For this assignment, I plan to explore sentiment analysis using the methods introduced in Chapter 2 of Text Mining with R. I will first reproduce the original example using Jane Austen’s novels to understand how sentiment analysis works and how different sentiment lexicons classify words as positive, negative, or associated with emotions.
After completing the original example, I plan to use a different text
dataset, such as a collection of public speeches, to examine how
sentiment changes across different texts. I will use R and packages such
as tidytext, dplyr, and ggplot2
to clean the text, organize it into individual words, analyze sentiment,
and create visualizations. I also plan to include an additional
sentiment lexicon to compare the results with the lexicons used in the
original example.
Some challenges I expect include cleaning unstructured text, handling words that have different meanings depending on context, and differences in how sentiment lexicons classify words. I will compare the results, identify patterns, and explain how the findings differ from the original example.