Every day, online communities create massive amounts of data worldwide. One popular use of social networks is to provide a timely and cost-effective option for reflecting real-world occurrences. Users of social networks can transmit information in a dynamic, seamless way practically anywhere and anytime. Social computing, a branch of computer science concerned with the intersection of social behavior and computational systems, arose as a result of the advent of social network technologies and platforms. Social computing applications are fundamentally linked to those that harness social network users' behaviors, ideas, and emotions, such as stock price prediction, promoting items or advertisements, extracting users' opinions to enhance product development processes, analyzing political information, and so on.

Social good can be described as anything that helps the most people in the most significant way imaginable. While applications of knowledge extracted from social networks are vast, only a small set are devoted to doing good for society. For example, real-time analysis of Twitter data has been used to model earthquake warning detection systems, identify medical and emergency needs during recovery from natural disasters (such as the Haiti Earthquake), detect the spread of influenza-like illness, and discover abusive behaviors in social networks. Furthermore, many studies have investigated the use of social media to monitor real-world population-wide and individual health, such as drinking problems, epidemics, drug abuse, and mental illness. With the recent outbreak of COVID-19, many studies showed that social media could be used to monitor depression and public discourses during the pandemic. This research topic invites manuscripts that address intelligent applications and computational techniques related to utilizing social networks or social media data for social good. Survey and review papers addressing the relevant issues are also welcome.

Topics of interest include, but are not limited to:
- Intelligent applications of social computing in public health, sustainability, environment, equality, justice, education, cultural heritage, peace, economics, public welfare, etc
- Mining social media data for policy development, smart government, and Sustainable Development Goals (SDG)
- Investigating fraud, collusion, corruption, and criminal activities using social networks
- Innovative and intelligent computational technologies, such as artificial intelligence, natural language processing (NLP), deep learning, computer vision, graph mining techniques, etc., that facilitate utilizing social media data for social good
- Resource construction from social media data that enables social good applications

This research topic strongly emphasizes both the computational and real-world impact aspects of social computing for social good applications. Submitted manuscripts should clearly define research questions and novel contributions as well as present rigorous empirical studies and evaluations of the proposed methodologies. Furthermore, societal implications and relevant ethical issues should also be discussed. Ethical issues may involve privacy concerns regarding data collection, storage, and processing of social media data and reproducibility of the research.
Every submission through the Data Analytics and Social Impact section must have a clear, strong, and demonstrated social impact and discussions of ethical choices and values as well a discussion of the human impact of the work.


Keywords: Social Computing, Social Good, Social Network Analytics, Social Media Mining, Artificial Intelligence, Machine Learning