Call for Papers:Vol.9 Issue.6

Submission
Last date		 30-Dec-2023
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-9,Issue-6. 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
COMPREHENSIVE SURVEY ON IMPACT OF ARTIFICIAL INTELLIGENCE IN BANKINGCSEAbdul Gafoor K Download
Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic StrategiesComputer ScienceDr. Bhavesh M. Patel Download
TOKENIZATION TECHNIQUES IN NLP:A COMPREHENSIVE REVIEWComputer ScienceDr. Bhavesh M. Patel Download
COMPREHENSIVE SURVEY OF EFFECTIVE PREDICTION MODEL OF CRM AND CUSTOMERS BY USING ARTIFICIAL INTELLIGENCECSEKumar Abhishek Download
ANALYSIS OF EFFECTIVE PREDICTION MODEL OF CRM AND CUSTOMERS BY USING ARTIFICIAL INTELLIGENCECSEKumar Abhishek Download
IMPROVING THE ACCURACY OF BUSINESS RECOMMENDATION SYSTEM USING DISTANCE METRIC TECHNIQUESComputer ScienceMustapha Maidawa Download
A REVIEW ON MACHINE LEARNING TECHNIQUES IN CORONARY ARTERY DISEASE: CHALLENGES AND FUTURE DIRECTIONComputer ScienceAbi Izang Igyem Download
COTTON LEAF DISEASE DETECTIONSCOMPUTER SCIENCE AND ENGINEERING M. SENTHIL KUMAR Download
ProductPulseComputer EngineeringProf. Ravishankar. C. Bhaganagare Download
YOLOV3-BASED OBJECT DETECTION FOR VISUALLY IMPAIREDCOMPUTER ENGINEERINGMJ SHASHANK Download
Detection of Android Malware Using Multiple Linear Regression Models-Based Classifierscomputer EngineeringM. Parkavi Download
OPERATING SYSTEM DEVELOPMENT BASED ON OPEN SOURCE SOFTWARE IN OLINE LEARNING SYSTEM-A REVIEWcomputer EngineeringG.TAMILSELVAN Download
Food Image Processing Using Deep LearningImage Processing, Artificial IntelligenceT. Sai Sindhuja Download
Artificial Neural Network-based Fault Detection and Classification for Photovoltaic SystemElectrical EngineeringP Manmadha Reddy Download
Advanced CCTV Analytic Solution for Fire DetectionComputer Science EngineeringPONRASU T Download
12