Riccardo Cantini

Biographic Data

ID1854508
NAMERiccardo Cantini
GIVEN NAMESRiccardo
FAMILY NAMECantini
SIGNATURECANTINI R
AFFILIATIONSUniversity of Calabria
ORCID0000-0003-3053-6132
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0

  • 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…

  • 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…