论文标题
IMDB扰流板数据集
IMDB Spoiler Dataset
论文作者
论文摘要
当我们考虑观看电影或电视节目时，用户生成的评论通常是我们的第一个联系点。但是，除了告诉我们要消费的媒体的定性方面外，评论可能不可避免地包含不希望的启示性信息（即“破坏者”），例如电影中角色的令人惊讶的命运，或者在犯罪中遇到的电影中的凶手身份。
User-generated reviews are often our first point of contact when we consider watching a movie or a TV show. However, beyond telling us the qualitative aspects of the media we want to consume, reviews may inevitably contain undesired revelatory information (i.e. 'spoilers') such as the surprising fate of a character in a movie, or the identity of a murderer in a crime-suspense movie, etc. In this paper, we present a high-quality movie-review based spoiler dataset to tackle the problem of spoiler detection and describe various research questions it can answer.
