Hate Speech Hashtag Classification Using Hybrid Artificial Neural Network (ANN) Method

  • Aryasatya L
  • Sibaroni Y
N/ACitations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

Social networking sites Twitter is frequently used as a platform for information gathering various communities/forums as well as individuals to discuss certain things. Dissemination of information on Twitter can be in the form of positive information and negative information. One of the negative information is hate speech contained in the form of hashtags on twitter. Hate Speech Hashtag Classification was be carried out using the Hybrid Artificial Neural Network (ANN) method to produce satisfactory results compared to previous methods such as KNN and so on because the large amount of data in Twitter will be very profitable and produce good accuracy when using Hybrid Learning, Hybrid Learning with 5 Cross Validation the highest accuracy is 79% , the lowest is 73%, the average accuracy is 76%.

Cite

CITATION STYLE

APA

Aryasatya, L., & Sibaroni, Y. (2022). Hate Speech Hashtag Classification Using Hybrid Artificial Neural Network (ANN) Method. JURIKOM (Jurnal Riset Komputer), 9(4), 784. https://doi.org/10.30865/jurikom.v9i4.4425

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free