# Predicting Phubbing Through Machine Learning: A Study of Internet Usage and Health Risks
## 1 Introduction  
The concept of phubbing first emerged in the early 2010s and has rapidly become widespread with digitalisation in modern society. In particular, the fact that mobile devices are at the centre of our daily lives makes it important to understand the effects of this behaviour on individuals and communities. However, there are not enough studies on the long-term social and psychological effects of phubbing in the existing literature. This study aims to fill this gap in the literature, to predict the potential future risks of phubbing, andto raise public awareness. The findings of this study will enable the development of new strategic approaches for both academic circles and policymakers. Phubbing refers to individuals neglecting their social ties by focussing on their mobile phones instead of face-to-face interaction with the people around them. This behaviour, which is becoming increasingly common today, can have negative effects on both psychological and physical health. Phubbing can lead to feelings of insecurity, alienation, and loneliness in interpersonal relationships, while increasing stress and anxiety levels due to a lack of social support. In addition, physical health problems such as sleep disorders, eye strain, and posture disorders may also occur due to constant phone use. Therefore, it is clear that phubbing negatively affects both social relationships and the general health of individuals; therefore, it is an important issue that needs attention in modern society. In parallel with the changes in technology, communication tools and forms have also changed, and the internet and digital-based communication tools have become a constant part of daily and social life [1; 2; 3; 4]. In particular, portable phones, which provide instant interaction independently of space and time and are constantly connected to the online network, have a strong impact on people's social relationships and daily lives [5; 6]. The main reason for this impact is that individuals increasingly use the internet to communicate with friends, family, or colleagues or meet strangers [7], to have fun, to engage in hobbies and play games [8], or to obtain information, learn, and research [9]. Several studies have utilised advanced machine learning techniques for time series forecasting [10; 11]. However, few have applied these methods to understand the socio-behavioural implications of internet usage, as addressed in this study. Our research builds on these works by leveraging machine learning models to explore the long-term effects of digital behaviours like phubbing. Individuals tend to prefer smartphones to computers for internet use [12]. In China, mobile phones are a prevalent tool for internet access, with over 97% of online users relying on them to connect to the web. On the other hand, in Turkey, 73.5% of internet traffic is generated through mobile devices [13]. Although these high usage rates are mainly due to the obvious benefits of smartphones, such as comfort and convenience, especially in recent years, researchers and scientists have begun to examine the harm that they cause to mental and physical health. In addition to this harm, there has been growing concern about the potential negative effects of smartphones on the quality of social interactions and relationships [14; 15; 16; 17]. One of the negative effects that arises due to intensive smartphone use is the concept of \"phubbing\", the act of focusing on the smartphone instead of the person being interacted with in a disrespectful and condescending manner during social interaction. Phubbing is a term derived by combining the terms \"phone\" and \"snubbing\", while \"being phubbed\" means being ignored and belittled by someone who uses their cell phone while in the company of others [18]. The negative consequences for social relationships are broad and deep, including romantic partners [18] or parents [17].