With Trend Shift Detection and Adaptation

    Open AccessRiccardo Cantini, Fabrizio Marozzo et al.ARTICLEIEEE Transactions on Computational…2026

    Hashtag recommendation systems have emerged as a key tool for automatically suggesting relevant hashtags and enhancing content categorization and search. However, existing static models struggle to adapt to the highly dynamic nature of social media conversations, where new hashtags constantly emerge and existing ones undergo semantic shifts. To address these challenges, this article introduces hashtag recommendation by detecting and adapting to t…

  • Harnessing prompt-based large language models for disaster monitoring and automated reporting from social media feedback

    Open AccessRiccardo Cantini, Cristian Cosentino et al.ARTICLEOnline Social Networks and Media2025

    In recent years, social media has emerged as one of the main platforms for real-time reporting of issues during disasters and catastrophic events. While great strides have been made in collecting such information, there remains an urgent need to improve user reports’ automation, aggregation, and organization to streamline various tasks, including rescue operations, resource allocation , and communication with the press. This paper introduces an i…

  • Detecting mental disorder on social media

    Open AccessLoris Belcastro, Riccardo Cantini et al.ARTICLEOnline Social Networks and Media2025

    In the digital era, the prevalence of depressive symptoms expressed on social media has raised serious concerns, necessitating advanced methodologies for timely detection. This paper addresses the challenge of interpretable depression detection by proposing a novel methodology that effectively combines Large Language Models (LLMs) with eXplainable Artificial Intelligence (XAI) and conversational agents like ChatGPT. In our methodology, explanatio…

  • Multistakeholder Disaster Insights From Social Media Using Large Language Models

    Open AccessLoris Belcastro, Cristian Cosentino et al.ARTICLEIEEE Transactions on Computational…2025

    In recent years, social media has emerged as a primary channel for users to promptly share feedback and issues during disasters and emergencies, playing a key role in crisis management. While significant progress has been made in collecting and analyzing social media content, there remains a pressing need to enhance the automation, aggregation, and customization of this data to deliver actionable insights tailored to diverse stakeholders, includi…

  • Analyzing voter behavior on social media during the 2020 US presidential election campaign

    Open AccessLoris Belcastro, Francesco Branda et al.ARTICLESocial Network Analysis and Mining2022References: 40

    Every day millions of people use social media platforms by generating a very large amount of opinion-rich data, which can be exploited to extract valuable information about human dynamics and behaviors. In this context, the present manuscript provides a precise view of the 2020 US presidential election by jointly applying topic discovery, opinion mining, and emotion analysis techniques on social media data. In particular, we exploited a clusterin…

  • ParSoDA

    Open AccessLoris Belcastro, Fabrizio Marozzo et al.ARTICLESocial Network Analysis and Mining2019

  • Analyzing polarization of social media users and news sites during political campaigns

    Open AccessFabrizio Marozzo, Alessandro BessiARTICLESocial Network Analysis and Mining2018Cited by: 13References: 29