Prediction and inference from social networks and social media. (2017)

• Record Type: Book
• Further Information: Note: Jalal Kawash, Nitin Agarwal, Tansel Özyer, editor.
• Editors: Kawash, Jalal; Agarwal, Nitin; Özyer, Tansel
• Contents: Preface; Contents; 1 Having Fun?: Personalized Activity-Based Mood Prediction in Social Media; 1 Introduction; 2 Related Work; 3 Social Media Data; 3.1 Twitter Dataset; 3.2 Ground Truth; 4 Features; 5 Prediction; 5.1 Prediction Framework; 5.2 General Prediction Results; 5.3 Personalized Prediction Results; 6 Conclusion and Future Work; References; 2 Automatic Medical Image Multilingual Indexation Through a Medical Social Network; 1 Introduction; 2 Related Work; 2.1 Medical Social Networks; 2.2 Multilingual Indexation Approaches; 2.2.1 An Overview. 2.2.2 Indexation Approaches via Social Networks3 Social Network Architecture Description and Implementation; 4 The Proposed Methodology; 4.1 Comments' Pre-processing; 4.2 Cleaning, Correcting, and Lemmatization; 4.2.1 Cleaning; 4.2.2 Correcting Words; 4.2.3 Lemmatization Words; 4.3 Terms' Extraction; 4.3.1 Simple Terms' Extraction; 4.3.2 Compound Terms' Extraction; 4.3.3 Concepts' Extraction; 5 Experimental Results; 5.1 Data Test and Evaluation Criteria; 5.2 Evaluation and Results of Our Approach; 6 Conclusion and Future Work; References. 3 The Significant Effect of Overlapping Community Structures in Signed Social Networks1 Introduction; 1.1 Contribution of the Paper; 2 Related Work; 3 Use of Terms, Variables and Definitions; 4 Signed Disassortative Degree Mixing and Information Diffusion Approach; 4.1 Identifying Leaders; 4.2 Signed Cascading Process; 4.3 Overlapping Community-Based Ranking Algorithms; 4.3.1 Overlapping Community-Based HITS; 4.3.2 Overlapping Community-Based PageRank; 4.4 Baseline OCD Methods; 4.4.1 Signed Probabilistic Mixture Model ; 4.4.2 Multi-Objective Evolutionary Algorithm in Signed Networks. 5 Sign Prediction5.1 Classifiers; 5.1.1 Logistic Regression; 5.1.2 Bagging; 5.1.3 J48; 5.1.4 Decision Table; 5.1.5 Bayesian Network and Naive Bayesian; 5.2 Sign Prediction Features; 5.2.1 Simple Degree Sign Prediction Features; 5.2.2 OC-HITS Sign Prediction; 5.2.3 OC-PageRank Sign Prediction; 6 Dataset and Metrics; 6.1 Real World Networks; 6.2 Synthetic Networks; 6.3 Evaluation Metrics; 6.3.1 Normalized Mutual Information; 6.3.2 Modularity; 6.3.3 Frustration; 7 Results; 7.1 Results of OCD; 7.1.1 Network Size n; 7.1.2 Average Node Degree k; 7.1.3 Maximum Node Degree maxk.
• Publisher Details: Cham : Springer
• Publication Date: 2017
• Extent: 1 online resource
• Subjects: 303.49; Computer science; Social prediction; Social networks; Social media; SOCIAL SCIENCE -- General; Social media; Social networks; Social prediction; Computer Science; Data Mining and Knowledge Discovery; Applications of Graph Theory and Complex Networks; Computers and Society; User Interfaces and Human Computer Interaction; Science -- System Theory; Computers -- Social Aspects -- General; Computers -- User Interfaces; Mathematical physics; Ethical & social aspects of IT; User interface design & usability; Data mining; Computers -- Database Management -- Data Mining; Data mining; Electronic books
• Languages: English
• ISBNs: 9783319510491; 3319510495
• Related ISBNs: 9783319510484; 3319510487
• Notes: Note: Online resource; title from PDF title page (EBSCO, viewed March 24, 2017).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.