New research methods & algorithms in social network analysis

• Published in: Future generation computer systems Vol. 114; pp. 290 - 293
• Main Authors: Camacho, David, Luzón, Ma Victoria, Cambria, Erik
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2021
• Subjects: Community detection; Natural language processing; Sentiment analysis; Social media mining; Social network analysis; Community detection; Sentiment analysis; Social media mining; Natural language processing; Social network analysis
• ISSN: 0167-739X; 1872-7115
• DOI: 10.1016/j.future.2020.08.006

The exponential growth of social media and online social networks (e.g., Facebook, Twitter, Instagram, and TikTok) has changed the daily lives of millions of people. The ease to accessing, gathering and processing available data and the high societal and industrial interest in such data have attracted the interest of a large of research disciplines. This special issue has been focused mainly on Data Science and Artificial Intelligence techniques, and their application to social network analysis. The issue provides a total of 12 selected papers (out of 65) that represent latest advances and developments in these areas. •New trends and application of advanced data science and artificial intelligence techniques for knowledge extraction from social networks.•Selected papers related to the application of machine learning, soft computing, and computational intelligence to complex social media-based domains.•Current contributions and challenges in social media analysis, social network analysis, information theory, natural language processing, sentiment analysis and opinion mining, community detection, machine learning and evolutionary computation.