# Analysis of the Pre and Post-COVID-19 Lockdown Use of Smartphone Apps in Spain
## 1 Introduction  
The global pandemic of COVID-19 has led to confinement in homes in most countries in the world and has caused a change in smartphone usage habits. Undoubtedly, it has increased the time of use of the smartphones and their applications [1]. Indeed, a greater knowledge of the use of these devices, what applications are used, how the times of use change in the presence of an extraordinary event [1], etc. are not only a matter of academic interest, but also the key to understanding what mechanisms can effectively improve the users' experience, plan traffic in telecommunications networks [2] or help reduce the energy consumption of smartphones [3].  
Today, the use of the smartphone rises at a strong pace [4] and they have become much more than just a personal communication device. Social networks, leisure applications, games, etc. represent distractions that help users indulge to avoid feeling bored, lonely or depressed. However, screen time abuse and smartphone addiction can be a source of mental and physical problems. [PERSON] and [PERSON], 2005 [5], have pointed out that an excessive use of the smartphone may cause health problems such as headaches, fatigue, impaired concentration, insomnia, and hearing problems. It was also reported that some dimensions of personality such as low self-esteem, extraversion, higher approval motivation, and higher self-monitoring were more likely in people who suffer from smartphone addiction. In addition to these problematic behaviors, smartphone addiction can affect individuals' loneliness and work or academic performance [6]. An increase in smartphone use also carries an increase in vulnerability to outside security threats [7], potentially allowing hackers to gain access to personal information or private files, servers and programs.  
This study intends to gather and characterize data from Spanish smartphone users about their pre- and post-lockdown usage time during the first wave of COVID-19 in 2020, using unsupervised machine learning models and visualization techniques to provide insight on the effects caused by an unprecedented, high-impact social event such as the confinement.  
An attempt has not only been made to characterize the use of smartphones and their applications, through sociodemographic variables (age, sex), variables of a technological nature (version of the Android phone used) and psychological variables (addiction, personality, social digital pressure (SDP), depression and type of neighborhood where they reside), but it has also been studied if these variables have a significant impact on the time of use of the smartphone.  
We have analyzed the detailed usage traces of 1940 Android users residing in Spain, between January and May 2020, through a representative sample of the national population. By treating these data, it was possible to obtain, using machine learning techniques, a 2D distribution of the pre-COVID and post-COVID time of use, allowing the users to be clustered and analyzed in 4 groups based on their smartphone use. We assess and discuss the differences between the 4 clusters formed and how they relate to the variables of interest. In summary, this study tries to follow the methodology depicted in the flow diagram of Figure 1.  
The remaining of the paper is organized as follows. Section 2 explores related works and psychosocial indicators that could potentially lead to an increase in smartphone usage in critical situations, such as a home confinement. Section 3 describes the data used in our study: its source, the collection procedure, the participants' profiles and the statistical/exploratory analyses carried out. Section 4 introduces the machine learning and visualization techniques used for the data analysis and characterization. Section 4 presents the obtained results, followed by their discussion in Section 5.