Type of Credit: Partially Required
Credit(s)
Number of Students
In this course, the following topics will be presented and discussed: social media analysis, blogs and friendship network analysis, email and messaging analytics, influence spreading and viral marketing, social reputation and trust, user profiling and recommendation systems, social media searches, expertise and authority discovery, community identification, link prediction, collaborative data analysis, and data mining with social factors.
能力項目說明
Some websites own considerable amount of data, e.g., the user topology of Facebook contains billions of nodes. For a large variety of social networking applications, community detection is the one of the most basic issues for mining their data. Moreover, new topics emerge for modeling the user behaviors with the abundant social information, e.g., credibility mining, user interest modeling, user demographics and social strategy inference, advertisement targeting, fraud/anomaly detection, influence probability learning. On the other hand, analyzing social links provides fundamental knowledge for different applications, e.g., link prediction for friend/item recommendation, social influence for viral marketing, and anchor link inference for identity authentication. Also, graph pattern mining is one of the most important topics for graph data mining as well as the pairwise shortest path query and triangle counting. Furthermore, to avoid malice adversary obtaining users’ real identities of each corresponding node, privacy-preserving graph mining plays a very important role when social network data is used in practical commercial sales. The clustering and classification of documents in social media are also important for social networks.
教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
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1. Data Mining in Social Network
2. Frequent Pattern Mining
3. Clustering
4. Classification
5. Classification
6. Statistics Property of Social Network
7. Community Discovery
8. Midterm
9. Node Classification
10. Link prediction
11. Privacy in Social Network Text Mining
12. Text Mining in Social Network
13.Project Proposal
14. Social Influence
15. Social Tagging
16. Project Presentation
check in the class