
Introducing the features of NetMiner.
Guide to installing NetMiner.
Open the NetMiner file (.nmf) to see the data structure of NetMiner.
Learn how to import network data into NetMiner and how to edit the data.
Learn how to visualize networks and analyze networks with NetMiner.
Learn how to install and use NetMiner's plugins.
Explore the basic assumptions and analysis process for text network analysis.
Explore the applications of text network analysis and how to collect text data.
For text network analysis, learn how to extract words, analyze morpheme, tag parts of speech, and measure word importance.
For text network analysis, learn how to model word networks.
Learn about the topic modeling (LDA) method.
Learn about the topic modeling (LDA) method.
Let's practice importing text data into NetMiner.
Let's practice filtering text data, preprocessing(Dictionary), and creating word networks.
Let's take a look at the procedure for text network analysis using email text data.
Let's practice importing email text data into NetMiner. Please download and prepare the attached sample data.
Let's practice creating wordclouds and filtering words using email text data.
Let's practice topic modeling (LDA) using email text data.
Let's practice visualizing the results of a topic modeling (LDA) analysis.
Let's practice using a plug-in that automates the text analysis process.
Explore the realm of unstructured text data analysis with our course focused on harnessing NetMiner's text network analysis features. Delve into the process of analyzing varied text data, such as emails, news articles, and speeches, employing the powerful capabilities of NetMiner.
This course provides a comprehensive theoretical foundation for the entire text network analysis process. Learn to extract words from sprawling unstructured text data, uncover hidden topics, and construct as well as visualize engaging word networks. Further, we'll explore the critical skill of identifying key words, enhancing your overall analytical proficiency.
But we don't just stop at theory. This course includes practical exercises that enable you to apply learned techniques to real-world data. Experience firsthand the application of analysis methods to data like email texts using NetMiner. This hands-on experience will solidify your understanding and facilitate the translation of theoretical knowledge into practical skills.
This comprehensive course, balanced with theory and practice, is an invaluable asset for anyone seeking to bolster their data analysis abilities. Join us on this journey to mastery in text network analysis with NetMiner.
The details of this course are summarized as follows:
1. An overview of text analysis using Social Network Analysis (SNA).
2. An introduction to basic text analysis theory, covering topics such as morphological analysis, the importance of words using Term Frequency-Inverse Document Frequency (TF-IDF), word network modeling, and Latent Dirichlet Allocation (LDA) for topic modeling.
3. Practical exercises with NetMiner functions, including inputting text data, filtering data, applying a user dictionary, and generating word networks.
4. Hands-on experience with email text analysis, applying what you've learned to real-world data using the Enron email dataset.
This course provides a comprehensive exploration of text analysis using NetMiner, blending theoretical understanding with practical application for a well-rounded learning experience.