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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Understanding and predicting the success lifecycle of an influencer |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2023 |
| Abstract Text | Although influencer marketing has been experiencing tremendous growth, and many firms have been trying to find the right influencers for their marketing campaigns, there has been little research on identifying the timing of the high-impact work or analyzing the hot streak periods of influencers on social media. My thesis is among the first works in this area on the TikTok platform where I applied some methods used in previous literature. All the analyses were made using the video-level popularity metrics of TikTok: “number of likes”, “number of shares”, “number of plays”, and “number of comments”. In addition, unlike other studies, I created the visualization of the hot streak durations of TikTok authors to analyze information such as the start, and end time of hot streaks, or the length of hot streaks for each author. All plots for the analyses were built with bokeh- a Python library for interactive data visualizations. In conclusion, with the dataset in my thesis study, first I found that the timing of the most popular video is random in TikTok users’ lifecycles. Second, I discovered that the timing of the biggest hit and the second hit are close to each other, so TikTok authors may experience average success close to their most popular videos. Third, I detected a pattern indicating that TikTok authors use more diverse hashtags during hot streak periods than before them. Lastly, I observed that the relative hot streak length -success duration- of an author is usually between 12% and 50%. As a result, marketers can use these observations in my thesis to identify successful influencers on the TikTok platform. Finally, the formulas and visualization methods used in my thesis can be applied to a larger TikTok dataset or other datasets from other social media platforms such as Instagram, or YouTube. |
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