References

Aragon, Tomas J. 2020. Epitools: Epidemiology Tools. https://doi.org/10.32614/CRAN.package.epitools.
Bache, Stefan Milton, and Hadley Wickham. 2026. Magrittr: A Forward-Pipe Operator for r. https://magrittr.tidyverse.org.
Bilisoly, Roger. 2008. Practical Text Mining with Perl. Wiley Series on Methods and Applications in Data Mining. Wiley. http://books.google.com.au/books?id=YkMFVbsrdzkC.
Breiman, Leo, Adele Cutler, Andy Liaw, and Matthew Wiener. 2024. randomForest: Breiman and Cutlers Random Forests for Classification and Regression. https://www.stat.berkeley.edu/~breiman/RandomForests/.
Cameron, Allan, and Teun van den Brand. 2025. Geomtextpath: Curved Text in Ggplot2. https://allancameron.github.io/geomtextpath/.
Dahl, David B., David Scott, Charles Roosen, Arni Magnusson, and Jonathan Swinton. 2019. Xtable: Export Tables to LaTeX or HTML. http://xtable.r-forge.r-project.org/.
Dragulescu, Adrian, and Cole Arendt. 2020. Xlsx: Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files. https://github.com/colearendt/xlsx.
Durant, Will. 1926. The Story of Philosophy. 2012th ed. Simon; Schuster.
Feinerer, Ingo, and Kurt Hornik. 2026. Tm: Text Mining Package. https://tm.r-forge.r-project.org/.
Fellows, Ian. 2018. Wordcloud: Word Clouds. http://blog.fellstat.com/?cat=11.
Firke, Sam. 2024. Janitor: Simple Tools for Examining and Cleaning Dirty Data. https://github.com/sfirke/janitor.
Gagolewski, Marek. 2026. Stringi: Fast and Portable Character String Processing Facilities. https://stringi.gagolewski.com/.
Gandrud, Christopher. 2014. Repreoducible Research with R and RStdio. The R Series. CRC Press.
Harrell Jr, Frank E. 2026. Hmisc: Harrell Miscellaneous. https://hbiostat.org/R/Hmisc/.
Hester, Jim, and Jennifer Bryan. 2026. Glue: Interpreted String Literals. https://glue.tidyverse.org/.
Hodge, David. 2026. Ggblanket: Publication-Quality Ggplot2 Visualisation. https://davidhodge931.github.io/ggblanket/.
Hornik, Kurt. 2026. RWeka: R/Weka Interface. https://doi.org/10.32614/CRAN.package.RWeka.
Hothorn, Torsten, Kurt Hornik, Carolin Strobl, and Achim Zeileis. 2026. Party: A Laboratory for Recursive Partytioning. https://codeberg.org/thothorn/party.
Hothorn, Torsten, and Achim Zeileis. 2026. Partykit: A Toolkit for Recursive Partytioning. https://codeberg.org/thothorn/partykit.
Keitt, Tim. 2024. colorRamps: Builds Color Tables. https://doi.org/10.32614/CRAN.package.colorRamps.
Knuth, Donald E. 1984. “Literate Programming.” The Computer Journal (British Computer Society) 27 (2): 97–111. http://www.literateprogramming.com/knuthweb.pdf.
Kuhn, Max, and Ross Quinlan. 2025. C50: C5.0 Decision Trees and Rule-Based Models. https://topepo.github.io/C5.0/.
Liu, Zhongxin, Xin Xia, Christoph Treude, David Lo, and Shanping Li. 2019. “Automatic Generation of Pull Request Descriptions.” 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE), November. https://doi.org/10.1109/ase.2019.00026.
Milborrow, Stephen. 2026. Rpart.plot: Plot Rpart Models: An Enhanced Version of Plot.rpart. http://www.milbo.org/rpart-plot/index.html.
Neuwirth, Erich. 2022. RColorBrewer: ColorBrewer Palettes. https://doi.org/10.32614/CRAN.package.RColorBrewer.
Ooms, Jeroen, and Bill Denney. 2026. Writexl: Export Data Frames to Excel Xlsx Format. https://ropensci.r-universe.dev/writexl.
