gknox79 / smwa-computing-lecture-intro-text

Introduction to Text Analytics

Social Media and Web Analytics: Computing Lecture 2

Learning Objectives

By the end of this class you should be able to:

• Explain the advantages and disadvantages of using text as data
• Compute the number of characters and words within a piece of text
• Define the terms unigram, token, stopword, word stem and TF-IDF
• Transform a dataset of text into a dataset of tokens
• Remove standard and customized stopwords from a data set of tokens
• Visualize the most common words used in a data set of tokens
• Lemmatize a set of tokens and explain the advantages of doing so
• Compute a TF-IDF metric on a set of tokens
• Explain the output of a statistical command that produces TF-IDF scores
• Visualize word clouds that show common or distinguishing words between two categories of text

Instructions for Students (Before Coming to Class)

Accessing Materials & Following Along Live in Class

Clone a copy of this repository using Git. To clone a copy of this repository to your own PC:

git clone https://github.com/tisem-digital-marketing/smwa-computing-lecture-intro-text.git

Once you have cloned the files, open the cloned repository in RStudio as an RStudio project and use the empty R scripts to follow along with the lecture as we work through material.

At the conclusion of the class, the course instructor's scripts are made available in the branch instructor. Recall that you can switch between branches using the git branch <BRANCHNAME> command in a terminal. Thus to switch to the instructor branch:

git branch instructor

And to switch back to the branch that you worked through live in class:

git branch main

NOTE: Git does not like you to switch branches with uncommitted changes. Before you switch branches, be sure to commit any changes to the files.

Installing required packages

This lecture makes use of additional R packages:

• janitor
• readr
• dplyr
• tibble
• tidyr
• ggplot2
• stringr
• tidytext
• textstem
• tokenizers
• reshape2
• wordcloud

Install these packages before coming to class.

Meta-Information

• Module Maintainer: Lachlan Deer (@lachlandeer)
• Course: Social Media and Web Analytics
• Institute: Dept of Marketing, Tilburg University
• Current Version: 2022 edition

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Suggested Citation

Deer, Lachlan. 2022. Social Media and Web Analytics: Computing Lecture 2 - Introduction to Text as Data Methods. Tilburg University. url = "https://github.com/tisem-digital-marketing/smwa-computing-lecture-intro-text"

@misc{smwa-compllecture02-2022,
      title={"Social Media and Web Analytics: Computing Lecture 2 - Introduction to Text as Data"},
      author={Lachlan Deer},
      year={2022},
      url = "https://github.com/tisem-digital-marketing/smwa-computing-lecture-intro-text"
}