1. Recognizing Literary Tropes in Plot Synopses Sam Carton April 12, 2013

2. Outline I.Introduction II.Data III.Method IV.Experiment V.Results VI.Conclusion

3. Data – TVTropes.org TVTropes.org o ~30,000 tropes overall o 6,583 pages for films, books, video games o 983 tropes that occur >50 times in that collection

4. Data - Wikipedia ~40,000,000 English- language pages 41 gigs uncompressed text

5. Data - Disambiguation Non-trivial ?

6. Data - Disambiguation Match titles, then match article glosses Regular expressions for years, media types 3,796 article pairs 283 tropes 6,583 article pairs 983 tropes

7. Method – Naïve Bayes Naïve Bayes C W1W1 W2W2 W3W3 WNWN … CW1W1 1.4 0.9 CW2W2 1.2 0.4 CW3W3 1.9 0.7 CWNWN 1.1 0.05

8. Method – Text pre- processing Pre- processing method Preprocessed sentence Original After witnessing the power of their guns, the human tribe does not want the expedition to leave, and tries to keep them on the plateau." POS- tagged IN VBG DT NN IN PRP$ NNS, DT JJ NN VBZ RB VB DT NN TO VB, CC VBZ TO VB PRP IN DT NN. Stopwords After [content] the [content] of their [content] the [content] [content] does not want the [content] to [content], and tries to [content] them on the [content] " Stemmedwitnes power gun, human trib expedit leav, keep plateau.

9. Method – N-grams Instead of individual words, look at sequences of words Unigram o After witnessing the power of their guns, the human tribe does not want the expedition to leave, and tries to keep them on the plateau.“ BECOMES [After],[witnessing],[the],[power]… Bigram o After witnessing the power of their guns, the human tribe does not want the expedition to leave, and tries to keep them on the plateau.“ BECOMES [After witnessing], [witnessing the], [the power], [power of]…

10. Experiment 1.Main Experiment o Performance of N-gram/preprocessing combinations 2.Trope frequency experiment o Performance of models on more-frequent/less-frequent tropes 3.Media type experiment o Performance of models on different media types

11. Results – Main 1

12. Results – Main 2

13. Results – Trope frequency

14. Results – Media types

15. Conclusion Hard problem More data needed o Positive examples More sophisticated models One size fits all?

16. Future work Additional text data Consider inter-trope correlations More media types