This master’s thesis examines the factors influencing the virality of videos published by Slovenian companies on the social media platform TikTok. The main objective of the study was to determine the extent to which content-related and technical characteristics of videos contribute to their performance, measured through views, likes, shares, and comments. The empirical part is based on a quantitative analysis of 384 videos, which were coded according to selected content and technical variables. Multiple linear regression analysis and analysis of variance (ANOVA) were used to test the hypotheses, while logistic regression analysis was additionally applied to assess the probability of video virality. The results indicate that content characteristics such as entertainment value, storytelling, practical value, and positive emotions do not have a statistically significant impact on most performance indicators. In contrast, the number of followers, as a technical factor, shows a statistically significant positive effect across all observed metrics and increases the likelihood of a video becoming viral. Negative emotions were found to significantly increase user engagement in the form of comments. The findings suggest that virality on TikTok cannot be explained solely by content, but rather represents a combination of multiple factors, including audience size, platform algorithms, and user interactions. The study contributes to a better understanding of TikTok as a marketing tool and provides practical insights for companies in developing effective content strategies.
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