The continuously growing number of people participating in Internet-based, online, political activism suggests that the latter has the potential to replace offline forms of unconventional political participation in the future. If that is the case, it is essential to understand the nature and objectives of such type of participation. This article addresses the question of distinctive preconditions of online activism. As a result of the mixed-effect logistic regression analysis of the European Social Survey data, it was found that online activism contrasts with other unconventional types of political participation in respect to the effect of social trust. It is suggested that the key differences between the preconditions of online and offline forms of participation may speak in favour of several phenomena. First of all, it is proposed that social networking services (SNSs) managed to create an illusion of directness of political participation. Secondly, new groups of people with the lower risk preferences may be recruited into online political action. Lastly, groups that do not believe in the effectiveness of political participation or that have other motives, such as a search for attention, may be more likely to participate online. The results call for further research on how SNSs reshape how people understand political engagement and how they want to be involved.

Despite the fact that preconditions of political participation were thoroughly examined before, there is still not enough understanding of which factors directly affect political participation and which factors correlate with participation due to common background variables. This article scrutinises the causal relations between the variables associated with participation in online activism and introduces a three-step approach in learning a reliable structure of the participation preconditions’ network to predict political participation. Using Bayesian network analysis and structural equation modeling to stabilise the structure of the causal relations, the analysis showed that only age, political interest, internal political efficacy and no other factors, highlighted by the previous political participation research, have direct effects on participation in online activism. Moreover, the direct effect of political interest is mediated by the indirect effects of internal political efficacy and age via political interest. After fitting the parameters of the Bayesian network dependent on the received structure, it became evident that given prior knowledge of the explanatory factors that proved to be most important in terms of direct effects, the predictive performance of the model increases significantly. Despite this fact, there is still uncertainty when it comes to predicting online participation. This result suggests that there remains a lot to be done in participation research when it comes to identifying and distinguishing factors that stimulate new types of political activities.

This paper presents a study on the dynamics of sentiment polarisation in the active online discussion communities formed around a controversial topic—immigration. Using a collection of tweets in the Swedish language from 2012 to 2019, we track the development of the communities and their sentiment polarisation trajectories over time and in the context of an exogenous shock represented by the European refugee crisis in 2015. To achieve the goal of the study, we apply methods of network and sentiment analysis to map users’ interactions in the network communities and quantify users’ sentiment polarities. The results of the analysis give little evidence for users’ polarisation in the network and its communities, as well as suggest that the crisis had a limited effect on the polarisation dynamics on this social media platform. Yet, we notice a shift towards more negative tonality of users’ sentiments after the crisis and discuss possible explanations for the above-mentioned observations.

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