Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bollywood Movie Corpus for Text, Images and Videos   In past few years, several data-sets have been released for text and images.
We present an approach to create the data-set for use in detecting and removing
gender bias from text. We also include a set of challenges we have faced while
creating this corpora. In this work, we have worked with movie data from
Wikipedia plots and movie trailers from YouTube. Our Bollywood Movie corpus
contains 4000 movies extracted from Wikipedia and 880 trailers extracted from
YouTube which were released from 1970-2017. The corpus contains csv files with
the following data about each movie - Wikipedia title of movie, cast, plot
text, co-referenced plot text, soundtrack information, link to movie poster,
caption of movie poster, number of males in poster, number of females in
poster. In addition to that, corresponding to each cast member the following
data is available - cast name, cast gender, cast verbs, cast adjectives, cast
relations, cast centrality, cast mentions. We present some preliminary results
on the task of bias removal which suggest that the data-set is quite useful for
performing such tasks.

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The categories of this paper are: alg-geom
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The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: chao-dyn
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-th
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The categories of this paper are: stat