Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour
TikTok’s recommendation algorithm has created a novel user experience. Guided by existing literature on algorithmic personalisation, this study investigated the relationship between algorithmically-curated content on TikTok, Gen Z TikTok users’ self-concepts, and their consumer behaviours. Based on...
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sg-ntu-dr.10356-1744892024-04-07T15:37:05Z Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour Yupar, Tin Win Tan, Misa Li Sin Kang Hyunjin Wee Kim Wee School of Communication and Information hjkang@ntu.edu.sg Other Algorithms TikTok’s recommendation algorithm has created a novel user experience. Guided by existing literature on algorithmic personalisation, this study investigated the relationship between algorithmically-curated content on TikTok, Gen Z TikTok users’ self-concepts, and their consumer behaviours. Based on a series of in-depth interviews with 18 Gen Z TikTok users, this study delved into how TikTok’s algorithmically-curated content reflects and influences Gen Z’s self concept. The study also explored how the algorithmically-influenced self-concept in turn influences Gen Z TikTok users’ consumer behaviours. It was found that many Gen Z TikTok users were keenly aware of the algorithm and its workings. They attempted to influence the algorithm such that it better aligns with their self-concept. Their algorithmically-curated content feeds reflected various aspects of their self-concepts, with their interactions with the content playing a role in influencing their feed. Algorithmically-curated content had a notable influence on their self-concepts, though some perceived otherwise. It was also found the algorithmically-influenced self-concept played a role in influencing consumer behaviour, particularly purchase behaviour. These findings advance our understanding of the dynamics between algorithms, self-concept and consumer behaviour, and highlight the power of algorithms in shaping users’ internal perceptions and external behaviours. Bachelor's degree 2024-04-01T01:50:27Z 2024-04-01T01:50:27Z 2024 Final Year Project (FYP) Yupar, T. W. & Tan, M. L. S. (2024). Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/174489 https://hdl.handle.net/10356/174489 en SCI23023 application/pdf Nanyang Technological University |
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Other Algorithms Yupar, Tin Win Tan, Misa Li Sin Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
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TikTok’s recommendation algorithm has created a novel user experience. Guided by existing literature on algorithmic personalisation, this study investigated the relationship between algorithmically-curated content on TikTok, Gen Z TikTok users’ self-concepts, and their consumer behaviours. Based on a series of in-depth interviews with 18 Gen Z TikTok users, this study delved into how TikTok’s algorithmically-curated content reflects and influences Gen Z’s self concept. The study also explored how the algorithmically-influenced self-concept in turn influences Gen Z TikTok users’ consumer behaviours. It was found that many Gen Z TikTok users were keenly aware of the algorithm and its workings. They attempted to influence the algorithm such that it better aligns with their self-concept. Their algorithmically-curated content feeds reflected various aspects of their self-concepts, with their interactions with the content playing a role in influencing their feed. Algorithmically-curated content had a notable influence on their self-concepts, though some perceived otherwise. It was also found the algorithmically-influenced self-concept played a role in influencing consumer behaviour, particularly purchase behaviour. These findings advance our understanding of the dynamics between algorithms, self-concept and consumer behaviour, and highlight the power of algorithms in shaping users’ internal perceptions and external behaviours. |
author2 |
Kang Hyunjin |
author_facet |
Kang Hyunjin Yupar, Tin Win Tan, Misa Li Sin |
format |
Final Year Project |
author |
Yupar, Tin Win Tan, Misa Li Sin |
author_sort |
Yupar, Tin Win |
title |
Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
title_short |
Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
title_full |
Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
title_fullStr |
Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
title_full_unstemmed |
Algorithmic personalisation on TikTok and its effect on Gen Z's self-concept and consumer behaviour |
title_sort |
algorithmic personalisation on tiktok and its effect on gen z's self-concept and consumer behaviour |
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Nanyang Technological University |
publishDate |
2024 |
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https://hdl.handle.net/10356/174489 |
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1814047240672509952 |