Where in the World

Which countries are tweeting about COVID-19 vaccines?

not present
infrequent
very frequent

This map shows from which countries people are tweeting about COVID-19 vaccines. The project is currently analyzing only tweets written in English, so it is normal that more English-speaking states are highlighted. Darker colours mean a higher concentration of tweets.


This Week in Hashtags

What were the most tweeted hashtags in the last 7 days?

Here is a glance at the hottest hashtags when it comes to tweets about COVID-19 vaccines. The larger and darker the rectangle is, the more the hashtag was tweeted.

Most shared Web Pages and Websites

What sources of information have people used in the last week?

What are the sources from which people get their information? This is an issue that in recent years has reached high importance given the significant increase in fake news and misleading information.

Here we highlight the most popular URLs shared in the last week by tweets mentioning COVID-19 vaccines.

Through a constantly updated classification we can monitor the domains that have been tweeted the most, which are the websites from which the users recover information about the vaccines.


Symptom Discussed by the Users

What possible symptoms are being discussed?

What symptoms or medical terms are mentioned when people tweet about COVID-19 vaccines? This Word Cloud shows what the people of Twitter have focused since we started monitoring it.

The algorithm that this module is based on has been developed by the same research group and has been recently published in two of the most important conferences in the field of Artificial Intelligence and Natural Language Processing: EACL 2021 and W3PHIAI (Best Short Paper - sponsored by IBM), workshop co-located with AAAI 2021.

Click on a concept to explore related tweets or filter the words by vaccine.

Please select at least one vaccine to visualize the data
Filter words by vaccine

Most frequent concepts per vaccine

Discover which side-effects were mentioned more frequently for every vaccine.

The code for the algorithm and the processed data are available for research purposes.

Contact us at: nlp4ade@gmail.com


Team

Project Developers

Beatrice Portelli
Beatrice Portelli

Graduate Research Fellow @ University of Udine

Adverse Drug Reaction Extraction NLP Machine Learning Fake news detection
Roberto Tonino
Roberto Tonino

Master Degree Student @ University of Udine

Web Development Web Design
Edoardo Lenzi
Edoardo Lenzi

Master Degree Student @ University of Udine

Adverse Drug Reaction Extraction NLP
Simone Scaboro
Simone Scaboro

Master Degree Student @ University of Udine

Adverse Drug Reaction Extraction NLP
Gabriele Dominici
Gabriele Dominici

Bachelor Degree Student @ University of Udine

Machine Learning Deep Learning

Lead Board

Giuseppe Serra
Giuseppe Serra

Associate Professor, Co-lead of the Artificial Intelligence Laboratory @ University of Udine

Machine Learnig Deep Learning
Enrico Santus
Enrico Santus

AI Advisor @ Women’s Brain Project (WBP)

Computational Linguistics NLP
Emmanuele Chersoni
Emmanuele Chersoni

Postdoctoral Researcher @ Hong Kong Polytechnic University

Computational Linguistics NLP

Advisory Board

Nicola Marino
Nicola Marino

Co-Founder @ INTECH Innovative Training Technologies

Health Innovation Advisor
Simone Bianco
Simone Bianco

Research Staff Member and Manager @ IBM Almaden Research Center

Health Innovation Advisor
Carlo Tasso
Carlo Tasso

Full Professor, Co-lead of the Artificial Intelligence Laboratory @ University of Udine

AI Advisor

Disclaimer

The information in this website is obtained from Twitter and automatically processed by machine learning algorithms, without any human verification or fact-checking.

The utilized algorithm is described in this paper. By no means the visualized information should be intended as trustable for any scope.