Early Detection of Mental Health Disorders by Social Media Monitoring is popular PDF and ePub book, written by Fabio Crestani in 2022-09-14, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Early Detection of Mental Health Disorders by Social Media Monitoring can be Read Online from any device for your convenience.

Early Detection of Mental Health Disorders by Social Media Monitoring Book PDF Summary

eRisk stands for Early Risk Prediction on the Internet. It is concerned with the exploration of techniques for the early detection of mental health disorders which manifest in the way people write and communicate on the internet, in particular in user generated content (e.g. Facebook, Twitter, or other social media). Early detection technologies can be employed in several different areas but particularly in those related to health and safety. For instance, early alerts could be sent when the writing of a teenager starts showing increasing signs of depression, or when a social media user starts showing suicidal inclinations, or again when a potential offender starts publishing antisocial threats on a blog, forum or social network. eRisk has been the pioneer of a new interdisciplinary area of research that is potentially applicable to a wide variety of situations, problems and personal profiles. This book presents the best results of the first five years of the eRisk project which started in 2017 and developed into one of the most successful track of CLEF, the Conference and Lab of the Evaluation Forum.

Detail Book of Early Detection of Mental Health Disorders by Social Media Monitoring PDF

Early Detection of Mental Health Disorders by Social Media Monitoring
  • Author : Fabio Crestani
  • Release : 14 September 2022
  • Publisher : Springer Nature
  • ISBN : 9783031044311
  • Genre : Technology & Engineering
  • Total Page : 337 pages
  • Language : English
  • PDF File Size : 20,8 Mb

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