Implementation of Backpropagation Neural Network in Sentiment Analysis on Twitter to Public Figures

Abstract

Sentiment analysis is a process for identifying or analyzing people's opinions on a topic. Sentiment analysis analyzes each word in a sentence to find out the opinions or sentiments expressed in the sentence. The opinions expressed can be in the form of positive or negative opinions. Twitter is one of the most popular social media in Indonesia. Twitter users always discuss various kinds of topics every day. One of the things discussed on Twitter and which has become a trending topic several times is about public figures. This study discusses the analysis of positive or negative sentiments towards public figures based on tweet data carried out by text processing. The results of text processing are classified using a backpropagation neural network. Tests were carried out using 69 test data, resulting in an accuracy of 62.3%, with 43 correct classification results.

Social Network Text Sentiment Analysis Method Based on CNN-BiGRU in Big Data Environment

“…Te topics pushed by the Internet in real time and the infnity of Internet users' comments and forwarding make the speed of public opinion propagation very fast. Terefore, for a topic, Internet users are easy to generate polarization of groups and even lead to group events on the Internet or in real life [3,4]. Te comment sentiment expressed by Internet users will not only afect the spread of public opinion on the whole topic but the users' sentiments will be afected by other users.…”