Call for Papers:Vol.12 Issue.2

Submission
Last date		 28-Apr-2026
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-12,Issue-2. 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: :  A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH
PaperId: :  13981
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 7 Issue 2 2021
DUI:    16.0415/IJARIIE-13981
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
P.KALADEVIK.S.RANGASAMY COLLEGE OF TECHNOLOGY
K.KOWSICKK.S.RANGASAMY COLLEGE OF TECHNOLOGY

Abstract

COMPUTER SCIENCE AND ENGINEERING
Identify Hate speech in Twitter, Machine Learning.
Classification options were derived from the content of every tweet, as well as grammatical dependencies between words to acknowledge “othering” phrases, incitement to reply with antagonistic action, and claims of sensible or even discrimination against social teams. The results of the classifier were best employing a combination of probabilistic, rule-based, and spatial-based classifiers with a voted ensemble meta-classifier. I incontestible however the results of the classifier will be robustly utilised during a applied math model wont to forecast the seemingly unfold of cyber hate during a sample of Twitter information. The applications to policy and deciding ar mentioned. I planned a cooperative multi-domain sentiment classification approach to coach sentiment classifiers for multiple domains at the same time. In our approach, the sentiment info in numerous domains is shared to coach a lot of correct and strong sentiment classifiers for every domain once labelled information is scarce. Specifically, I decompose the sentiment classifier of every domain into 2 parts, a world one and a domain-specific one. the worldwide model will capture the overall sentiment information and is shared by varied domains. The domain-specific model will capture the precise sentiment expressions in every domain. additionally, we tend to extract Tri_Model(Naive mathematician IBK,SVM)sentiment information from each labeled and unlabeled samples in every domain and use it to reinforce the educational of Tri_Model ( Naive bayes,IBK,SVM)sentiment classifiers. Besides, we tend to incorporate the similarities between domains into my approach as regularization over the Tri_Model(Naïve bayes mathematician IBK,SVM)sentiment classifiers to encourage the sharing of sentiment info between similar domains. 2 styles of domain similarity measures ar explored, one supported matter content and therefore the different one supported sentiment expressions. Moreover, I introduce 2 economical algorithms to resolve the model of our approach. Experimental results on benchmark datasets show that our approach will effectively improve the performance of multi-domain sentiment classification and considerably vanquish baseline ways.

Citations

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

IJARIIE P.KALADEVI, and K.KOWSICK. "A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH" International Journal Of Advance Research And Innovative Ideas In Education Volume 7 Issue 2 2021 Page 969-974
MLA P.KALADEVI, and K.KOWSICK. "A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH." International Journal Of Advance Research And Innovative Ideas In Education 7.2(2021) : 969-974.
APA P.KALADEVI, & K.KOWSICK. (2021). A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH. International Journal Of Advance Research And Innovative Ideas In Education, 7(2), 969-974.
Chicago P.KALADEVI, and K.KOWSICK. "A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH." International Journal Of Advance Research And Innovative Ideas In Education 7, no. 2 (2021) : 969-974.
Oxford P.KALADEVI, and K.KOWSICK. 'A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH', International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 2, 2021, p. 969-974. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_MACHINE_LEARNING_METHOD_TO_IDENTIFY_HATE_SPEECH_USING_TRIMODEL_APPROACH_ijariie13981.pdf (Accessed : ).
Harvard P.KALADEVI, and K.KOWSICK. (2021) 'A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH', International Journal Of Advance Research And Innovative Ideas In Education, 7(2), pp. 969-974IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_MACHINE_LEARNING_METHOD_TO_IDENTIFY_HATE_SPEECH_USING_TRIMODEL_APPROACH_ijariie13981.pdf (Accessed : )
IEEE P.KALADEVI, and K.KOWSICK, "A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH," International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 2, pp. 969-974, Mar-App 2021. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_MACHINE_LEARNING_METHOD_TO_IDENTIFY_HATE_SPEECH_USING_TRIMODEL_APPROACH_ijariie13981.pdf [Accessed : ].
Turabian P.KALADEVI, and K.KOWSICK. "A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 7 number 2 ().
Vancouver P.KALADEVI, and K.KOWSICK. A MACHINE LEARNING METHOD TO IDENTIFY HATE SPEECH USING TRIMODEL APPROACH. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2021 [Cited : ]; 7(2) : 969-974. Available from: https://ijariie.com/AdminUploadPdf/A_MACHINE_LEARNING_METHOD_TO_IDENTIFY_HATE_SPEECH_USING_TRIMODEL_APPROACH_ijariie13981.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
JANMITRA - AI POWERED PLATFORM BRIDGING SOCIETIES WITH NGO'S AND ORGANIZATIONScomputer engineeringUMESH AAGDE Download
Improvising Personalized Travel Recommendation System with Recency Effectscomputer science engineeringMrs. Fathima Zahera Download
Ensemble Models and Explainable AI for Malware DetectionComputer Science M Vandana Download
Smart E-Healthcare SystemComputer EngineeringVattikoti Sai Download
SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPSComputer EngineeringAmalkrishna K B Download
SMART COLLEGE SECURITY:AI-POWERED IDCARD VIOLATION AND FACE RECOGNITIONSYSTEMComputer science Athira Thomas Download
Consumer Behavioural Analysis Using Advanced Clustering TechniquesComputer Science and EngineeringSupriya Thati Download
A Low-Cost Smartphone-Based Sign Language Translator Using Computer Vision for Real-Time Deaf–Hearing CommunicationComputer Science and EngineeringHarsh Mishra Download
Predicting Stock Market Trends using Deep Learning TechniquesComputer Science and EngineeringAkruthi Shere Download
A SURVEY ON SMART VOTING SYSTEM USING BLOCKCHAINComputer Science EngineeringAleena Shaju Download
A SURVEY ON SECURESCAN 360: CYBER INTEGRATED SYSTEM FOR THREAT DETECTION AND IMAGE AUTHENTICATIONComputer Science and EngineeringAparna Sunil Download
Efficient Use of Dialog Boxes in GUI Development using VB.NETComputer ScienceDR. RISHI MATHUR Download
A SURVEY ON HOPEBITE: AI-POWERED SMART FOOD DISTRIBUTION FOR COMMUNITIES IN NEEDComputer Science and EngineeringJUGAL KRISHNA V S Download
A SURVEY ON ACCIDENT DETECTION AND AUTOMATED EMERGENCY NOTIFICATION SYSTEM USING YOLO V8Computer EngineeringVipin Varghese Download
INVISIBLE DISABILITY AND ROUTINE WELLNESS TRACKERComputer Science and EngineeringAnna Rose Poly Download
12