In the current digital era, the development of information technology is growing rapidly. The development of information technology is followed by the development of social media, one of the social media that is on the rise is Twitter. Because there are many Twitter users around the world, Twitter stores a lot of data that can be used for something, one of which is to determine the category of public opinion about a company or university, in this study the focus is more on the category of public opinion about Telkom University. The public opinion can be grouped or categorized to make it easier to determine the topic being discussed. Determining opinions manually will take a long time due to the large number of tweets. Therefore, there must be another method to determine the categories of public opinion on Twitter. One of them is the Latent Dirichlet Allocation (LDA) method with a dataset of tweets of Indonesian-language Twitter users. With this method, grouping tweets on a large scale is more efficient. From the modeling made, the most optimum results obtained with a coherence score using the c_umass method of -15.33029 with a combination of 9 topics, 0.31 alpha value, and 0.01 beta value.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.