Nanopublication

 Article: DWAEF: a deep weighted average ensemble framewo... DataScience ResearchPaper ScholarlyWork

http://id.crossref.org/issn/2451-8492 2451-8492 http://purl.org/dc/terms/title has the title (this is a literal) "Data Science" .

The journal with ISSN http://id.crossref.org/issn/https://doi.org/10.3233/DS-220058 DS-220058 http://purl.org/dc/terms/title has the title (this is a literal) "DWAEF: a deep weighted average ensemble framework harnessing novel indicators for sarcasm detection" .

https://orcid.org/0000-0002-3340-8112 Prakher Pandey http://schema.org/email has the email address (this is a literal) "prakher205723@keshav.du.ac.in" .

https://orcid.org/0000-0002-4472-1681 Richa Sharma http://schema.org/email has the email address (this is a literal) "richasharma@keshav.du.ac.in" .

https://orcid.org/0000-0002-5169-209X VISHAL MAURYA http://schema.org/email has the email address (this is a literal) "vishal205750@keshav.du.ac.in" .

https://orcid.org/0000-0002-6785-9691 Simrat Deol http://schema.org/email has the email address (this is a literal) "simrat205711@keshav.du.ac.in" .

https://orcid.org/0000-0003-0636-4000 Udit Kaushish http://schema.org/email has the email address (this is a literal) "udit205805@keshav.du.ac.in" .

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https://ror.org/04gzb2213 04gzb2213 http://xmlns.com/foaf/0.1/name has the name (this is a literal) "University of Delhi, India" .

https://orcid.org/0000-0002-3340-8112 Prakher Pandey http://schema.org/affiliation has the affiliation https://ror.org/04gzb2213 04gzb2213 .

https://orcid.org/0000-0002-4472-1681 Richa Sharma http://schema.org/affiliation has the affiliation https://ror.org/04gzb2213 04gzb2213 .

https://orcid.org/0000-0002-5169-209X VISHAL MAURYA http://schema.org/affiliation has the affiliation https://ror.org/04gzb2213 04gzb2213 .

https://orcid.org/0000-0002-6785-9691 Simrat Deol http://schema.org/affiliation has the affiliation https://ror.org/04gzb2213 04gzb2213 .

https://orcid.org/0000-0003-0636-4000 Udit Kaushish http://schema.org/affiliation has the affiliation https://ror.org/04gzb2213 04gzb2213 .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/dc/terms/abstract abstract "Sarcasm is a linguistic phenomenon often indicating a disparity between literal and inferred meanings. Due to its complexity, it is typically difficult to discern it within an online text message. Consequently, in recent years sarcasm detection has received considerable attention from both academia and industry. Nevertheless, the majority of current approaches simply model low-level indicators of sarcasm in various machine learning algorithms. This paper aims to present sarcasm in a new light by utilizing novel indicators in a deep weighted average ensemble-based framework (DWAEF). The novel indicators pertain to exploiting the presence of simile and metaphor in text and detecting the subtle shift in tone at a sentence’s structural level. A graph neural network (GNN) structure is implemented to detect the presence of simile, bidirectional encoder representations from transformers (BERT) embeddings are exploited to detect metaphorical instances and fuzzy logic is employed to account for the shift of tone. To account for the existence of sarcasm, the DWAEF integrates the inputs from the novel indicators. The performance of the framework is evaluated on a self-curated dataset of online text messages. A comparative report between the results acquired using primitive features and those obtained using a combination of primitive features and proposed indicators is provided. The highest accuracy of 92% was achieved after applying DWAEF, the proposed framework which combines the primitive features and novel indicators together as compared to 78.58% obtained using Support Vector Machine (SVM) which was the lowest among all classifiers." .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/dc/terms/date date "2023" .

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https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/pav/authoredBy authoredBy https://orcid.org/0000-0002-3340-8112 Prakher Pandey .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/pav/authoredBy authoredBy https://orcid.org/0000-0002-4472-1681 Richa Sharma .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/pav/authoredBy authoredBy https://orcid.org/0000-0002-5169-209X VISHAL MAURYA .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/pav/authoredBy authoredBy https://orcid.org/0000-0002-6785-9691 Simrat Deol .

https://doi.org/10.3233/DS-220058 doi:10.3233/DS-220058 http://purl.org/pav/authoredBy authoredBy https://orcid.org/0000-0003-0636-4000 Udit Kaushish .

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Tobias Kuhn, 21 Aug 2023, 13:24:56 UTC

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