• E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

INTERNATIONAL JOURNAL OF INVENTIONS IN ENGINEERING & SCIENCE TECHNOLOGY

International Peer Reviewed (Refereed), Open Access Research Journal
(By Aryavart International University, India)

Paper Details

Developing An Integrated Machine Learning Based Detection of Sarcasm

Sehaj Bedi

Amity University, Noida

51 - 56 Vol. 6, Jan-Dec, 2020
Receiving Date: 2020-10-04;    Acceptance Date: 2020-11-16;    Publication Date: 2020-11-23
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Abstract

Sarcasm is a real paradox, broadly utilized on Twitter. It is generally used to send personal data, a message sent by individuals. Because of various purposes, I can utilize Sarcasm like analysis and derision. However, even this is hard for an individual to observe. The sarcastic redesign framework is exceptionally useful for further developing programmed sentiment examination collected from various informal organizations and microblogging locales. Sentiment investigation suggests to web clients of a specific local area, communicated mentalities and assessments of ID and accumulation. To recognize Sarcasm, we propose an example-based methodology using Twitter social media. We offer four arrangements of highlights that incorporate a ton of explicit Sarcasm. We use them to group tweets as snide and non-wry. We likewise focus on each proposed set and assess its additional cost classification

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