大数据分析全英文 (36).pdf

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1、2Big Data ApplicationComputing AlgorithmComputing ModelData processing systemComputing Platform&EngineData Storing SystemSpark MLlibData VisualizationData Products and Data ServicesBig Data ApplicationData Application systemTensorFlowRecommendation SystemSocial Networking3CONTENTS1Social Network2Soc

2、ial Network Analysis3 Metrics of social networking analysis4Force-directed graph drawing5Hands on 41 What is social networkA social network is a social structure made up of a set of social actors(such as individuals or organizations),sets of dyadic ties,and other social interactions between actors.I

3、t characterizes networked structures in terms of nodes(individual actors,people,or things within the network)and the ties,edges,or links(relationships or interactions)that connect them.Video:SN1-Social Network Analysis Overview52 Social Network Analysis1 Presented Using a graph 2 Low Average Distanc

4、eSocial network analysis(SNA)is the process of investigating social structures through the use of networks and graph theory.Video:SNA2-What is Social Network Analysis 00-031364 Metrics of social networking analysisNodes and edges:Average Clustering Coefficient Eigenvector Centrality Average Path Len

5、gth Network:Average Degree Average Weighted Degree Network Diameter Graph Density Shortest Path Hits Modularity PageRank Connected Components 75 Force-directed graph drawing Force-directed graph drawing is an important technology on social network visualization.Force-directed graph drawing algorithm

6、s are a class of algorithms for drawing graphs in an aesthetically-pleasing way.Currently force-directed graph drawing algorithms are Force atlas algorithm,Fruchterman-Reingold algorithm,Yifan Hu algorithm,etc.85 Fruchterman-Reingold algorithm Fruchterman-Reingold algorithm is one of the most common

7、ly used algorithms.This algorithm uses electromagnetism theories,and generates a circular graph.Repulsive force =2;Gravitation force =2Final state:force balancedOriginal graphFruchterman-Reingold style95 SNA Hands on1 Hands-on Experiment:Networkx1.1 Loading data and generate graphs1.2 Network analys

8、is 1.3 Visualization using Networkx1.4 Edge bundling using datashader2 Hands-on experiment:Gephi2.1 Load data and analysis 2.2 Graph simplifying using Fruchterman-Reingold algorithm2.3 Visualization and beautification3 Hands-on experiment:Node2Vec to implement social network recommendation3.1 Social network recommendation background setting3.2 Biased random walk3.3 Node representation learning3.4 Recommendation