Text Summarization Application for Indonesian Twitter Document by Using Top-N Feature Selection Algorithm
Zul Indra, Yessi Jusman, Doni Winarso · 2020
The rapid development of information technology has changed many things in our lives. One of the most influential technological developments in our lives is the emergence of the internet. One of the phenomenal examples in the world of information technology is the existence of social media services. This service has replaced the habit of people looking for information and writing down its expressions. With a very high data growth rate, it has raised new problems for Twitter users. The large number of tweets sometimes causes difficulties in understanding the information. To solve this problem, one solution that can be applied is to summarize the information circulating on Twitter. Text summarization is a field of study in natural language processing (NLP). This algorithm aims to reduce the number of words in a document so that the information is easier to understand. NLP can be used to help us summarize tweet documents so that they are easier to understand. This study aims to develop tweet summarization software using the top-n feature selection algorithm. Based on the experiment that has been done, the application has succeeded in summarizing the tweet document by displaying the terms that have the highest weight. Hence, users can more quickly understand information from Twitter without having to read the entire tweet document.