Analisis Bibliometrik Tren Penelitian Gerakan Opini Digital di Media Sosial

Abstract

Popular social media platforms such as Instagram, X (formerly Twitter), Facebook, and TikTok not only function as a digital public sphere for people to start discussions, but also become an arena for mobilizing various social and political movements thanks to the speed and wide reach of social media. In this context, the Digital Movement Opinion (DMO) or digital opinion movement is present as an articulation of public opinion that is mobilized through uploads, comments, and the use of certain hashtags on an issue on social media. This movement can influence policy, public opinion, and social change. Over time, the number of studies on digital opinion movements on social media has increased every year. However, these studies are still scattered with various approaches and disciplines, and have not been systematically mapped in a complete bibliometric analysis framework. The purpose of this study is to identify and map research trends on digital opinion movements on social media. This study uses a bibliometric analysis method with a quantitative approach. Data collection in this study uses the help of Publish or Perish software to obtain journal article data from the Google Scholar and Crossref databases with the keywords "digital opinion movement" and "social media" in the 2015-2025 period. The research findings found 227 articles discussing digital opinion movements with 222 authors and 4072 different keywords. The trend of digital opinion movement research shows a positive trend, while the visualization map based on keywords produces three clusters and the authors are divided into five clusters. The keywords 'medium', 'hashtag', 'digital movement opinion', and 'social media twitter' are research topics that are widely studied by researchers and are still hot topics. Meanwhile, the keywords 'gephi', 'instagram', 'response', 'interaction', 'relationship', 'sna', 'social media user', 'message' and 'opinion mobilization' are keywords that have not been widely used or studied in digital opinion movement research.