Marco Viviani

Associate Professor

University of Milano-Bicocca

Italy

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About

Marco Viviani is an Associate Professor at Università degli Studi di Milano-Bicocca, Italy. His research areas include blockchain technology, health misinformation detection, and social media engagement analysis, as reflected in his recent publications. He has contributed to studies on MEV strategies in Ethereum, long document classification, and the dynamics of online health communities.

Articles (12)

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2025

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2025

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2025

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2024

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2024

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2023

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2022

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2022

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2021

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2021

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2021

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2020

Collaborators (5)

Davide Mancino

University of Milano-Bicocca

ITALY

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Andrea Michienzi

Junior Assistant Professor

University of Pisa

ITALY

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Xiancheng LI

Queen Mary University of London

UNITED KINGDOM

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Alberto Leporati

Associate Professor

University of Milano-Bicocca

ITALY

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Federico Pianzola

Assistant Professor

University of Groningen

NETHERLANDS

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Marco Viviani

Research Interests

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About

Articles (12)

Striking the Balance: Evaluating Content Quality and Reward Dynamics in Blockchain Online Social Media

Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning–Based Sentiment Analysis

Long Document Classification in the Transformer Era: A Survey on Challenges, Advances, and Open Issues

A Role and Reward Analysis in Off-chain Mechanisms for Executing MEV Strategies in Ethereum Proof-of-Stake

Comparing Echo Chamber Detection Metrics: A Cross-modeling and Cross-platform Analysis of Twitter and Reddit

Vec4Cred: a model for health misinformation detection in web pages

Readers' engagement through digital social reading on Twitter: the TwLetteratura case study

Health Misinformation Detection in the Social Web: An Overview and a Data Science Approach

Assessing vulnerability to psychological distress during the COVID-19 pandemic through the analysis of microblogging content

Echo chamber detection and analysis

Surveilling COVID-19 Emotional Contagion on Twitter by Sentiment Analysis

Detecting Binge Drinking and Alcohol-Related Risky Behaviours from Twitter’s Users: An Exploratory Content- and Topology-Based Analysis

Collaborators (5)

Davide Mancino

Andrea Michienzi

Xiancheng LI

Alberto Leporati

Federico Pianzola

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