Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA
PaperId: :  17671
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 4 2022
DUI:    16.0415/IJARIIE-17671
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
ATHIRA K MENONIES COLLEGE OF ENGINEERING
NEETHU PIIES COLLEGE OF ENGINEERING
DR.G.KIRUTHIGAIES COLLEGE OF ENGINEERING

Abstract

COMPUTER SCIENCE ENGINEERING
MANUSCRIPT SHOULD BE PUBLISHED
Complex linguistic term sarcasm is frequently used in social media and e-commerce websites. In Natural Language Processing applications like sentiment analysis and opinion mining, failure to recognise sarcastic utterances will confound classification algorithms and produce erroneous results. Numerous studies on the detection of sarcasm have used various learning methods. The majority of these learning methods, though,have always placed their primary attention solely on the expressed ideas, disregarding the context. AsAs a result, they missed the sarcastic expression's semantics and background information. Secondly,A word embedding learning technique is widely used in NLP deep learning approaches as a typical method for convolutional feature vector representation, which does not take into account the polarity of the words emotional connotations.To solve the challenges noted above, this work suggests a context-based feature technique for sarcasm identification using the deep learning model, BERT model, and traditional machine learning. For the categorization, two Twitter and Internet Argument Corpus, version two (IAC-v2) benchmark datasets were used.the three learning models are employed. The initial model makes use of deep learning and embedding-based representation.recurrent neural network with a bidirectional long short term memory (Bi-LSTM) (RNN),the development of word embedding and context using Global Vector representation (GloVe)learning. The second model is constructed using a pre-trained Bidirectional Encoder representation and is based on Transformer.both Transformer (BERT). The third model, by contrast, is based on the feature fusion of the BERT feature.a feature with sentiment-related, syntactic, and GloVe embedding

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. "SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 4 2022 Page 173-179
MLA ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. "SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA." International Journal Of Advance Research And Innovative Ideas In Education 8.4(2022) : 173-179.
APA ATHIRA K MENON, NEETHU P, & DR.G.KIRUTHIGA. (2022). SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA. International Journal Of Advance Research And Innovative Ideas In Education, 8(4), 173-179.
Chicago ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. "SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 4 (2022) : 173-179.
Oxford ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. 'SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 4, 2022, p. 173-179. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/SARCASM_DETECTION_USING_MACHINE_LEARNING_BY_TWITTER_DATA_ijariie17671.pdf (Accessed : ).
Harvard ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. (2022) 'SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA', International Journal Of Advance Research And Innovative Ideas In Education, 8(4), pp. 173-179IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/SARCASM_DETECTION_USING_MACHINE_LEARNING_BY_TWITTER_DATA_ijariie17671.pdf (Accessed : )
IEEE ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA, "SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 4, pp. 173-179, Jul-Aug 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/SARCASM_DETECTION_USING_MACHINE_LEARNING_BY_TWITTER_DATA_ijariie17671.pdf [Accessed : ].
Turabian ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. "SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 4 ().
Vancouver ATHIRA K MENON, NEETHU P, and DR.G.KIRUTHIGA. SARCASM DETECTION USING MACHINE LEARNING BY TWITTER DATA. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(4) : 173-179. Available from: https://ijariie.com/AdminUploadPdf/SARCASM_DETECTION_USING_MACHINE_LEARNING_BY_TWITTER_DATA_ijariie17671.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Real-Time Hand Gesture Recognition with Finger Counting (Using OpenCV and Mediapipe)Computer scienceBhumika Sahu Download
Diffie Hellman Key Exchange Algorithm with Man in the middle attack (MITM)Computer Science EngineeringMahesh Purushottam Gajbhiye Download
AN IMPROVED ATTRIBUTE BASED ACCESS CONTROL IN PERSONAL HEALTH RECORDS USING CLOUD WITH CONSTANT CIPHERTEXT LENGTHScience and TechBitrus Isahaka Dzarma Download
Driver Drowsiness Detection System By Measuring EAR and MARComputer Engineering Zoya Fatema Khan Download
Cloud-Based File Storage and Sharing Web ApplicationComputer Science & EngineeringMohammed Aadil Download
STUDYNEST: ONLINE LEARNING PLATFORM WITH AI RECOMMENDATION SYSTEMComputer Science and Engineering Urvashi Suresh Waghmare Download
Leveraging AWS for Developing and Hosting a Dynamic Food Ordering Web ApplicationComputer EngineeringAfshin Khanam Download
Edge-to-Cloud Synergy: An Autoencoder-GAN Framework for Anomaly Detection in Healthcare Records, Financial Statements, and Secure Cloud StorageInformation TechnologyKarthik Kushala Download
E-Commerce Fraud Detection Based on Machine Learning TechniquesComputer Science EngneeringVikram Ankush Ade Download
Detection of Phishing Website Using Gradient Boosting AlgorithmComputer Science and EngineeringYAWALKAR PRASAD PRAMOD Download
Property Dealing WebComputer Science EngineeringYash Chaudhari Download
Reinforcement Learning for the Evolution of Antimicrobial Nano formulationsmachine learningMadhusudan Download
SecuraVault: A secured blockchain based cloud storage systemComputer Engineering Anshika Jaiswal Download
Autoimmune Disease Detection in women Using Machine Learning Approachcomputer science EngineeringJ. L. V. S. Download
Medicine Overdose Detection System Using Machine LearningComputer Science EngineeringDr.Somashekhar B M Download
12