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Detect movie spoilers:

An external resource independent approach

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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

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Dataset

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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.