Advances in Social Networks Analysis and Mining Proceedings of the 16th International Conference on Advances in Social Networks Analysis and Mining - ASONAM 2024 Volume 2 /
This 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 devel...
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| Format: | Electronic eBook |
| Language: | English |
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Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edition: | 1st ed. 2025. |
| Series: | Lecture Notes in Social Networks,
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| Online Access: | https://doi.org/10.1007/978-3-031-85386-9 |
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| 245 | 1 | 0 | |a Advances in Social Networks Analysis and Mining |h [electronic resource] : |b Proceedings of the 16th International Conference on Advances in Social Networks Analysis and Mining - ASONAM 2024 Volume 2 / |c edited by I-Hsien Ting, Reda Alhajj, Panagiotis Karampelas, Min-Yuh Day. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a 1 online resource (XVI, 433 p. 122 illus.). |b 104 illus. in color. | ||
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| 490 | 1 | |a Lecture Notes in Social Networks, |x 2190-5436 | |
| 505 | 0 | |a Data Veracity Analysis in Social Medias – A review -- Route Recommendation for Healthcare by Reducing Approach Bias as a Food Desire -- Visual and Textual Analysis of the Online Anti-Feminicide Movement in Mexico: A Narrative Network Approach -- Using Social Network Analysis to Analyze Eye-tracking Behavior Data in the Area of Education Science -- Empirical study of the Sardex network -- A Novel Network Dataset Based on Football Players' Co-Appearances -- Predicting the Role of Temozolomide Drug in Glioma By integrating Available Genomic Databases and Computational Methods -- A Measure of the Robustness of Clusters in a Network with No Ground Truth - A Chronic Lower Back Pain Case Study -- Smart Human Resource Management System -- Searching Temporal Knowledge Graphs to Understand The Impacts of Disasters -- Multi-agent Analytics-Driven Content Discovery: A Narrative Contagion Approach -- Navigating the Anomalies: A Comprehensive Analysis of YouTube Channel Behavior -- ISAC: An Interactive Hierarchical Interface for Efficient Structural Analysis and Vertex Search in Complex Networks -- Russian Invaders on the Internet’s Front Page – A Survey of Behaviors in Ukraine-Related Subreddits -- Echoes of War: How Reddit Narratives Shape Sectarian Views of the Israel-Hamas War -- CantastorIA: Enhancing Audiobook Engagement through Adaptive Soundtracks and Voice Cloning -- Detecting Jailbreaking Prompts: an Anti-Persuation Filter Framework -- Geo-Localization Using Multimodal Large Language Models -- Popping the Social Bubble: Using AI to Increase Transparency in Harmful Content Moderation -- Beyond the Click: How YouTube Thumbnails Shape User Interaction and Algorithmic Recommendations -- A multi-aspect analysis of echo chambers on video-sharing social media -- Bangla Emotion Detection Dataset With An Extended Taxonomy And Its Evaluation -- Homophily Detection in Opinion Dynamics from Reddit Discussions -- Smile for the Camera, Act Green: Corporate Social Media's Deceptive Sustainability Charade -- SocialRec: User Activity Based Post Weighted Dynamic Personalized Post Recommendation System in Social Media -- FLASH: Federated Learning-Based LLMs for Advanced Query Processing in Social Networks through RAG -- Investigating Gender Bias in StackOverflow with LLMs. 4WHContext: A Context Based Hate Speech Detection Framework From Social Media Posts -- Measuring the Sociolinguistic Patterns of Climate Debate Polarization in the Facebook Context -- Detecting and Measuring Anomalous Behaviors on YouTube -- Beyond Likes: Enhancing Social Media Engagement Metrics -- Claim Verification Leveraging In-Context Learning and Retrieval Augmented Generation -- Deepfake Media Forensics: State of the Art and Challenges Ahead -- A Router-based Parental Control Tool for Safe Social Network Usage -- Bipartite Graph Modeling for the Analysis of Fake News Propagation -- Mining Likes and Transactions per User for Cross-Domain Product Recommendation in Social Network and E-Commerce -- Towards Systemic Risk Evaluation, Attribution, and Mitigation in Networked Systems: Work in Progress -- On Understanding the Dark Web through Graph Analytics -- A Deep Neural Framework for Fault Detection in IoT-based Sensor Networks -- Combining Knowledge graph and LLM to extract thesaural relationship and concepts on Cybersecurity -- A Thesaurus for the Cybersecurity domain to specialized knowledge management and indexing operations -- Sentiment Analysis for Early Warnings and Disaster Management: a Survey -- Community Detection in Complex Networks exploiting Spectral Graph Sparsification for Efficient Disaster Response -- HalpernSGD: Enhancing Neural Network Efficiency and Sustainability, Exploiting Halpern-Inspired Optimization [Extended Abstract] -- Graph Learning for Bidirectional Disease Contact Tracing on Real Human Mobility Data -- Turning Multidimensional Big Data Analytics into Practice: Design and Implementation of ClustCube Big-Data Tools in Real-Life Scenarios -- Fifty Shapes of Reddit: Do Prolife Activists Have the Same Interaction Patterns of Gun Fanatics? -- Heuristics for the Influence Maximization Problem on Hypergraphs -- Blocking Social Contagions via Dominating Sets Using a Modified Linear Integer Programming Formulation -- Exploring Writing Style Consistency to Timely Identify Heterogeneous Social Bots -- Profit Maximization in Signed Social Networks -- Learning Effectiveness of Natural Science Education in the Context of Social Networks: A Case Study of Plant Identification Application -- Applying Opinion Mining and Social Volume Analysis for Enhanced Visitor Relationship Management in A Museum: An Empirical Study -- Generative AI in ESG Reporting: A Systematic Review -- Research on the Detection and Rephrasing of Toxic Text Based on Large-scale Pre-training Language Models -- Dynamic Stock Trading: Integrating Historical, Real-Time Stock Data and Sentiments for Recommendation and Price Prediction Trends -- A Successive Analysis of Online Networked Common Knowledge Experiments -- EVOLVE: Predicting User Evolution and Network Dynamics in Social Media Using Fine-Tuned GPT-like Model -- CAMERA: Context Based Emotion Detection Framework And Its Evaluation. | |
| 520 | |a This 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 volume 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Application software. | |
| 650 | 0 | |a Quantitative research. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 1 | 4 | |a Computer and Information Systems Applications. |
| 650 | 2 | 4 | |a Data Analysis and Big Data. |
| 650 | 2 | 4 | |a Machine Learning. |
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| 700 | 1 | |a Karampelas, Panagiotis. |e editor. |0 (orcid)0000-0003-1684-7612 |1 https://orcid.org/0000-0003-1684-7612 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Day, Min-Yuh. |e editor. |0 (orcid)0000-0001-6213-5646 |1 https://orcid.org/0000-0001-6213-5646 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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