ANALISIS SENTIMEN TERHADAP ISU FEMINISME DI TWITTER MENGGUNAKAN MODEL CONVOLUTIONAL NEURAL NETWORK (CNN) - Brescia Ayundina Yuniarossy; Kartika Maulida Hindrayani; Aviolla Terza Damaliana (Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 2024)
The development of technology is very significant in various fields, especially in the field of digital technology. Sentiment analysis of feminism issues on Twitter tends to be significant in understanding public opinion, especially Twitter users. Being a place for people to vent, Twitter spreads the message of those who tweet to a wide audience and it often happens that a tweet becomes an influence on public opinion. Twitter can be a tool to find out public sentiment towards a figure, group, and organization. Feminism is a movement to voice the rights of a human being to be equal regardless of gender. In this study, a Convolutional Neural Network (CNN) approach is used to analyze sentiment towards the issue of feminism on Twitter. The data collected from Twitter contains a variety of conversations, opinions, and views on feminism. By building and training a CNN model that is able to process text data and classify sentiment based on each tweet. By applying the CNN model, it aims to identify sentiment patterns towards Twitter users on the issue of feminism, especially the topics of domestic violence and sexual harassment. Where these two topics will be discussed in this research. Another goal is to provide valuable insights for researchers, activists, and policy makers in understanding the dynamics of public opinion on the issue of domestic violence and sexual harassment. The results of this sentiment analysis are expected to make a significant contribution to supporting discussions on social issues on social media