Schedule for the T&T Course

• Tu 05.03 [#01] Citation Management and Academic Writing I
• Tu 19.03 [#02] “Off with the Interface!” Getting to know the command line
• Tu 26.03 [#03] Version Control and Collaboration
• Tu 02.04 [#04] Citation Management and Academic Writing II
• Tu 09.04 [#05] Regular expressions
• Tu 30.04 [#06] Webscraping
• Tu 07.05 [#07] Text Markup [TEI XML], and how to remove it…
• Tu 14.05 [#08] Structuring data
• Tu 21.05 [#09] Georeferencing with QGIS
• Tu 28.05 [#10] Text to Map (1/2)
• Tu 04.06 [#11] Text to Map (2/2)
• Tu 18.06 [#12] Topic modeling with R / Python
• Tu 25.06 [#13] Social Network Analysis with Gephi

Detailed Schedule

Tu 05.03 [#01] Citation Management and Academic Writing I

• Using Styles in MS Word
• Using Zotero for managing bibliography

Tu 19.03 [#02] “Off with the Interface!” Getting to know the command line

Tu 26.03 [#03] Version Control and Collaboration

Tu 02.04 [#04] Citation Management and Academic Writing II

Tu 09.04 [#05] Regular expressions

Tu 30.04 [#06] Webscraping

Tu 07.05 [#07] Text Markup [TEI XML], and how to remove it…

Tu 14.05 [#08] Structuring data

Tu 21.05 [#09] Georeferencing with QGIS

Tu 28.05 [#10] Text to Map (1/2)

Tu 04.06 [#11] Text to Map (2/2)

Tu 18.06 [#12] Topic modeling with R / Python

• with R (but better with Python)
• Python: gensim (https://radimrehurek.com/gensim/intro.html)

Tu 25.06 [#13] Social Network Analysis with Gephi

Schedule for the R Course

Some topics are foundational and are taught in the TNT Class

• Tu 05.03 [#01] Introduction
• Tu 19.03 [#02] Data
• Tu 26.03 [#03]
• Tu 02.04 [#04]
• Tu 09.04 [#05]
• Tu 30.04 [#06]
• Tu 07.05 [#07]
• Tu 14.05 [#08]
• Tu 21.05 [#09]
• Tu 28.05 [#10]
• Tu 04.06 [#11]
• Tu 18.06 [#12] Topic modeling with R
  • Those who did it last year in TNT, can do Python (in TNT class, or on their own)
• Tu 25.06 [#13] Project presentations

Detailed Schedule

Tu 05.03 [#01] Introduction

• Installing R: https://cloud.r-project.org/
• Installing RStudio: https://www.rstudio.com/products/rstudio/download/
• Basic commands in R

Tu 19.03 [#02] Data

• Creating, Collection and Organinzing Data
  • READING: Broman, Karl W., and Kara H. Woo. “Data Organization in Spreadsheets.” The American Statistician 72, no. 1 (January 2, 2018): 2–10. https://doi.org/10.1080/00031305.2017.1375989.

Tu 26.03 [#03]

Tu 02.04 [#04]

Tu 09.04 [#05]

Tu 30.04 [#06]

Tu 07.05 [#07]

Tu 14.05 [#08]

Tu 21.05 [#09]

Tu 28.05 [#10]

Tu 04.06 [#11]

Tu 18.06 [#12]

Tu 25.06 [#13]

Topics to cover:

1. R basics:
   • Basic intro;
     • Interactive tutorial:
       • Swirl, https://swirlstats.com/
       • learnr, https://rstudio.github.io/learnr/examples.html
   • Specific tools in R:
     • RMarkdown
     • Shiny
     • ggplot2 and ggvis
     • tidyverse

• topic modeling
• stylometry

Materials and Datasets

• Library of Congress:
  • [DATA] 25 mln book records: http://www.loc.gov/cds/products/MDSConnect-books_all.html
• Miriam Posner (UCLA):
  • [DATA] collection of datasets: http://miriamposner.com/classes/dh201w19/final-project/datasets/
  • class materials: http://miriamposner.com/classes/dh201w19/
• Lincoln Mullen (Geprge Mason U):
  • [DATA] historydata R-package: https://lincolnmullen.com/software/historydata/
  • Computational Historical Thinking, https://dh-r.lincolnmullen.com/
• Paul Vierthaler:
  • Lecture slides, https://github.com/vierth/hth2018Lectures

Notes

• Kieran Healy’s “Data Visualization: A Practical Guide”, http://socviz.co/
• Jupiter notebooks can be converted to markdown with jupyter nbconvert *.ipynb --to markdown, where *.ipynb is the name of the jupyter notebook file. Then the notebook can be published as a blogpost with Jekyll.
• Rmarkdown:
  • https://bookdown.org/yihui/rmarkdown/
  • https://rmarkdown.rstudio.com/
• RStudio: