Correlations Between Sentiment Analysis of Movie Tweets, Film Critics Reviews, and Box Office Earnings
Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Producer
Director
Performer
Choreographer
Costume Designer
Music
Videographer
Lighting Designer
Set Designer
Crew Member
Funder
Rehearsal Director
Concert Coordinator
Advisor
Moderator
Panelist
Alternative Title
Department
Swarthmore College. Dept. of Linguistics
Type
Thesis (B.A.)
Original Format
Running Time
File Format
Place of Publication
Date Span
Copyright Date
Award
Language
en_US
Note
Table of Contents
Terms of Use
Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
Rights Holder
Access Restrictions
Terms of Use
Tripod URL
Identifier
Abstract
This thesis explores correlations between sentiment analysis ratings from
movie tweets, film critics' ratings, and box office earnings. Two sentiment
analysis tools, NLTK and Pattern, are used to collect and automatically
extract the sentiments behind tweets about five movies released during
summer 2013: Despicable Me 2, The Bling Ring, Man of Steel, Monsters
University, and World War Z. The average ratings for each movie are
compared to the scores for each movie on Metacritic and Rotten
Tomatoes. Overall, for most of the movies the results from the sentiment
analysis ratings and film critics were similar, although in some instances
they did vary considerably. Additionally, Pattern corresponded better with
the film critics' ratings than NLTK. Furthermore, through graphical and
statistical analysis, correlations between these sets of ratings and the box
office earnings are studied. The analysis did not result in significant
correlations to make concrete conclusive predictions.