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Social Media Mining for Covid-19

Researchers Involved

Dr. Fabio Rinaldi

research areas

COVID-19
Health data
Social media

timeframe

2020 - 2020

Motivation and goals:

Motivation and goals:

In recent years we have witnessed a combination of an enormous amount of fake or misleading information disseminated through social media. During the current COVID-19 pandemic the problem has been particularly noticeable. Wrong and misleading information can spread extremely rapidly, potentially causing serious harm, a problem which has been termed as an infodemic. In this project, we aim to investigate methods to detect potentially damaging misinformation before it spreads.

Data:

Data:

A very large collection of tweets related to COVID-19.

Methods:

Methods:

  • Calculation of language, hashtag and domain distribution
  • LDA topic models
  • Calculation of number of posts per day/hashtag
  • Sentiment analysis by hashtag
  • Detection of mentions of paper preprints
  • Detection of mentions of drugs
  • Stance detection
  • Discovering of emerging preprints and trending drugs
  • Monitoring of the distribution of sources and topics of posts