Collapse of an Online Social Network: The Blame on Social Capital
Julia Koltai | Hungarian Academy of Sciences, Centre for Social Sciences | Hungary
The rise and popularity of online social networks is a recent phenomenon. In this study, we analyze the reasons and mechanisms behind the collapse of an online social network (OSN), iWiW. Significant cascading mechanisms have been identified in the pattern of abandoning the site at its peak of popularity and after. It is of key importance to study who were the key actors that started these cascades and abandoned the site early compared to others in their network. We contrasted explanations based on preserving accumulated social capital vs. building new social capital with motives influenced by innovativeness. On the one hand, those who are well embedded in their existing network have more to lose. On the other hand, people might want to escape from redundancy and indebtedness indicated by a high local clustering coefficient. We find with heterogeneous choice models that lower degree and a high local clustering are associated with early abandonment. The significant effects of age and innovativeness that depend on the life stage of the OSN indicate that mechanisms related to social capital are not the only reasons for the collapse.
keywords: social capital, online social networks
Mechanisms of social capital formation within non-commercial local exchange and trade system (LETS)
Beata Łopaciuk-Gonczaryk | University of Warsaw, Faculty of Economic Sciences | Poland
The paper will examine socio-economic mechanisms operating in a Polish, non-commercial local exchange and trade system (LETS), based on community currency, and its impact on social capital formation. LETS allows, through the use of an internet platform, to extend the traditional neighbourly help to a wider group of people, and also contributes to the creation of social ties, especially if transactions include direct interpersonal interactions and are accompanied by additional events strengthening the existence of the community. Performance of peer-to-peer transaction platforms is conditioned both by technical solutions, as well as norms and preferences of their users. To some extent, those norms and preferences may be influenced and developed by social interactions connected with conducting transactions within LETS. The main focus of the study is to determine how interpersonal interactions connected with transactions within the LETS under study may influence social norms and collaboration attitudes.
Data have been obtained from the web-based platform, supporting the transactions and enabling to give recommendations. Additional information has been acquired from in-depth interviews. Data on transactions, in context of the LETS analysed, can be treated as evidences of interpersonal interactions, as most of them involve face-to-face contact and have a social component. Some users are given recommendations, which are almost in all cases enthusiastically positive (only one recommendation is negative) and look like credentials that somebody fits well into the system. Therefore they may be treated as information that the recommended user follows the system norms and suits its internal culture. Comparing the network of transactions with the data on recommendations may provide information on norms’ diffusion.
The study faces the challenge of distinguishing between influence and selection, as system users may not only influence each other while interacting but also they may be attracted into the system in the first place because of their specific views and attitudes. In order to try to solve this puzzle, evolution of the network is going to be observed, as the data cover the period from September 2012 to December 2016. During the whole period, there were in total 919 active users, 6599 transactions completed and only 446 (positive) recommendations given. There are no incentives to give recommendations, other than sense of gratitude, and as a result the number of recommendations is very small in comparison to the number of transactions. Therefore a fact of receiving recommendations by an actor in a given period is treated as a proxy attribute indicating following system norms and showing highly collaborative attitudes. This attribute’s change from period to period is supposed to be influenced by interactions with well-behaving, experienced system users in a role of providers of goods or services. Stochastic actor-based model for co-evolution of social network and individual behaviour is utilized to verify the hypothesis stated. The approach taken involves controlling the effects of endogenous network formation (reciprocity and network closure), possible selection effect (system users with good reputation will probably have high popularity as providers) and other attributes (like the fact of being a recommendation giver).
Smoking motivations differences according to peer groups’ gender composition. A social network study of 12 000 European adolescents.
Adeline Grard | UCL Université catholique de Louvain | Belgium
Background: In the last decades, gender differences in smoking prevalence have reduced, and in some European countries, girls smoking rates now exceed boys’ ones. Most regular smokers initiate smoking during adolescence, when they are particularly susceptible to peer influence. Yet, if peer effect explains the way smoking spread in a peer group, it does not explain why it may affect differently boys and girls. Recent studies have underlined the important role of peer group gender composition in adolescent smoking. For instance, adolescents with other-sex friends are more likely to smoke than those with same-sex friends. One possible explanation is that same-gender peer groups entail specific norms and values regarding tobacco. Yet, to establish a common norm regarding tobacco, peer groups have to share similar beliefs or motivations to smoke. To test this hypothesis, it is important to analyze how motivations are shared by adolescents connected to each other in a network and to consider their gender as a characteristic of clusters.
Methods: In 2016, 12 000 students of 14-16 years participated to a social network survey in 60 different schools, located in 7 different European cities. Adolescents had to nominate up to 5 best friends in their school directory. We also collected data on smoking status, smoking motivations, and sociodemographics. We classified smoking motivations in four categories, depending on their position on two axes: negative versus positive motivations; and individual versus social motivations. We then organized adolescents’ clusters into three groups: only-girls triads; only-boys triads and mixed gender triads.
Hypothesis: we hypothesize that (1) motivations for (not) smoking differ across genders, and that (2) smoking motivations are shared differently according to triads’ gender composition.
Results: Results indicate that social (positive and negative) motivations are more common among girls, while positive individual motivations were more reported by boys. On the clusters level, analysis reveal differences in the type of motivations shared, and in the motivations scores, according to the gender composition of the cluster. This underlines that smoking norms are different, but also that they are more embedded, depending on the gender composition of the peer group.
Conclusions: Smoking prevention programs could be more efficient if they would adapt to gender differences in smoking motivations and use peer group prevention techniques.