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README.md
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- movie dialog
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- cornell
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---
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- movie dialog
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- cornell
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---
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Cornell Movie-Dialogs Corpus
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Distributed together with:
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"Chameleons in imagined conversations: A new approach to understanding coordination of linguistic style in dialogs"
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Cristian Danescu-Niculescu-Mizil and Lillian Lee
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Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, ACL 2011.
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(this paper is included in this zip file)
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NOTE: If you have results to report on these corpora, please send email to [email protected] or [email protected] so we can add you to our list of people using this data. Thanks!
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Contents of this README:
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A) Brief description
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B) Files description
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C) Details on the collection procedure
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D) Contact
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A) Brief description:
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This corpus contains a metadata-rich collection of fictional conversations extracted from raw movie scripts:
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- 220,579 conversational exchanges between 10,292 pairs of movie characters
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- involves 9,035 characters from 617 movies
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- in total 304,713 utterances
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- movie metadata included:
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- genres
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- release year
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- IMDB rating
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- number of IMDB votes
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- IMDB rating
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- character metadata included:
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- gender (for 3,774 characters)
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- position on movie credits (3,321 characters)
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B) Files description:
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In all files the field separator is " +++$+++ "
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- movie_titles_metadata.txt
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- contains information about each movie title
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- fields:
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- movieID,
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- movie title,
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- movie year,
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- IMDB rating,
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- no. IMDB votes,
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- genres in the format ['genre1','genre2',�,'genreN']
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- movie_characters_metadata.txt
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- contains information about each movie character
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- fields:
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- characterID
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- character name
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- movieID
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- movie title
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- gender ("?" for unlabeled cases)
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- position in credits ("?" for unlabeled cases)
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- movie_lines.txt
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- contains the actual text of each utterance
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- fields:
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- lineID
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- characterID (who uttered this phrase)
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- movieID
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- character name
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- text of the utterance
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- movie_conversations.txt
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- the structure of the conversations
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- fields
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- characterID of the first character involved in the conversation
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- characterID of the second character involved in the conversation
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- movieID of the movie in which the conversation occurred
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- list of the utterances that make the conversation, in chronological
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order: ['lineID1','lineID2',�,'lineIDN']
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has to be matched with movie_lines.txt to reconstruct the actual content
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- raw_script_urls.txt
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- the urls from which the raw sources were retrieved
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C) Details on the collection procedure:
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We started from raw publicly available movie scripts (sources acknowledged in
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raw_script_urls.txt). In order to collect the metadata necessary for this study
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and to distinguish between two script versions of the same movie, we automatically
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matched each script with an entry in movie database provided by IMDB (The Internet
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Movie Database; data interfaces available at http://www.imdb.com/interfaces). Some
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amount of manual correction was also involved. When more than one movie with the same
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title was found in IMBD, the match was made with the most popular title
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(the one that received most IMDB votes)
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After discarding all movies that could not be matched or that had less than 5 IMDB
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votes, we were left with 617 unique titles with metadata including genre, release
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year, IMDB rating and no. of IMDB votes and cast distribution. We then identified
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the pairs of characters that interact and separated their conversations automatically
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using simple data processing heuristics. After discarding all pairs that exchanged
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less than 5 conversational exchanges there were 10,292 left, exchanging 220,579
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conversational exchanges (304,713 utterances). After automatically matching the names
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of the 9,035 involved characters to the list of cast distribution, we used the
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gender of each interpreting actor to infer the fictional gender of a subset of
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3,321 movie characters (we raised the number of gendered 3,774 characters through
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manual annotation). Similarly, we collected the end credit position of a subset
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of 3,321 characters as a proxy for their status.
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D) Contact:
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Please email any questions to: [email protected] (Cristian Danescu-Niculescu-Mizil)
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