Challenges and Perspectives of Social Networks within Social Computing

Dear Colleagues,

Social networks allow people to connect with each other and express their thoughts, opinions and emotions, sharing content in different forms (documents, photos, videos, etc.).

This implies a pervasive use of social networks that makes available very large amounts of data on conversations, text, audio and video (i.e., multimodal data) that are significant due to their huge sizes, the variety of their topics and the dynamism of the language used.

This significant amount of data gives rise to the need of addressing both technological and social challenges. In particular, the availability of large amounts of data can be used for addressing emergent challenges (ranging from fake news to security) using different methodologies, technologies and tools related to topic areas such as human–computer interaction, social media and AI, social networks and big data, virtual reality and augmented reality environments, e-learning environments, Internet of Things, security, entertainment, video indexing and retrieval and monitoring systems, and to systems for supporting communication within crisis scenarios (public emergencies such as pandemics, wars or earthquakes).

These challenges can be addressed by applying methods and tools including machine learning, deep learning, emotion recognition, fake news detection, pattern recognition, semantic knowledge discovery, social network mining, text mining, multimedia data mining, and social and educational studies.

The purpose of this Special Issue is to discuss the role of social networks within challenges and perspectives in the different areas of application. Therefore, this Special Issue welcomes contributions of original research, advancements, developments and experiments in the following fields (not an exhaustive list):

• Machine learning and social networks analysis;
• Deep learning and social networks analysis;
• Human–computer interaction and social networks;
• Tools for augmenting social-emotional interaction;
• Fake news and social networks;
• Virtual reality and social networks;
• Augmented reality and social networks;
• Internet of Things and social networks;
• Security and social networks;
• Privacy and social networks;
• Emotion recognition and social networks;
• Social networks, emotions and social phenomena;
• Impact of social networks;
• Social interaction and social networks;
• E-learning and social networks.

Dr. Maria Chiara Caschera
Dr. Patrizia Grifoni
Dr. Fernando Ferri
Guest Editors

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• machine learning and social networks analysis
• deep learning and social networks analysis
• emotion recognition and social networks
• human–computer interaction and social network
• fake news and social networks
• virtual reality and social networks
• augmented reality and social networks
• internet of Things and social networks
• security and social networks
• privacy and social networks
• datasets for social networks analysis
• social interaction and social networks
• social impacts of social networks
• social phenomena and social networks