Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data
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 spec...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924011818 |
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| _version_ | 1832576515195273216 |
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| author | Mohammad Harun Or Rashid Md Tanbeer Jubaer Barisha Chowdhury Md Minhazul Islam |
| author_facet | Mohammad Harun Or Rashid Md Tanbeer Jubaer Barisha Chowdhury Md Minhazul Islam |
| author_sort | Mohammad Harun Or Rashid |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e3320d669caf4064b4e24aae16eaf0e4 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-e3320d669caf4064b4e24aae16eaf0e42025-01-31T05:11:32ZengElsevierData in Brief2352-34092025-02-0158111219Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley DataMohammad Harun Or Rashid0Md Tanbeer Jubaer1Barisha Chowdhury2Md Minhazul Islam3Department of Humanities, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh; Corresponding author.Department of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshDepartment of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshDepartment of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshThe 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.http://www.sciencedirect.com/science/article/pii/S2352340924011818Social media studyAudio storyUser commentsUser engagementsLive commentsBangla language |
| spellingShingle | Mohammad Harun Or Rashid Md Tanbeer Jubaer Barisha Chowdhury Md Minhazul Islam Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data Data in Brief Social media study Audio story User comments User engagements Live comments Bangla language |
| title | Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data |
| title_full | Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data |
| title_fullStr | Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data |
| title_full_unstemmed | Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data |
| title_short | Live and mediated user engagements: A comparative dataset from two Bengali audio-story based youtube channelsMendeley Data |
| title_sort | live and mediated user engagements a comparative dataset from two bengali audio story based youtube channelsmendeley data |
| topic | Social media study Audio story User comments User engagements Live comments Bangla language |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924011818 |
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