Conference Proceedings

A Basic Study on Spoiler Detection from Review Comments Using Story Documents

Abstract

In many shopping sites such as Amazon.com it is possible to view and write reviews of items (products and content). Reviews of items including stories, such as novels, movies, and comics, include reviewers’ opinions. Often, these reviews also include descriptions of the story. In some cases, these descriptions may spoil later reader’s or viewer’s enjoyment and excitement. Hereinafter, we call these descriptions spoilers. Spoilers may be related to the position in the story line. In this study we use story documents. Story documents are documents that record all of the details of the given story. Using the story documents, we investigate the location to which the content of the spoilers correspond in the story documents. Based on the result of the investigation, we consider how to detect spoilers in reviewers’ comments.

Information

Book title

2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)

Date of issue

2016/10/13

DOI

10.1109/WI.2016.0098

Keywords

opinion mining / spoiler detection / story document / ネタバレ / spoiler

Citation

Kyosuke Maeda, Yoshinori Hijikata, Satoshi Nakamura. A Basic Study on Spoiler Detection from Review Comments Using Story Documents, 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2016.