{"product_id":"social-network-analysis-9781119836230","title":"Social Network Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eSOCIAL NETWORK ANALYSIS\u003c\/b\u003e \u003cp\u003e\u003cb\u003eAs social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose.\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eSocial network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. \u003c\/p\u003e\u003cp\u003eThe book features: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSocial network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network.\u003c\/li\u003e \u003cli\u003eAn understanding of network analysis and motivations to model phenomena as networks.\u003c\/li\u003e \u003cli\u003eReal-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted.\u003c\/li\u003e \u003cli\u003eExemplifies information cascades that spread through an unde\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Overview of Social Network Analysis and Different Graph File Formats 1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAbhishek B. and Sumit Hirve\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction—Social Network Analysis 2\u003c\/p\u003e \u003cp\u003e1.2 Important Tools for the Collection and Analysis of Online Network Data 3\u003c\/p\u003e \u003cp\u003e1.3 More on the Python Libraries and Associated Packages 9\u003c\/p\u003e \u003cp\u003e1.4 Execution of SNA in Terms of Real-Time Application: Implementation in Python 13\u003c\/p\u003e \u003cp\u003e1.5 Clarity Toward the Indices Employed in the Social Network Analysis 14\u003c\/p\u003e \u003cp\u003e1.5.1 Centrality 14\u003c\/p\u003e \u003cp\u003e1.5.2 Transitivity and Reciprocity 15\u003c\/p\u003e \u003cp\u003e1.5.3 Balance and Status 15\u003c\/p\u003e \u003cp\u003e1.6 Conclusion 15\u003c\/p\u003e \u003cp\u003eReferences 15\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Introduction To Python for Social Network Analysis 19\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAgathiya Raja, Gavaskar Kanagaraj and Mohammad Gouse Galety\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 20\u003c\/p\u003e \u003cp\u003e2.2 SNA and Graph Representation 21\u003c\/p\u003e \u003cp\u003e2.2.1 The Common Representation of Graphs 21\u003c\/p\u003e \u003cp\u003e2.2.2 Important Terms to Remember in Graph Representation 23\u003c\/p\u003e \u003cp\u003e2.3 Tools To Analyze Network 24\u003c\/p\u003e \u003cp\u003e2.3.1 MS Excel 24\u003c\/p\u003e \u003cp\u003e2.3.2 Ucinet 26\u003c\/p\u003e \u003cp\u003e2.4 Importance of Analysis 26\u003c\/p\u003e \u003cp\u003e2.5 Scope of Python in SNA 26\u003c\/p\u003e \u003cp\u003e2.5.1 Comparison of Python With Traditional Tools 27\u003c\/p\u003e \u003cp\u003e2.6 Installation 27\u003c\/p\u003e \u003cp\u003e2.6.1 Good Practices 28\u003c\/p\u003e \u003cp\u003e2.7 Use Case 29\u003c\/p\u003e \u003cp\u003e2.7.1 Facebook Case Study 30\u003c\/p\u003e \u003cp\u003e2.8 Real-Time Product From SNA 32\u003c\/p\u003e \u003cp\u003e2.8.1 Nevaal Maps 33\u003c\/p\u003e \u003cp\u003eReferences 34\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Handling Real-World Network Data Sets 37\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eArman Abouali Galehdari, Behnaz Moradi and Mohammad Gouse Galety\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 37\u003c\/p\u003e \u003cp\u003e3.2 Aspects of the Network 38\u003c\/p\u003e \u003cp\u003e3.3 Graph 41\u003c\/p\u003e \u003cp\u003e3.3.1 Node, Edges, and Neighbors 41\u003c\/p\u003e \u003cp\u003e3.3.2 Small-World Phenomenon 42\u003c\/p\u003e \u003cp\u003e3.4 Scale-Free Network 43\u003c\/p\u003e \u003cp\u003e3.5 Network Data Sets 46\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 49\u003c\/p\u003e \u003cp\u003eReferences 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Cascading Behavior in Networks 51\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eVasanthakumar G. U.