Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: "Having 2 hours to write a paper is fun!": Detecting Sarcasm in
  Numerical Portions of Text   Sarcasm occurring due to the presence of numerical portions in text has been
quoted as an error made by automatic sarcasm detection approaches in the past.
We present a first study in detecting sarcasm in numbers, as in the case of the
sentence 'Love waking up at 4 am'. We analyze the challenges of the problem,
and present Rule-based, Machine Learning and Deep Learning approaches to detect
sarcasm in numerical portions of text. Our Deep Learning approach outperforms
four past works for sarcasm detection and Rule-based and Machine learning
approaches on a dataset of tweets, obtaining an F1-score of 0.93. This shows
that special attention to text containing numbers may be useful to improve
state-of-the-art in sarcasm detection.

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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: supr-con
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: acc-phys
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The categories of this paper are: atom-ph
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The categories of this paper are: q-bio
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The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-ex
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The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an