Social media has become the most important platform for interaction and information among people and for society. Although it supports social good through applications such as disaster relief coordination and health promotion, the misuse of these platforms for social harm has been rampant in recent years. In the pursuit of gaining a better understanding of online human behavior, research in social media analytics has seen significant development of advanced techniques. On the other hand, by the complex nature of the social media, and other large-scale socio-technical infrastructures, it has been challenging to detect, monitor, overcome, and counter the malevolent behavior by ill-intentioned actors. This becomes even more dangerous if it is orchestrated by malicious groups or state actors, threatening our society at large. Major problems of our society amplified by social media platforms include, but not limited to, hate speech, radicalization, harassment, cyberbullying, fake news, human trafficking, drug dealing, and gender-based stereotyping and violence with significant implications on the well-being of individuals as well as communities. These trends have led to a rising prominence of social media analytics in academia, politics, and homeland security, using computational techniques from natural language processing, statistics, network science, data mining, machine learning, computational linguistics, human-computer interaction, and cognitive science.
This special issue welcomes theoretical, analytical, and empirical contributions using any kind of research method, including experiments, primary data from social media logs, case studies, simulations, surveys, and so on. Submissions are encouraged to examine the nature of both harmful and social good intentional behaviors on social media towards understanding, detecting, and monitoring good communication while countering harmful communication, by employing computational social media analytics techniques. The target audience for this special issue will consist of researchers, practitioners, and graduate students from various disciplines, including (but not limited to) behavioral science, computer and information sciences, psychology, sociology, political science, cognitive science, cultural study, information systems, terrorism and counter-terrorism, operations research, and communication.
Through this special issue, we aim to bring together researchers and practitioners from different disciplines, to share, exchange, learn, and develop preliminary results, new concepts, ideas, principles, and methodologies on social, cultural, emotional, communicative, and linguistic aspects of harmful communications and their content on social media.
Read more about IEEE Internet Computing magazine here: https://www.computer.org/csdl/magazine/ic.
Topics include, but are not limited to:
- Misinformation, disinformation, fake news (e.g., during elections, epidemics, and disasters, as well as regarding health topics like vaccines), and spreading deep fakes
- Online extremism
- Harassment and cyberbullying
- Hate speech
- Gender-based violence
- Human trafficking
- Illicit drug trafficking
- Mental health implications of social media
- Validity of social media in smart health and well-being
- Ethical and privacy-preserving social media analytics
- Emotional and psychological support
- Trust relationship and community dynamics
- Relationship of social web and mainstream news media
- Cultural implications of social web usage
- Social good campaigns and movements
- Influencer identification and community detection for movements
- Paper submissions due: CLOSED
- First-round reviews due: July 8, 2020
- Revisions due: August 12, 2020
- Final decision notification: September 16, 2020
- Camera-ready submissions due: September 30, 2020
- Publication: November/December 2020
All submissions must be original manuscripts of fewer than 5,000 words, focused on the topics of the special issue. All manuscripts are subject to peer review on both technical merit and relevance to IEEE Internet Computing’s international readership–primarily practicing engineers and academics who are looking for material that introduces new technology and broadens familiarity with current topics. We do not accept white papers, and papers that are primarily theoretical or mathematical must clearly relate the mathematical content to a real-life or engineering application. To submit a manuscript, create or access an account on ScholarOne. All submissions must comply with IEEE Internet Computing’s submission guidelines and will be reviewed by research peers.
Contact the guest editors at email@example.com.
Nitin Agarwal, University of Arkansas, USA
Ugur Kursuncu, AI Institute, University of South Carolina, USA
Hemant Purohit, George Mason University, USA
Amit Sheth, AI Institute, University of South Carolina, USA