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23/4/21
Detect movie spoilers:
An external resource independent approach
23/4/21
Movie spoiler
• Comments that reveal important information on movie’s plot.– Reduce customers' intention to watch the movie
• Example– In <Sixth Senth>, the real murdererturned out to be $%#%$@
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What
• Detect movie spoilers, automatically screen them.– Most Relevant Previous study: To compare the
comment with movie’s synopsis(Guo 2010).– But Synopsis is not always available• External resource independent approach is needed
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Difficulties• There is no theorized feature that distinguishes
spoilers.
• Objective: In the end the heroine died• Subjective: The death of the heroine was very sad to
me.Specific Terms• The criminal was Michael Brown.• The criminal was who you can hardly imagine—the
little boy!
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Possible feature
• POS tag ngrams• Sentiment polarity• subjectivity• Tense of verbs• movie specific terms• Average word length• Sentence length
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How
Movie reviews
Feature Extractor
Featuresets(POS tags)
(sentiment polarity(tense etc.)
Manually tagged reviews
features
SVMEnsembleSVM
Feature Selection Classifier training Evaluation
Spoiler Classifier
23/4/21
Dataset
23/4/21
Why
• Many users want the evaluation on the movie from the review comments but not spoliers that reveal plots. (Or the opposite)
• Film industry will suffer from spoilers.
• Result can be extend to other industries like novels, comics and games.
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