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        <title>Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network</title>
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        <namePart type="given">Sudipta</namePart>
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    <abstract>Folksonomy of movies covers a wide range of heterogeneous information about movies, like the genre, plot structure, visual experiences, soundtracks, metadata, and emotional experiences from watching a movie. Being able to automatically generate or predict tags for movies can help recommendation engines improve retrieval of similar movies, and help viewers know what to expect from a movie in advance. In this work, we explore the problem of creating tags for movies from plot synopses. We propose a novel neural network model that merges information from synopses and emotion flows throughout the plots to predict a set of tags for movies. We compare our system with multiple baselines and found that the addition of emotion flows boosts the performance of the network by learning \approx18% more tags than a traditional machine learning system.</abstract>
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        <date>2018-08</date>
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%0 Conference Proceedings
%T Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network
%A Kar, Sudipta
%A Maharjan, Suraj
%A Solorio, Thamar
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F kar-etal-2018-folksonomication
%X Folksonomy of movies covers a wide range of heterogeneous information about movies, like the genre, plot structure, visual experiences, soundtracks, metadata, and emotional experiences from watching a movie. Being able to automatically generate or predict tags for movies can help recommendation engines improve retrieval of similar movies, and help viewers know what to expect from a movie in advance. In this work, we explore the problem of creating tags for movies from plot synopses. We propose a novel neural network model that merges information from synopses and emotion flows throughout the plots to predict a set of tags for movies. We compare our system with multiple baselines and found that the addition of emotion flows boosts the performance of the network by learning \approx18% more tags than a traditional machine learning system.
%U https://aclanthology.org/C18-1244
%P 2879-2891

Markdown (Informal)

[Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network](https://aclanthology.org/C18-1244) (Kar et al., COLING 2018)

• Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network (Kar et al., COLING 2018)

ACL

• Sudipta Kar, Suraj Maharjan, and Thamar Solorio. 2018. Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2879–2891, Santa Fe, New Mexico, USA. Association for Computational Linguistics.