LEADER 04046nam 22005775 450 001 9911048822603321 005 20251225180442.0 010 $a3-032-13509-5 024 7 $a10.1007/978-3-032-13509-4 035 $a(CKB)44551406600041 035 $a(MiAaPQ)EBC32466423 035 $a(Au-PeEL)EBL32466423 035 $a(DE-He213)978-3-032-13509-4 035 $a(EXLCZ)9944551406600041 100 $a20251222d2026 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Social Networks Analysis and Mining $eProceedings of the 17th International Conference on Advances in Social Networks Analysis and Mining - ASONAM 2025 /$fedited by Panagiotis Karampelas, Min-Yuh Day, I-Hsien Ting, Reda Alhajj 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (661 pages) 225 1 $aLecture Notes in Social Networks,$x2190-5436 311 08$a3-032-13508-7 327 $aTargets of Terrorgram: The Who, What, and Where of Threatening Communication on Terrorgram -- Cross-Subreddit Behavior as Open-Source Indicators of Coordinated Influence: A Case Study of r/Sino & r/China -- When Words Become Warnings: Assessing Threats in Online Spaces -- Modelling effects of social network topology on opinion dynamics during the COVID-19 pandemic -- Explainable Data-Driven Digital Twin for Stress Management -- Exploring Gender-Specific Symptoms in Coronary Heart Disease Diagnosis -- Enhancing Explainability in Knowledge Graph Construction for Healthcare Services Using Large Language Models -- Fuzzy Consensus Clustering for Deep Learning Tuning by using Medical Diagnosis as a case -- Mislabeling Misinformation: Annotation Consistency Shapes Machine Learning for DIY Health Risks -- On the Use of 3D Modeling, Reconstruction and Printing Techniques for the Development of an Ankle Bone Prosthesis -- Therapist by Chance: Investigating ChatGPT?s Emotional and Mental Health Support via Sentiment Analysis on Social Networks. 330 $aThis book explores the evolution of social network analysis and mining (SNAM), a field that originated in social and business communities but has expanded significantly in recent years. The rise of online social platforms, email logs, phone records, and instant messaging systems has driven the development of advanced techniques for analyzing social networks, drawing heavily on graph theory and machine learning. As the Web increasingly becomes a social medium, it fosters human interaction, the sharing of experiences and knowledge, and the formation and evolution of communities. This transformation has amplified the importance of SNAM in fields such as academia, politics, homeland security, and business, where understanding the complex relationships between networked actors is crucial. This book presents a comprehensive collection of cutting-edge research and developments in SNAM, offering a valuable resource for researchers and practitioners seeking to deepen their understanding of social networks and their applications. 410 0$aLecture Notes in Social Networks,$x2190-5436 606 $aApplication software 606 $aQuantitative research 606 $aMachine learning 606 $aComputer and Information Systems Applications 606 $aData Analysis and Big Data 606 $aMachine Learning 615 0$aApplication software. 615 0$aQuantitative research. 615 0$aMachine learning. 615 14$aComputer and Information Systems Applications. 615 24$aData Analysis and Big Data. 615 24$aMachine Learning. 676 $a005.3 700 $aKarampelas$b Panagiotis$01058500 701 $aKarampelas$01884836 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911048822603321 996 $aAdvances in Social Networks Analysis and Mining$94519532 997 $aUNINA