Description
One of the most important sources of Goodreads are comments and reviews made by readers and not only. The general trend is to review the book in a very detailed way, reach of particulars and advises for others. For us, this means a great opportunity to see how it is articulated the opinion of peoples on the most rated books about defectors.
Processing comments with Aylien Tone Analyzer we created a list of emotion linked to single comments of the most rated books. The visualization show us how the most expressed emotion is joy. Without context it could mean something grotesque, if we link it to the topic we are analyzing, anyway, after a manual analysis we understood how joy is not linked to the book content itself, but with the experience of reading the rated books. Joy is followed by sadness and anger, on a few cases even towards authors themselves. Books (the Chinese network for Books) doesn’t allowed the user to leave any comments, so in this case we cannot compare the results.
Protocol
We automatically scraped comments from GoodReads using BeautifulSoup library in python and we use Tone Analyzer tool to extract the tone of the comment in JSON. We convert it into Excel and we create a dataset.
Data
Timestamp: 11/2016 - 11/2017
Data source: Goodreads, Books
Download data (9MB)
Per each book listed there are different tones with different scores.