YULYANA, ESTHER and Kunto, Yohanes Sondang and Yuliana, Oviliani Yenty (2025) An Innovative Business Intelligence Modelling Approach on The Effects of Social Media Features on User Engagement. [UNSPECIFIED]
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Abstract
The intensity of today�s social media landscape is unparalleled, with platforms that have evolved beyond basic messaging to include features such as story sharing, video content, shopping, and more. These are all in a bid to enhance user engagement. Although the effect of social media features on user engagement has been studied before, most of these studies have relied on in-person interviews, which can change the natural setting and unintentionally introduce response biases. This research adopted a different approach by utilizing observational data to analyze whether specific features influence user engagement. Data were from SEMrush and covered a time series of 2�60 points of user engagement metrics from two popular social media platforms in Indonesia: Instagram and TikTok. We retrospectively searched for credible references to determine when each feature was first introduced on these platforms. We used monthly fixed-effects regressions with robust standard errors to model the relationship between social media features and two metrics of user engagement: average visit duration and bounce rate. Our findings reveal diverse effects of features on user engagement. For instance, introducing a shopping feature increased the average visit duration of Instagram users, but conversely, a similar feature degraded the user engagement of TikTok users. Such intriguing patterns are discussed further in the paper.
Item Type: | UNSPECIFIED |
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Additional Information: | Paper sudah dipublish di IEEE Explorer, saat ini sedang menunggu terindex scopus sesuai dengan janji ICBIM 2024 https://www.icbim.org/index.html |
Subjects: | Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science H Social Sciences |
Divisions: | Graduate Program > Economic Management |
Depositing User: | Admin |
Date Deposited: | 11 Jan 2025 07:14 |
Last Modified: | 13 Jan 2025 16:32 |
URI: | https://repository.petra.ac.id/id/eprint/21364 |
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