Text Mining & Social Network Analysis
Predictive Analytics
| Intermediate
- 11 Videos | 53m 37s
- Includes Assessment
- Earns a Badge
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
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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
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1.Overview of Text Mining6m 1sUP NEXT
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2.Assigning within Document Predictor Variables5m 20s
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3.Text Normalization4m 13s
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4.Assigning Across Document Predictor Variables3m 16s
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5.Term Frequency and Inverse Document Frequency4m 13s
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6.Sentiment Analysis3m 32s
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7.Text Mining Applications3m 23s
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8.Overview of Social Network Analysis5m 49s
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9.Ego-centric and Network-centric Analysis4m 9s
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10.Social Network Mapping3m 39s
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11.Key Terms and Concepts4m 32s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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