Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channels.

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-12-10 eCollection Date: 2025-02-01 DOI:10.1016/j.dib.2024.111219

Mohammad Harun Or Rashid, Md Tanbeer Jubaer, Barisha Chowdhury, Md Minhazul Islam

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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.

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现场和中介用户参与：来自两个基于孟加拉语音频故事的youtube频道的比较数据集。

数据集包含 YouTube 上两个音频故事制作频道的用户参与和语言相关信息。该数据集提供了现场参与和中介参与的比较视图，其中包括用户与基于音频故事的 YouTube 内容互动的相关信息。该数据集的特别之处在于包含了 YouTube 视频现场评论的文本数据。它涵盖了从 2022 年 7 月到 2024 年 2 月的数据，产生了 230 个相关频道的音频故事。该数据集中包含来自视频的 250,000 多条评论和近 300,000 次实时聊天。它提供了内容的量化信息，如浏览量、评论和点赞数。除了文本数据和数字参与相关数据外，该数据集还包含用户评论的语言分类。预计该数据集将用于进一步的研究，为不同学科提供新的见解，揭示数字参与的模式、不同平台的语言使用以及直播与直播后互动的动态。此外，内容创建者和营销人员还可以利用该数据集的见解来优化其受众参与策略。该数据集是数字媒体、语言学和社交媒体分析等跨学科研究的宝贵资源。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.