Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text
  and English Humor Literature   Sarcasm is a sophisticated way of wrapping any immanent truth, mes-sage, or
even mockery within a hilarious manner. The advent of communications using
social networks has mass-produced new avenues of socialization. It can be
further said that humor, irony, sarcasm, and wit are the four chariots of being
socially funny in the modern days. In this paper, we manually extract the
sarcastic word distribution features of a benchmark pop culture sarcasm corpus,
containing sarcastic dialogues and monologues. We generate input sequences
formed of the weighted vectors from such words. We further propose an
amalgamation of four parallel deep long-short term networks (pLSTM), each with
distinctive activation classifier. These modules are primarily aimed at
successfully detecting sarcasm from the text corpus. Our proposed model for
detecting sarcasm peaks a training accuracy of 98.95% when trained with the
discussed dataset. Consecutively, it obtains the highest of 98.31% overall
validation accuracy on two handpicked Project Gutenberg English humor
literature among all the test cases. Our approach transcends previous
state-of-the-art works on several sarcasm corpora and results in a new gold
standard performance for sarcasm detection.

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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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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: math-ph
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The categories of this paper are: adap-org
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
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The categories of this paper are: plasm-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: nlin
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The categories of this paper are: q-fin