6th International Workshop on Mining Actionable Insights from Social Networks

Special Edition on

Healthcare Social Analytics

Topics of Interest

We solicit original, unpublished and innovative research work on all aspects of the theme of this special issue. The topics of interest include but are not limited to:

  • Social media mining for automatic health monitoring and surveillance.

  • Predicting a user's health status on social media.

  • User behavior analysis and susceptibility prediction with regard to health-related data on social media.

  • Predictive models for early detection of trends in health-related issues on Social Media.

  • Early detection of disease outbreaks

  • Explainable AI for healthcare social media analytics.

  • Ethics, bias, and fairness in analysing social media for healthcare applications.

  • Analysing health-related misinformation on social media.

  • Prescriptive countermeasure methods against formation and circulation of health-related misinformation.

  • New datasets and evaluation methodologies to help healthcare social analytics.

Submission Guidelines

Papers submitted to this special issue for possible publication must be original and must not be under consideration for publication in any other journal or conference. Previously published or accepted conference papers must contain at least 30% new material to be considered for the special issue. All papers are to be submitted through the journal editorial submission system. At the beginning of the submission process in the submission system, authors need to select "healthcare social analytics" as the article type. All manuscripts must be prepared according to the journal publication guidelines which can also be found on the website provided above. Papers will be evaluated following the journal's standard review process.

Important Dates

Submission Deadline: 1 November 2021

First Notification: 15 February 2022

Revisions Due: 1 April 2022

Issue of Publication: 2022

Guest Editors

Ebrahim Bagheri, Ryerson University

Diana Inkpen, University of Ottawa

Christopher C. Yang, Drexel University

Fattane Zarrinkalam, Thomson Reuters Labs

Daniel Dajun Zeng, Chinese Academy of Sciences