Call For Papers
The 6th International Workshop on Mining Actionable Insights from Social Networks (MAISoN 2021)
Special Edition on Healthcare Social Analytics
@15th International AAAI Conference on Web and Social Media (ICWSM-2021)
Jun 7, 2021
Workshop website: https://www.maisonworkshop.org/
- Submission deadline: March 27, 2021
- Acceptance notification: April 10, 2021
With the emergence and growing popularity of social media such as blogging systems, wikis, social bookmarking, social networks and microblogging services, many users are extensively engaged in at least some of these applications to express their feelings and views about a wide variety of social topics as they happen in real time by commenting, tagging, joining, sharing, liking, and publishing posts. According to Statista, there were an estimated 2.65 billion people using social media in 2018, a number projected to increase to almost 3.1 billion in 2021. This has resulted in an ocean of data which presents an interesting opportunity for performing data mining and knowledge discovery in many domains including healthcare. The recent highly impressive advances in machine learning and natural language processing present exciting opportunities for developing automatic methods for the collection, extraction, representation, analysis, and validation of social media data for health applications. These methods should be able to simultaneously address the unique challenges of processing social media data and timely discover meaningful patterns identifying emerging health threats.
In this workshop, we invite researchers and practitioners from different disciplines such as computer science, big data mining, machine learning, social media analysis and other related areas to share their ideas and research achievements in order to deliver technology and solutions for healthcare social analytics.
Topics of interest include, but are not limited to:
- Social media mining for automatic health monitoring and surveillance
- Predicting 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
We invite the submission of regular research papers (4-6 pages) as well as position papers (2-4 pages). We recommend papers to be formatted according to the AAAI two-column, camera-ready style. No source files (Word or LaTeX) are required at the time of submission for review; only the PDF file is permitted. All papers will be peer reviewed.
All submissions must be submitted in PDF format according to the guidelines through the Easychair installation: https://easychair.org/my/conference?conf=maison2021.
Ebrahim Bagheri, Ryerson University, firstname.lastname@example.org
Diana Inkpen, University of Ottawa, email@example.com
Christopher C. Yang, Drexel University, firstname.lastname@example.org
Fattane Zarrinkalam, Thomson Reuters Centre for AI and Cognitive Computing, email@example.com