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 51\u003c\/p\u003e \u003cp\u003e4.1.1 Types of Data Generated in OSNs 52\u003c\/p\u003e \u003cp\u003e4.1.2 Unstructured Data 52\u003c\/p\u003e \u003cp\u003e4.1.3 Tools for Structuring the Data 53\u003c\/p\u003e \u003cp\u003e4.2 User Behavior 53\u003c\/p\u003e \u003cp\u003e4.2.1 Profiling 54\u003c\/p\u003e \u003cp\u003e4.2.2 Pattern of User Behavior 54\u003c\/p\u003e \u003cp\u003e4.2.3 Geo-Tagging 55\u003c\/p\u003e \u003cp\u003e4.3 Cascaded Behavior 56\u003c\/p\u003e \u003cp\u003e4.3.1 Cross Network Behavior 56\u003c\/p\u003e \u003cp\u003e4.3.2 Pattern Analysis 58\u003c\/p\u003e \u003cp\u003e4.3.3 Models for Cascading Pattern 59\u003c\/p\u003e \u003cp\u003eReferences 60\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Social Network Structure and Data Analysis in Healthcare 63\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSailee Bhambere\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 64\u003c\/p\u003e \u003cp\u003e5.2 Prognostic Analytics—Healthcare 64\u003c\/p\u003e \u003cp\u003e5.3 Role of Social Media for Healthcare Applications 65\u003c\/p\u003e \u003cp\u003e5.4 Social Media in Advanced Healthcare Support 67\u003c\/p\u003e \u003cp\u003e5.5 Social Media Analytics 67\u003c\/p\u003e \u003cp\u003e5.5.1 Phases Involved in Social Media Analytics 68\u003c\/p\u003e \u003cp\u003e5.5.2 Metrics of Social Media Analytics 69\u003c\/p\u003e \u003cp\u003e5.5.3 Evolution of NIHR 70\u003c\/p\u003e \u003cp\u003e5.6 Conventional Strategies in Data Mining Techniques 71\u003c\/p\u003e \u003cp\u003e5.6.1 Graph Theoretic 72\u003c\/p\u003e \u003cp\u003e5.6.2 Opinion Evaluation in Social Network 74\u003c\/p\u003e \u003cp\u003e5.6.3 Sentimental Analysis 75\u003c\/p\u003e \u003cp\u003e5.7 Research Gaps in the Current Scenario 75\u003c\/p\u003e \u003cp\u003e5.8 Conclusion and Challenges 77\u003c\/p\u003e \u003cp\u003eReferences 78\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Pragmatic Analysis of Social Web Components on Semantic Web Mining 83\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSasmita Pani, Bibhuprasad Sahu, Jibitesh Mishra, Sachi Nandan Mohanty and Amrutanshu Panigrahi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 84\u003c\/p\u003e \u003cp\u003e6.2 Background 87\u003c\/p\u003e \u003cp\u003e6.2.1 Web 87\u003c\/p\u003e \u003cp\u003e6.2.2 Agriculture Information Systems 88\u003c\/p\u003e \u003cp\u003e6.2.3 Ontology in Web or Mobile Web 90\u003c\/p\u003e \u003cp\u003e6.3 Proposed Model 90\u003c\/p\u003e \u003cp\u003e6.3.1 Developing Domain Ontology 91\u003c\/p\u003e \u003cp\u003e6.3.2 Building the Agriculture Ontology with OWL-DL 94\u003c\/p\u003e \u003cp\u003e6.3.2.1 Building Class Axioms 94\u003c\/p\u003e \u003cp\u003e6.3.3 Building Object Property Between the Classes in OWL-DL 95\u003c\/p\u003e \u003cp\u003e6.3.3.1 Building Object Property Restriction in OWL-DL 96\u003c\/p\u003e \u003cp\u003e6.3.4 Developing Social Ontology 97\u003c\/p\u003e \u003cp\u003e6.3.4.1 Building Class Axioms 99\u003c\/p\u003e \u003cp\u003e6.3.4.2 Analysis of Social Web Components on Domain Ontology Under Agriculture System 