Analyzing nomophobia among TikTok users: a data mining and text analysis approach

Abstract This study aims to investigate the phenomenon of nomophobia (fear of being without a mobile phone) among TikTok users from various countries. The study analyzes a dataset of TikTok posts from December 2020 to December 2022, employing volume analysis, keyword and latent distribution analysis (LDA), and sentiment analysis. These methods are utilized to explore the dynamics and nuances of discussions related to nomophobia among a global user base The findings indicate a growing concern about nomophobia across different demographics, with variations in discussion intensity influenced by events such as new smartphone releases and digital well-being campaigns. For example, the release of major smartphone models often coincided with spikes in discussions, as did popular awareness campaigns advocating for reduced screen time. Sentiment analysis reveals a predominantly positive attitude towards managing digital dependency, with a larger proportion of posts expressing positive sentiment compared to negative sentiment. Notably, spikes in positive sentiment were observed during digital well-being campaigns, indicating an increasing trend in proactive discussions around smartphone use. Negative sentiments are mainly linked to the stress and anxiety associated with smartphone usage, while positive sentiments highlight efforts towards digital well-being and responsible online behavior. The study concludes that social media platforms, especially TikTok, are effective in disseminating information and shaping public perception about nomophobia. It suggests that more personalized, bottom-up approaches to digital health communication and strategic utilization of influencer narratives could better engage the public, particularly youth, and promote practical steps towards managing digital dependency.