Text Network Analysis with NetMiner
Using NetMiner for Text Data Preprocessing, Topic Modeling, and Word Network Extraction & Visualization.
Ratings 4.84 / 5.00
What You Will Learn!
- Fundamentals of unstructured text mining and analysis.
- Text data preprocessing, topic modeling, and word network extraction and visualization using NetMiner.
- Mastery of the entire process of text analysis with NetMiner.
- Gaining hands-on experience through real-world analytics using email text data.
Description
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.
Who Should Attend!
- Individuals interested in text mining and textual data analysis.
- Those fascinated by keyword network analysis.
- People seeking to analyze unstructured text data, such as speeches, essay surveys, news articles, Twitter posts, and more.