Alessandro Galeazzi

Orcid: 0000-0001-6859-0391

According to our database1, Alessandro Galeazzi authored at least 21 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Analyzing the changing landscape of the Covid-19 vaccine debate on Twitter.
Soc. Netw. Anal. Min., December, 2023

Comparing the Impact of Social Media Regulations on News Consumption.
IEEE Trans. Comput. Soc. Syst., 2023

News and Misinformation Consumption in Europe: A Longitudinal Cross-Country Perspective.
CoRR, 2023

Cross-Platform Social Dynamics: An Analysis of ChatGPT and COVID-19 Vaccine Conversations.
CoRR, 2023

Social media polarization reflects shifting political alliances in Pakistan.
CoRR, 2023

Beyond Active Engagement: The Significance of Lurkers in a Polarized Twitter Debate.
CoRR, 2023

Hurricanes Increase Climate Change Conversations on Twitter.
CoRR, 2023

Unveiling the Hidden Agenda: Biases in News Reporting and Consumption.
CoRR, 2023

The ecological rationality of decision criteria.
Synth., 2021

The echo chamber effect on social media.
Proc. Natl. Acad. Sci. USA, 2021

The COVID-19 infodemic does not affect vaccine acceptance.
CoRR, 2021

News consumption and social media regulations policy.
CoRR, 2021

Entropy and complexity unveil the landscape of memes evolution.
CoRR, 2021

Reputation-Based Spectrum Data Fusion against Falsification Attacks in Cognitive Networks.
Proceedings of the 19th Mediterranean Communication and Computer Networking Conference, 2021

Human Mobility in Response to COVID-19 in France, Italy and UK.
CoRR, 2020

Echo Chambers on Social Media: A comparative analysis.
CoRR, 2020

Evidence of economic segregation from mobility lockdown during COVID-19 epidemic.
CoRR, 2020

The COVID-19 Social Media Infodemic.
CoRR, 2020

Drifts and Shifts: Characterizing the Evolution of Users Interests on Reddit.
CoRR, 2019

The Limited Reach of Fake News on Twitter during 2019 European Elections.
CoRR, 2019

A Deep Neural Network Approach for Customized Prediction of Mobile Devices Discharging Time.
Proceedings of the 2017 IEEE Global Communications Conference, 2017