Assignment 10A: Sentiment Analysis

Approach

After reading chapter 2 of Text Mining with R and understanding the code used for sentiment analysis written by Julia Silge and David Robinson, I believe I can adapt their example code to make estimation on sentiment for book reviews of the Brandon Sanderson series known as Mistborn. I am not certain on whether I want to use the lexicons in a package like tidy text or find one through my own research. I will deiced what my plan will be by the end of Friday but I may also experiment with different packages to see which lexicons will work with my text corpus.

Challenges

Some challenges involved with this include fine tuning the sentiment analyse to my own goals, finding the appropriate lexicon, and being able to properly web scrape the reviews from a website. Spending extra time to experiment with the adapted code from the source to try and get a close expected outcome from the code. I assume that a lexicon with academic or review style language is best suited for this type of sentiment analyze and will look for that. I would like to web scrape a website for the reviews and put it in a data frame but if that takes more effort than I have time for then I will manually make a data frame.

Sources

Silge, Julia, and David Robinson. Text Mining with R: A Tidy Approach. O’Reilly Media, 2017.

Code adapted from Text Mining with R by Julia Silge and David Robinson (O’Reilly, 2017), licensed under CC BY-NC-SA 3.0.