Prediction and inference from social networks and social media /
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| Imprint: | Cham : Springer, 2017. |
|---|---|
| Description: | 1 online resource |
| Language: | English |
| Series: | Lecture notes in social networks Lecture notes in social networks. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11272581 |
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| 245 | 0 | 0 | |a Prediction and inference from social networks and social media / |c Jalal Kawash, Nitin Agarwal, Tansel Özyer, editor. |
| 264 | 1 | |a Cham : |b Springer, |c 2017. | |
| 300 | |a 1 online resource | ||
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| 490 | 1 | |a Lecture notes in social networks | |
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed March 24, 2017). | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 520 | |a This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field. | ||
| 650 | 0 | |a Social prediction. |0 http://id.loc.gov/authorities/subjects/sh85123986 | |
| 650 | 0 | |a Social networks. |0 http://id.loc.gov/authorities/subjects/sh87002172 | |
| 650 | 0 | |a Social media. |0 http://id.loc.gov/authorities/subjects/sh2006007023 | |
| 650 | 7 | |a SOCIAL SCIENCE |x General. |2 bisacsh | |
| 650 | 7 | |a Social media. |2 fast |0 (OCoLC)fst01741098 | |
| 650 | 7 | |a Social networks. |2 fast |0 (OCoLC)fst01122678 | |
| 650 | 7 | |a Social prediction. |2 fast |0 (OCoLC)fst01122769 | |
| 650 | 1 | 4 | |a Computer Science. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Applications of Graph Theory and Complex Networks. |
| 650 | 2 | 4 | |a Computers and Society. |
| 650 | 2 | 4 | |a User Interfaces and Human Computer Interaction. |
| 650 | 7 | |a Mathematical physics. |2 bicssc | |
| 650 | 7 | |a Ethical & social aspects of IT. |2 bicssc | |
| 650 | 7 | |a User interface design & usability. |2 bicssc | |
| 650 | 7 | |a Data mining. |2 bicssc | |
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Kawash, Jalal, |e editor. | |
| 700 | 1 | |a Agarwal, Nitin, |e editor. | |
| 700 | 1 | |a Özyer, Tansel, |e editor. | |
| 776 | 0 | 8 | |i Print version: |t Prediction and inference from social networks and social media. |d Cham : Springer, 2017 |z 3319510487 |z 9783319510484 |w (OCoLC)964291495 |
| 830 | 0 | |a Lecture notes in social networks. | |
| 880 | 8 | |6 505-00/(S |a 7.1.4 Fraction of Edges Sharing with Other Communities μ7.1.5 Maximum Community Size maxc; 7.1.6 Number of Nodes in Overlapping Communities on; 7.1.7 Number of Communities Which Nodes in Overlapping Communities Belong to om; 7.1.8 Fractions of Positive Connections Between Communities P+; 7.1.9 Experiments on Real World Network; 7.2 Simple Degree Sign Prediction Results; 7.2.1 OC-HITS Sign Prediction; 7.2.2 OC-PageRank Sign Prediction; 8 Conclusion and Future Work; References; 4 Extracting Relations Between Symptoms by Age-Frame Based Link Prediction; 1 Introduction. | |
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| 928 | |t Library of Congress classification |a HM901 |l Online |c UC-FullText |u https://link.springer.com/10.1007/978-3-319-51049-1 |z Springer Nature |g ebooks |i 12544879 | ||