A short, verified list
Resources
Required items are deliberately limited. Optional links provide another explanation when you need one.
Setup guides
- GitHub getting started walks through the private repository, GitHub Desktop, the first commit, and the first push using the exact course naming convention.
- Start Here remains the authoritative pre-course checklist for GitHub, R/RStudio, and Orange.
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Student repository template supplies the course folders and documentation files used during the Session 1 demonstration.
Orange Data Mining
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Install and get started with Orange
The official route to installation instructions, workflow examples, the widget catalog, and tutorials. Install Orange, then add Text Mining from Options → Add-ons.
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Text Preprocessing
Current official walkthrough of tokenization, stopwords, normalization, and corpus inspection.
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Bag of Words
Official walkthrough of count, binary, and TF-IDF representations in Orange’s Bag of Words widget.
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Hierarchical Clustering
The interface is older, but the explanation remains useful. Use the current widget documentation for the exact steps.
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Sentiment Analysis
Official walkthrough of Orange’s dictionary-based sentiment workflow. The class demonstration uses a supplied corpus.
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Topic Modelling and LDAvis
Current widget documentation for inspecting topics, term relevance, and topic prevalence.
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Text Mining widget catalog
Current documentation for Corpus, Preprocess Text, Bag of Words, embeddings, sentiment, and topic modeling.
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Orange Data Mining YouTube channel
The complete official video library includes beginner workflows and specialized text-mining demonstrations. Use it for review or troubleshooting. The channel is not a required playlist.
R and RStudio
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Install R
Choose your operating system from the official R Project download page and install R before installing RStudio.
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Install RStudio Desktop
After R is installed, use Posit’s stable RStudio Desktop installer. Open RStudio and run 1 + 1 in the Console to verify the setup.
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Swirl student guide
Complete R Programming lessons 1, 2, 4, 6, 7, and 12 before Session 2. Upload the single completion screenshot requested on the Assignments page.
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Introduction to R
Create or sign into a DataCamp account, then use the course classroom invitation from the instructor. Complete all six chapters in the three assigned blocks. No screenshot upload is required.
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Intermediate R
Complete all five chapters across the two assigned blocks. Completion is recorded in the DataCamp classroom. No screenshot upload is required.
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Text Mining with R: A Tidy Approach
A readable open reference for the R-only track. The full book is not assigned.
GitHub and FAIR
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Hello World
Optional broader background on repositories, commits, branches, and pull requests. Use the course-specific GitHub guide for required setup.
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FAIR Principles
The course translates these principles into concrete file, metadata, and provenance practices.
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NLP Corpora for Korean Studies
A documented catalog of Korean-language and Korea-focused corpora. Hackathon data will use an instructor-approved, prepared subset.
Text-as-data supplements
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Analyzing Documents with TF-IDF
Useful conceptual context. The Python exercises are not required.
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Install and get started with Orange
Course primer
Start with Text as Data in Six Moves. It is the course’s short conceptual alternative to a dense textbook chapter.
The R foundations assignment lists the required Swirl lessons, DataCamp chapters, deadlines, and how completion is checked. Use the R foundations fallback if DataCamp access is not active. The course corpora guide explains what data we will use and when it is released. Approved teaching files are distributed through the separate private BA3 Text as Data corpora repository. The larger NLP Corpora for Korean Studies catalog remains an optional reference.
How tutorials are selected
Required Orange videos must be official and short. They must also work with the current interface. An older video may remain as an optional explanation when paired with current widget documentation. Required preparation should stay under 20 minutes per session. The full official YouTube channel is a tutorial library. Students are not expected to watch it in sequence.