codebase

Hello, these scripts are for everyone, but they're designed for people who want to interpret their (social science) data and are interested in engaging with algorithms and programming (in R). Everything I do here you can do as well,  for free, on a reasonably modern computer. I'll try to illustrate my code with interesting real data. You can choose to read or code-along. 

Recommended guides to complement the content on this page: 

1. Ismay and Yim - Getting Started with Data in R

2. Wickham, Çetinkaya-Rundel, and Grolemund - R for Data Science (2e)

Google Colab Notebooks

These notebooks are interactive chunks of annotated R code along with their output. You can just read them, or modify or run them in your web browser of choice.

The notebooks are cloud-based, so you don't need to install anything on your computer or mobile device. You just need a browser, an internet connection, and a google account. The Gemini AI assistant (available on the top right corner of each notebook) can help explain bits of the code you'd like to know more about, and help you adapt it to your data and needs.

Applied: Identifying  recent technology and innovation management (TIM) research conversations

Identify large communities in a co-author network. Use network methods to obtain a purposive sample of papers. 

Exploratory: A content analysis of a corpus of short texts

Conduct a basic content analysis of a text corpus. Find most frequent words, compare across categories and over time.

Exploratory: Computationally-entangled interpretation of texts

Make sense of a large corpus of texts using network methods and an LDA topic model: Using algorithms to sample, summarize, and relate.

Shorts: Collaborators in a multi-author corpus

Create a co-author network from a SCOPUS database export.

Shorts: Handling data with Colab

Import and export data in different formats, some basic useful transformations.

Shorts: doc2excel - Word docs to excel for interpretive coding

Use Excel as a CAQDAS by converting text from word doc(s) to an excel file with one document/paragraph/sentence per row.

Shorts: Classroom tools

Randomly assign order of presentations or anonymize student names. Curve grades based on target mean and median.

Rmarkdown Notebooks

These notebooke are static chunks of annotated R code along with their output. These programs require a bit more juice to run, so they're best run on your laptop or desktop. To code along, please install R and RStudio on your machine, in that order.

Obsolete: Creating archival text data sets from Twitter, based on events, keywords, or users 

Requirements: An internet connection and a Twitter developer account with an approved Academic Track project.

Using an LDA Topic Model to summarize  and visualize thematic trends in a longitudinal single author archival text data set (Elon Musk Tweets 2010-2022)

Applications: Analyzing and representing changes in texts over time

Using machine methods to summarize, visualize, and interpret thematic trends in a longitudinal multi author archival text data set (Management Research Abstracts 1995-2019) 

Applications: Inductively identifying key themes, identifying "fingerprints" of authors or publications in a large longitudinal text data. Purposive sampling of papers based on theme rather than specific keywords. Measuring and representing similarity/dissimilarity/change over time (Good starting point for Lit Reviews). 

Coming soon...

Comparing the performance of LDA and BERT topic models

Creating a co-citation network from data exported from Web of Science/SCOPUS

Reference

To cite this page for code or research methodology, please use:

Bhardwaj, A. (2024) Codebase: Computational social science tools for students and scholars. https://www.anandb.net/code