Course details

Text Mining & Social Network Analysis

Text Mining & Social Network Analysis


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
Text mining facilitates social network analysis, giving analysts the ability to capture people's sentiments about various topics. Explore how text mining and social network analysis can greatly impact many diverse areas.

Target Audience
All individuals who are new to predictive analytics and wish to use it to optimize their business performance; business leaders; analysts; marketing, sales, software, and IT professionals who want to add predictive analytics to their skill set; and decision makers of any kind

Prerequisites
None

Expected Duration (hours)
0.9

Lesson Objectives

Text Mining & Social Network Analysis

  • start the course
  • 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
  • Course Number:
    df_prma_a13_it_enus

    Expertise Level
    Intermediate