Show and tell: Audience engagement in reporting on Covid-19 vaccination in data journalism-based media

Abstract

Data journalism is a new genre in journalism that utilizes data visualization to engage the audience in news reporting. This engagement also provides certainty and minimizes the spread of misinformation regarding the COVID-19 vaccination policy in Indonesia. This study aims to explain how data journalism-based media, which is Katadata.co.id, communicates their news and embodies audience engagement through data visualization. The type of research is content analysis with quantitative and qualitative data collection techniques. In quantitative data collection, 49 news titles were searched, which were the results of keyword discovery in January-March 2021 in the “Data Journalism” rubric of Katadata.co.id. The data were coded according to indicators from a multimodal perspective in the concept of ergodic work, which are static information graphs, non-interactive dynamic data visualizations, and interactive dynamic data visualizations. Furthermore, in the qualitative step, the data was analyzed in-depth to explore how Katadata.co.id communicated news about COVID-19 vaccination with the showing and telling models. As a result, the COVID-19 vaccination news on Katadata.co.id also involved the audience in communicating it. In reporting the news, Katadata.co.id uses narrative techniques, which is the instance of narrators technique to characterize the narrative through the presence of news writers, the sequentiality technique to show the movement from one event to another by sliding the pages, the temporal dimension technique to describe the changes over the time with the help of dynamic elements, and tellability techniques to describe the worth-presenting COVID-19 vaccination news.

Keywords

• data visualization, data journalism, covid-19 vaccination, martini glass, multimodal