Pedersen, Thomas Lin. 2025. Patchwork: The Composer of Plots. https://patchwork.data-imaginist.com.
Qin, D., X. Zhou, L. Chen, G. Huang, and Y. Zhang. 2020. “Dynamic Connection-Based Social Group Recommendation.” IEEE Transactions on Knowledge and Data Engineering 32 (3): 453–67.
R Core Team. 2026. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://doi.org/10.32614/R.manuals.
Rinker, Tyler. 2018. qdapDictionaries: Dictionaries and Word Lists for the Qdap Package. http://trinker.github.com/qdapDictionaries/.
———. 2025. Qdap: Bridging the Gap Between Qualitative Data and Quantitative Analysis. https://trinker.github.io/qdap/.
———. 2026. Wakefield: Generate Random Data Sets. https://github.com/trinker/wakefield.
Ripley, Brian. 2026. Nnet: Feed-Forward Neural Networks and Multinomial Log-Linear Models. http://www.stats.ox.ac.uk/pub/MASS4/.
Romanski, Piotr, Lars Kotthoff, and Patrick Schratz. 2023. FSelector: Selecting Attributes. https://github.com/larskotthoff/fselector.
Sarkar, Deepayan. 2026. Lattice: Trellis Graphics for r. https://lattice.r-forge.r-project.org/.
Schloerke, Barret, Di Cook, Joseph Larmarange, Francois Briatte, Moritz Marbach, Edwin Thoen, Amos Elberg, and Jason Crowley. 2025. GGally: Extension to Ggplot2. https://ggobi.github.io/ggally/.
Sing, Tobias, Oliver Sander, Niko Beerenwinkel, and Thomas Lengauer. 2026. ROCR: Visualizing the Performance of Scoring Classifiers. https://ipa-tys.github.io/ROCR/.
Soetaert, Karline. 2020. Diagram: Functions for Visualising Simple Graphs (Networks), Plotting Flow Diagrams. https://doi.org/10.32614/CRAN.package.diagram.
Spinu, Vitalie, Garrett Grolemund, and Hadley Wickham. 2026. Lubridate: Make Dealing with Dates a Little Easier. https://lubridate.tidyverse.org.
Therneau, Terry, and Beth Atkinson. 2026. Rpart: Recursive Partitioning and Regression Trees. https://github.com/bethatkinson/rpart.
Velten, Kai. 2009. Mathematical Modeling and Simulation. Wiley.
Wickham, Hadley. 2014. Advanced R. Chapman & Hall/CRC the r Series. Chapman & Hall.
———. 2025. Stringr: Simple, Consistent Wrappers for Common String Operations. https://stringr.tidyverse.org.
———. 2026. Lobstr: Visualize r Data Structures with Trees. https://lobstr.r-lib.org/.
Wickham, Hadley, and Jennifer Bryan. 2026. Readxl: Read Excel Files. https://readxl.tidyverse.org.
Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, Hiroaki Yutani, Dewey Dunnington, and Teun van den Brand. 2026. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://ggplot2.tidyverse.org.
Wickham, Hadley, Romain François, Lionel Henry, Kirill Müller, and Davis Vaughan. 2026. Dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org.
Wickham, Hadley, Jim Hester, and Jennifer Bryan. 2026. Readr: Read Rectangular Text Data. https://readr.tidyverse.org.
Wickham, Hadley, Thomas Lin Pedersen, and Dana Seidel. 2025. Scales: Scale Functions for Visualization. https://scales.r-lib.org.
Wickham, Hadley, Davis Vaughan, and Maximilian Girlich. 2025. Tidyr: Tidy Messy Data. https://tidyr.tidyverse.org.
Williams, Graham. 2026. Rattle: R Data Science Supporting Rattle. https://togaware.com/projects/rattle/.
Williams, Graham J. 2011. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery. Use R! New York: Springer.
Williams, Graham J. 2017. The Essentials of Data Science: Knowledge Discovery Using r. The r Series. CRC Press.
Xie, Yihui. 2014. Dynamic Documents with R and Knitr. The R Series. CRC Press.
———. 2025. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.

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