Behavior diffusion through social networks is a key social process. It may be guided by various factors such as network topology, type of propagated behavior, and the strength of network connections. In this paper, we claim that the type of social interactions is also an important ingredient of behavioral diffusion. We examine the spread of academic achievements of first-year undergraduate students through friendship and study assistance networks, applying stochastic actor-oriented modeling. We show that informal social connections transmit performance while instrumental connections do not. The results highlight the importance of friendship in educational environments and contribute to debates on the behavior spread in social networks.

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Peer group effects show the influence of student social environments on their individual achievements. Traditionally, a social environment is considered by researchers of peer effects as exogenously given. However, significant peers that affect performance are often those that are deliberately chosen. Students might choose their friends among peers with similar academic achievements. A dynamic analysis of student social networks and academic achievements is needed to disentangle social selection and social influence processes in network formation. Using data about the friendship and advice networks of first year undergraduate students, we show that friends tend to assimilate each others' achievements and choose advisers with similar grades. We explain these results by social segregation based on student performance. The article contributes to the dynamic analysis of student social networks and the understanding of the nature of peer group effects in education.

The introduction of digital technologies in everyday practices and the reduction of the age of children's access to the Internet creates the need to reflect on the potential benefits and risks associated with digitalization. The article summarizes the main data on the impact of the Internet, in particular social networks, on life satisfaction indicators and symptoms of depression in adolescents. The results of empirical studies conducted in different countries are ambiguous and do not allow to speak about universal effects that apply to all children and adolescents. We assume that the lack of unambiguous conclusions about the impact of digital technologies is due to the nonlinearity and differential effects. In particular, the power of influence depends on the individual characteristics, the intensity of the use of technology, socio-economic characteristics of the child's environment. This review shows the need for a differentiated approach to research the impact of digitalization on the well-being of children and to the practices of supporting the child in his development of the Internet.

Women have been systematically disadvantaged in the labour market. This could be explained by a complex association of factors, such as the lower speed of women’s professional growth within companies, their under-representation in management positions, and the unequal distribution of caregiving and housework between men and women. The rise of the gig economy—a market system that is based on hiring independent contractors and freelance workers as opposed to creating full-time contracts—has brought researchers and policymakers into a discussion on the effects of online platforms and flexible work arrangements on labour market gender parity. In this study, we examine the case of the largest online English-language school in Eastern Europe, Skyeng. Data on 6,461,404 lessons given by 13,571 teachers demonstrate that women had fewer working hours than men in most age categories, but especially for ages 30–35. The workload deficit for the women could be partly attributed to the fact that they worked less often than the men did in the evenings (7–10 p.m.). We conclude that, despite the flexible work arrangements the gig economy has offered, the women taught fewer classes than the men (i.e., having fewer paid working hours), which in turn led to a gender pay gap. The rapid growth of the gig economy makes it important to monitor gender-gap dynamics as well as discuss potential mechanisms eliminating gender inequality in the labour market.