Beyond words of popularization mining: Reviews on comic books movies

Lee, Angela Siew Hoong * and Kazz, N. S. M. Kamil and Shankaraar, Narendranaath (2018) Beyond words of popularization mining: Reviews on comic books movies. Indian Journal of Science and Technology, 11 (25). pp. 1-11. ISSN 0974-6846

[img] Text
Lee Angerla Beyond Words pdf.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (859kB)
Official URL: http://doi.org/10.17485/ijst/2018/v11i25/118570

Abstract

Objectives: This paper aims to analyse the terms used by the of movie critics on popular comic book movies. From the analysis we are able to know what are the factors that most movie critics will focus at, whether the top movie critics review has an impact on the decision of general movie goers and from this will determine why the movies was a box office success. Methods: The research is done via text mining from SAS Enterprise Miner software which utilize the text analytics tool to analyse movie reviews by movie critics’ professionals. The analytical processes involved are text parsing, text filtering, text clustering and the text topic method. Correlation of terms is identified to help in determining the significance of each terms nested within the reviews. Findings: The findings show that the actors, the movie's characters and the film storyline are the most common type of terms that most movie critics are focusing on, thus this factors is what drives the reputation of the film and making it a blockbuster hit around the world. Application/Improvements: The results obtained can help the entertainment industry on their decision making on what to focus on when it comes to producing comic books superheroes into movies based on the sentiment analysis in identifying the postive and negative terms and their relationship with one another.

Item Type: Article
Uncontrolled Keywords: actors; characters; comic book; movie reviews; superhero; text mining
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Others > Non Sunway Academics
Sunway University > School of Science and Technology > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 24 May 2019 05:17
Last Modified: 24 May 2019 06:37
URI: http://eprints.sunway.edu.my/id/eprint/1047

Actions (login required)

View Item View Item