EAI International Conference on Social Data and Artificial Intelligence (SDAI 2019)

August 7-9, 2019 , Minneapolis, United States

Scope & Topics

Social Data and Artificial Intelligence: One of the themes of this conference is to analyze and formulate new perspective of social theories and develop computational algorithms using large scale data sets. The research articles should incorporate different computational algorithms and data analysis techniques to address the problem of inconsistencies, inaccuracies and inadequacies of social data for policy making. The use of advanced artificial intelligence algorithms and technologies is encouraged.

Social Media Data Analysis in Healthcare: Research suggests that more and more people rely on online sources for health information including symptoms, treatments and general health-related advice. Moreover, the user behaviour currently active on social media demonstrates an openness to share facts related to their current health status. Such data could be used to provide real-time tracking and prediction of the spread of disease and other health concerns, or provide vital information about the effectiveness of the public health awareness strategies of health agencies such as Health Canada, the Centre for Disease Control (CDC) or the World Health Organization (WHO). However, the current understanding of online health data produced through social networks is limited in important ways: (a) existing databases are project specific and data gathering mechanisms are time-constrained; (b) existing health-tracking tools depend on single interfaces such as Facebook, Twitter or Instagram, and (c) there is a lack of capacity for real-time mapping of health care issues.

Topics of Interest :

• Social Data inadequacies and inconsistencies
  
• Predictive models of social behaviours
  
• Infrastructure and architecture for testing social theories
  
• Data collection and analysis platforms
  
• Relevance of IoT for social science theories
  
• Building capacity to continuously collect data across a range of social media networks
  
• Designing efficient parsers to deal with noisy social media datasets for real-time tracking of health issues, diseases and wellness
  
• Designing tools to map and measure the effectiveness of health campaigns by healthcare organizations
  
• Cross-validating the predictive models of social media datasets with ground truth data
  
• Developing frameworks and algorithms to perform real-time analysis of social media datasets
  

Important Dates

Submission Deadline	:	March 15, 2019
Authors Notification	:	May 15, 2019
Final Manuscript Due	:	July 01, 2019

 

User Name : austin
Posted 20-12-2018 on 16:15:51 AEDT

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