Text Mining & Social Network Analysis

Predictive Analytics
  • 11 Videos | 53m 37s
  • Includes Assessment
  • Earns a Badge
Likes 88 Likes 88
Text mining facilitates social network analysis, giving analysts the ability to capture people's sentiments about various topics. Examine how text mining and social network analysis can greatly impact many diverse areas.

WHAT YOU WILL LEARN

  • identify key characteristic of text mining
    assign within document predictor variables for text mining
    recognize key methods for text normalization
    assign across document predictor variables for text mining
    recognize the use of term frequency and inverse document frequency measures for text mining
    identify key characteristics of sentiment analysis
  • identify examples of text mining applications
    identify key characteristics of social network analysis
    distinguish between ego-centric and network-centric analysis
    identify key features of social network mapping
    recognize key terms and concepts used in social network and media analysis

IN THIS COURSE

  • Playable
    1. 
    Overview of Text Mining
    6m 1s
    UP NEXT
  • Playable
    2. 
    Assigning within Document Predictor Variables
    5m 20s
  • Locked
    3. 
    Text Normalization
    4m 13s
  • Locked
    4. 
    Assigning Across Document Predictor Variables
    3m 16s
  • Locked
    5. 
    Term Frequency and Inverse Document Frequency
    4m 13s
  • Locked
    6. 
    Sentiment Analysis
    3m 32s
  • Locked
    7. 
    Text Mining Applications
    3m 23s
  • Locked
    8. 
    Overview of Social Network Analysis
    5m 49s
  • Locked
    9. 
    Ego-centric and Network-centric Analysis
    4m 9s
  • Locked
    10. 
    Social Network Mapping
    3m 39s
  • Locked
    11. 
    Key Terms and Concepts
    4m 32s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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