Nanopublication: RA-dyreKi5
Full identifier: https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5fk6sXgmxTZn9rBzRmU9azGEiLTRhvXfqw5M
http://id.crossref.org/issn/2451-8492
2451-8492
http://purl.org/dc/terms/title
has the title
(this is a literal)
"Data Science"
.
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://orcid.org/0000-0002-3340-8112
Prakher Pandey
http://xmlns.com/foaf/0.1/name
name
"Prakher Pandey"
.
https://orcid.org/0000-0002-5169-209X
VISHAL MAURYA
http://xmlns.com/foaf/0.1/name
name
"Vishal Maurya"
.
https://orcid.org/0000-0003-0636-4000
Udit Kaushish
http://xmlns.com/foaf/0.1/name
name
"Udit Kaushish"
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/0000-0002-3340-8112
Prakher Pandey
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/0000-0002-4472-1681
Richa Sharma
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/0000-0002-5169-209X
VISHAL MAURYA
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/0000-0002-6785-9691
Simrat Deol
.
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https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/0000-0003-0636-4000
Udit Kaushish
.
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This nanopublication
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is created by
https://orcid.org/0000-0002-1267-0234
me (Tobias Kuhn)
.
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https://w3id.org/kpxl/ios/ds/np/RA-dyreKi5...
This nanopublication
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is published under the license
https://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International (CC BY 4.0)
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http://www.w3.org/1999/02/22-rdf-syntax-ns#type
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https://w3id.org/kpxl/ios/ds/terms/DataScienceNanopub
DataScienceNanopub
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"Article: DWAEF: a deep weighted average ensemble framewo..."
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"2023-08-21T13:24:56.821Z"
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RAi6zZAwha
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https://doi.org/10.3233/DS-220058
doi:10.3233/DS-220058
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