Classification Crisis Communication: Semiotic Approach with Latent Semantic Analysis

Abstract

Previous crisis communication research has been based on qualitative methods such as interviews or questionnaires, which require considerable manpower, material resources, and time to focus on specific topics. The current situation needs to be reflected timelier. With the rise of social communities, community users’ comments have gradually become an important reference for other community members. Twitter is one of the most popular social media in the world. During the COVID-19 pandemic, people were restricted by rules and government policies, such as wearing masks, maintaining social distancing, and avoiding crowding. This led people to spend time on devices. By using devices, most people are involved in social media activities. This study aims to discover the awareness Indonesians display in the text they upload to Twitter. Using the Twitter crawling technique, we collected data. We also analyzed the text with text mining techniques and latent semantic analysis (LSA) with semiotic methods. The crisis communication was classified, and the definition of crisis terminology was improved in social media.