Among the general population, students are especially sensitive to social media and smartphones because of their pervasiveness. Several studies have shown that there is a negative correlation between social media and academic performance since they can lead to behaviors that hurt students' careers, e.g., addictedness. However, these studies either focus on smartphones and social media addictedness or rely on surveys, which only provide approximate estimates. We propose to bridge this gap by i) parametrizing social media usage and academic performance, and ii) combining smartphones and time diaries to keep track of users' activities and their smartphone interaction. We apply our solution on the 72 students participating in the SmartUnitn project, which investigates students' time management and their academic performance. By analyzing the logs of social media apps on students' smartphones while they are studying and attending lessons, and comparing them to students' credits and grades, we can provide a quantitative and qualitative estimate of negative and positive correlations. Our results show the negative impact of social media usage, distinguishing different influence patterns of social media on academic activities and underline the need to take it into account and control the smartphone usage in academic settings.

Recent studies have shown that there is a negative correlation between social media and academic performance, since they can lead to behaviours that hurt students' careers, e.g., addictedness. However, these studies either focus on smartphones and social media addictedness per se or rely on sociological surveys, which only provide approximate estimations of the phenomena. We propose to bridge this gap by i) parametrizing social media usage and academic performance and ii) combining smartphones and time diaries to keep track of users' activities and their smartphone interaction. By analyzing the logs of social media apps while studying and attending lessons, and comparing them to students' GPA, we can quantify negative and positive correlations via smartphones.