Abstract
The dataset contains user engagement and language-related information from two audio story-producing channels on YouTube. It offers a comparative view of live and mediated engagements, which includes information pertinent to the user's interaction of audio-story based YouTube contents. The speciality of this dataset is the inclusion of textual data of live comments on YouTube videos. It covers the data from July 2022 to February 2024 yielding 230 audio stories of the respective channels. More than 250,000 comments and nearly 300,000 live chats from the videos are included in this dataset. It provides quantitative information of the contents such as number of views, comments and likes. Along with the textual data and numerical engagement-related data, this dataset contains the language categorization of the users' comments. It is expected that this dataset will be used in further research producing novel insights in different disciplines, uncovering patterns of digital engagement, language use in different platforms, and the dynamics of live versus post-live interactions. Additionally, content creators and marketers can utilize insights from this dataset to optimize their strategies for audience engagement. The dataset serves as a valuable resource for cross-disciplinary studies in digital media, linguistics, and social media analysis.