100\u003c\/p\u003e \u003cp\u003e6.4 Building Social Ontology Under the Agriculture Domain 100\u003c\/p\u003e \u003cp\u003e6.4.1 Building Disjoint Class 100\u003c\/p\u003e \u003cp\u003e6.4.2 Building Object Property 103\u003c\/p\u003e \u003cp\u003e6.5 Validation 104\u003c\/p\u003e \u003cp\u003e6.6 Discussion 104\u003c\/p\u003e \u003cp\u003e6.7 Conclusion and Future Work 105\u003c\/p\u003e \u003cp\u003eReferences 106\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Classification of Normal and Anomalous Activities in a Network by Cascading C4.5 Decision Tree and K-Means Clustering Algorithms 109\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGouse Baig Mohammad, S. Shitharth and P. Dileep\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 110\u003c\/p\u003e \u003cp\u003e7.1.1 Cascade Blogosphere Information 111\u003c\/p\u003e \u003cp\u003e7.1.2 Viral Marketing Cascades 112\u003c\/p\u003e \u003cp\u003e7.1.3 Cascade Network Building 113\u003c\/p\u003e \u003cp\u003e7.1.4 Cascading Behavior Empirical Research 113\u003c\/p\u003e \u003cp\u003e7.1.5 Cascades and Impact Nodes Detection 114\u003c\/p\u003e \u003cp\u003e7.1.6 Topologies of Cascade Networks 114\u003c\/p\u003e \u003cp\u003e7.1.7 Proposed Scheme Contributions 117\u003c\/p\u003e \u003cp\u003e7.2 Literature Survey 118\u003c\/p\u003e \u003cp\u003e7.2.1 Network Failures 122\u003c\/p\u003e \u003cp\u003e7.3 Methodology 123\u003c\/p\u003e \u003cp\u003e7.3.1 K-Means Clustering for Anomaly Detection 123\u003c\/p\u003e \u003cp\u003e7.3.2 C4.5 Decision Trees Anomaly Detection 124\u003c\/p\u003e \u003cp\u003e7.4 Implementation 125\u003c\/p\u003e \u003cp\u003e7.4.1 Training Phase Z\u003csub\u003eI\u003c\/sub\u003e 125\u003c\/p\u003e \u003cp\u003e7.4.2 Testing Phase 126\u003c\/p\u003e \u003cp\u003e7.5 Results and Discussion 127\u003c\/p\u003e \u003cp\u003e7.5.1 Data Sets 127\u003c\/p\u003e \u003cp\u003e7.5.2 Experiment Evaluation 127\u003c\/p\u003e \u003cp\u003e7.6 Conclusion 127\u003c\/p\u003e \u003cp\u003eReferences 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Machine Learning Approach To Forecast the Word in Social Media 133\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eR. Vijaya Prakash\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 133\u003c\/p\u003e \u003cp\u003e8.2 Related Works 135\u003c\/p\u003e \u003cp\u003e8.3 Methodology 135\u003c\/p\u003e \u003cp\u003e8.3.1 TF-IDF Technique 136\u003c\/p\u003e \u003cp\u003e8.3.2 Times Series 137\u003c\/p\u003e \u003cp\u003e8.4 Results and Discussion 138\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 141\u003c\/p\u003e \u003cp\u003eReferences 145\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Sentiment Analysis-Based Extraction of Real-Time Social Media Information From Twitter Using Natural Language Processing 149\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMadhuri Thimmapuram, Devasish Pal and Gouse Baig Mohammad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 150\u003c\/p\u003e \u003cp\u003e9.1.1 Applications for Social Media 153\u003c\/p\u003e \u003cp\u003e9.1.2 Social Media Data Challenges 154\u003c\/p\u003e \u003cp\u003e9.2 Literature Survey 157\u003c\/p\u003e \u003cp\u003e9.2.1 Techniques in Sentiment Analysis 164\u003c\/p\u003e \u003cp\u003e9.3 Implementation and Results 166\u003c\/p\u003e \u003cp\u003e9.3.1 Online Commerce 166\u003c\/p\u003e \u003cp\u003e9.3.2 Feature Extraction 167\u003c\/p\u003e \u003cp\u003e9.3.3 Hashtags 167\u003c\/p\u003e \u003cp\u003e9.3.4 Punctuations 167\u003c\/p\u003e \u003cp\u003e9.4 Conclusion 168\u003c\/p\u003e \u003cp\u003e9.5 Future Scope 171\u003c\/p\u003e \u003cp\u003eReferences 171\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Cascading Behavior: Concept and Models 175\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBithika Bishesh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 175\u003c\/p\u003e \u003cp\u003e10.2 Cascade Networks 177\u003c\/p\u003e \u003cp\u003e10.3 Importance of Cascades 178\u003c\/p\u003e \u003cp\u003e10.4 Purposes for Studying Cascades 179\u003c\/p\u003e \u003cp\u003e10.5 Collective Action 179\u003c\/p\u003e \u003cp\u003e10.6 Cascade Capacity 180\u003c\/p\u003e \u003cp\u003e10.7 Models of Network Cascades 180\u003c\/p\u003e \u003cp\u003e10.7.1 Decision-Based Diffusion Models 181\u003c\/p\u003e \u003cp\u003e10.7.2 Probabilistic Model of Cascade 181\u003c\/p\u003e \u003cp\u003e10.7.3 Linear Threshold Model 183\u003c\/p\u003e \u003cp\u003e10.7.4 Independent Cascade Model 183\u003c\/p\u003e \u003cp\u003e10.7.5 SIR Epidemic Model 184\u003c\/p\u003e \u003cp\u003e10.8 Centrality 186\u003c\/p\u003e \u003cp\u003e10.9 Cascading Failures 189\u003c\/p\u003e \u003cp\u003e10.10 Cascading Behavior Example Using Python 189\u003c\/p\u003e \u003cp\u003e10.11 Conclusion 192\u003c\/p\u003e \u003cp\u003eReferences 202\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Exploring Social Networking Data Sets 205\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eArulkumar N., Joy Paulose, Mohammad Gouse Galety, Manimaran A., S. Saravanan and Saleem Raja A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 206\u003c\/p\u003e \u003cp\u003e11.1.1 Network Theory 206\u003c\/p\u003e \u003cp\u003e11.1.2 Social Network Analysis 207\u003c\/p\u003e \u003cp\u003e11.2 Establishing a Social Network 208\u003c\/p\u003e \u003cp\u003e11.2.1 Designing the Symmetric Social Network 208\u003c\/p\u003e \u003cp\u003e11.2.2 Creating an Asymmetric Social Network 210\u003c\/p\u003e \u003cp\u003e11.2.3 Implementing and Visualizing Weighted Social Networks 212\u003c\/p\u003e \u003cp\u003e11.2.4 Developing the Multigraph for Social Networks 213\u003c\/p\u003e \u003cp\u003e11.3 Connectivity of Users in Social Networks 214\u003c\/p\u003e \u003cp\u003e11.3.1 The Degree to which a Network Exists 214\u003c\/p\u003e \u003cp\u003e11.3.2 Coefficient of Clustering 215\u003c\/p\u003e \u003cp\u003e11.3.3 The Shortest Routes and Length Between Two Nodes 215\u003c\/p\u003e \u003cp\u003e11.3.4 Eccentricity Distribution of a Node in a Social Network 217\u003c\/p\u003e \u003cp\u003e11.3.5 Scale-Independent Social Networks 218\u003c\/p\u003e \u003cp\u003e11.3.6 Transitivity 218\u003c\/p\u003e \u003cp\u003e11.4 Centrality Measures in Social Networks 218\u003c\/p\u003e \u003cp\u003e11.4.1 Centrality by Degree 219\u003c\/p\u003e \u003cp\u003e11.4.2 Centrality by Eigenvectors 219\u003c\/p\u003e \u003cp\u003e11.4.3 Centrality by Betweenness 220\u003c\/p\u003e \u003cp\u003e11.4.4 Closeness to All Other Nodes 220\u003c\/p\u003e \u003cp\u003e11.5 Case Study of Facebook 221\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 226\u003c\/p\u003e \u003cp\u003eReferences 227\u003c\/p\u003e \u003cp\u003eIndex 229\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48738370388311,"sku":"9781119836230","price":133.2,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119836230.jpg?v=1723811987","url":"https:\/\/bookcurl.com\/products\/social-network-analysis-9781119836230","provider":"Book Curl","version":"1.0","type":"link"}