Social media data analysis:

Fake news, conspiracy theories vs. critical thinking; hate speech, sexisim, misogyny, stereotypes and prejudice; irony, sarcasm and hurtful humour; stance detection; and mental health disorders.

  • Fake news and conspiracy theories
    Given a text, does it contain false information? Is it part of a disinformation campaign? Does it support a conspiracy theory? The focus is on detecting disinformation in social media texts and to analyse oppositional thinking to discriminate between conspiracy narratives and critical thinking.
  • Hate speech, sexism and misogyny
    Given a text, does it contain hate speech? The focus is to detect offensive language and hate speech in social media texts, also when the toxic language is conveyed in an implicit way via the usage of stereotypes or prejudice, and also figurative language (irony, sarcasm and hurtful humour). Special importance has been given to targets such as women (sexism and misogyny), immigrants (racism and xenophobia), LGBTIQ community, and overweight people.
  • Mental health disorders
    Given a text, does it contain any signal of anxiety or mental disorder in general? The focus is to early detect menatl disorders such as depression or anorexia from social media texts, analysisng also images and videos that people share in social media.
  • Author profiling
    Given a text, what are the author’s traits? The focus is on inferring traits such as gender, age, native language, language variety, and personality on the basis of the stylistic analysis of the author’s texts. This is of interest for areas such as marketing, forensics or security.
  • Stance detection
    Given a particular controversial topic, is the author’s opinion in favour or against? The focus is on monitoring sentiment in political debates on controversial topics (e.g. climate change)to understand the way polarized communities communicate.
  • Irony detection and sentiment analysis
    Given an opinion, is the author’s ironic? The focus is on understanding the opinion’s polarity in case forms of figurative language such as irony or sarcasm are used. This is of interest for areas such as marketing and online reputation..