Likes and Fragments: Examining Perceptions of Time Spent on TikTok
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929257036382208 |
|---|---|
| author | Goetzen, Angelica Wang, Ruizhe Redmiles, Elissa M. Zannettou, Savvas Ayalon, Oshrat |
| author_facet | Goetzen, Angelica Wang, Ruizhe Redmiles, Elissa M. Zannettou, Savvas Ayalon, Oshrat |
| contents | Researchers use information about the amount of time people spend on digital media for numerous purposes. While social media platforms commonly do not allow external access to measure the use time directly, a usual alternative method is to use participants' self-estimation. However, doubts were raised about the self-estimation's accuracy, posing questions regarding the cognitive factors that underline people's perceptions of the time they spend on social media. In this work, we build on prior studies and explore a novel social media platform in the context of use time: TikTok. We conduct platform-independent measurements of people's self-reported and server-logged TikTok usage (n=255) to understand how users' demographics and platform engagement influence their perceptions of the time they spend on the platform and their estimation accuracy. Our work adds to the body of work seeking to understand time estimations in different digital contexts and identifies new influential engagement factors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_02041 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Likes and Fragments: Examining Perceptions of Time Spent on TikTok Goetzen, Angelica Wang, Ruizhe Redmiles, Elissa M. Zannettou, Savvas Ayalon, Oshrat Computers and Society Researchers use information about the amount of time people spend on digital media for numerous purposes. While social media platforms commonly do not allow external access to measure the use time directly, a usual alternative method is to use participants' self-estimation. However, doubts were raised about the self-estimation's accuracy, posing questions regarding the cognitive factors that underline people's perceptions of the time they spend on social media. In this work, we build on prior studies and explore a novel social media platform in the context of use time: TikTok. We conduct platform-independent measurements of people's self-reported and server-logged TikTok usage (n=255) to understand how users' demographics and platform engagement influence their perceptions of the time they spend on the platform and their estimation accuracy. Our work adds to the body of work seeking to understand time estimations in different digital contexts and identifies new influential engagement factors. |
| title | Likes and Fragments: Examining Perceptions of Time Spent on TikTok |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2303.02041 |