This book explores the reasons behind the unexpected rise to power of Ukraine’s President Volodymyr Zelensky, a former comedian with no political background, and offers an in-depth analysis of the populist messages he delivered to the Ukrainian people via his TV show.
Taking a discourse analysis approach, the author draws on two main arguments of critical scholarship: the “populist explosion” of the recent decade came as a reaction to the inequalities and injustices of the global neoliberal order, and the success of neoliberalism can be explained by its ability to mask itself under attractive progressive covers. Developing these lines of argument, the book demonstrates not only how the “populist explosion” can lead to further neoliberalization, but also that the euphemizing effect can be achieved by mixing the virtual and the real, as in the case of Zelensky.
Departmental academic support plays an important role in a doctoral journey. However, different types of support may be related to different outcomes. This paper aims to provide a categorisation of types of departmental academic support and analyse the relationship between these different categories of support and doctoral students' confidence that they will complete their dissertations. The empirical base for the research is data from a cross-institutional survey of doctoral students at six Russian universities. Based on the results of latent class analysis (LCA), we distinguished six types of departmental academic support depending on the functions performed by supervisors, other faculty members and department heads. Consistent with previous research, we found that departmental academic support plays a crucial role in doctoral students' experiences and outcomes, while lack of support is related to a lower level of confidence about completing a dissertation. At the same time, our results provide evidence that excessive collective engagement in doctoral students' work from departmental staff may be less effective than the strong engagement of a supervisor, assisted by informational support from other staff members.
This volume constitutes refereed proceedings of the 6th International Conference on Digital Transformation and Global Society, DTGS 2021, held as a virtual event in June 2021. Due to the COVID-19 pandemic the conference was held online.
The 34 revised full papers and 4 short papers presented in the volume were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on eSociety: social informatics and digital inclusion issues; ePolity: e-governance and regulation; eCity: smart cities and urban planning; eHumanities: digital education and research methods; eCommunication: online discources and attitudes; eEconomy: challenges of the COVID-19 pandemic; eEconomy: e-commerce research.
This chapter examines the nature of governmental support of civil society in a non-democratic context, taking the example of Russia. Russian civil society organizations exist in dual realities when the state sets up a structure of supporting measures but at the same time limits the scope of their activity. While limiting measures and their effects on Russian civil society have been well analyzed, this chapter considers the issue of how state support for civil society actors actually shapes the sector and contributes to regime legitimacy. We argue that governmental support for civil society organizations in non-democratic regimes not only bolsters the state’s welfare function but also attempts to intertwine non-governmental welfare provision with elements of a state-led legitimation discourse.
This paper studies the willingness among Russia’s population to try out three new transport technologies: electric cars, car-sharing, and autonomous driving. The assumption is that these three offerings will in the near future appear as autonomously driving vehicles booked on a subscription basis. Next to socio-economic parameters such as age, gender, place of living or holding a driver’s licence, we introduce three measures: values of self-expression, attitudes towards science and technology and attitudes towards novelties in general to explain the likelihood to try out these transport innovations. Thereby, this paper increases the understanding of the preconditions that lead to widespread acceptance of transport innovations. An analysis of the psychological set-up of the respondents allowed for the identification of a group of enthusiasts that are excited to try out these new transportation offerings. We argue that application of such an approach deepens the understanding of social mechanisms behind technology adoption and can be useful for the identification of social groups that support related processes.
The current issue focuses on the specifics traits of animated images in GIF format, which allow spectator to get a unique user experience of interacting with moving pictures.
In some cases "animation" does not produce a significant aesthetic effect and is mainly used to attract viewer’s attention to some information, for example, to news or an advertised product (the strategy of "attention-grabbing"); in other cases by means of animation the illustrator fully conveys a specific message, “expands” the image to add meaning.
In this article we analyze the concept of GIF-illustrations, its history, its features in comparison with other technologies for video and animation transmission, for example: Macromedia Shockwave, Macromedia Flash, Microsoft Silverlight, Java etc., and the trajectory of its further development. Since the 2010, with increasing popularity of “GIFs”, a big number of GIF artists has appeared. Both artists and illustrators who turn to GIF in order to create an art project or a commercial project, to make a statement. Therefore, today an illustrator faces a “double” task: to create an image that will “work” both in a digital environment and as a “static” (for example, on paper).
Attempting to classify various scenarios of artist’s work with an animated image we argue that such images could be divided into three categories: 1) “technical” (it has an applied function, existing as an animated version of a technical illustration and making it easier for the user to understand the operation of a particular mechanism or some mechanics); 2) GIFs, which actualize the rhythm category (the effect of their “impact” on the viewer is built up by rhythmic repetition of individual elements in the frame or the whole frame); 3) “narrative” GIFs telling a certain story (the user must complete a significant part of this story on his own). These three scenarios can complement each other and have certain extensions.
Special attention deserve the GIFs that require “slow reading” to create an unusual communication situation, and to prompt the viewer to engage in processing of a visual narrative. Here one can observe an liaison to videoart, as well as compare GIF with other contemporary “shorts”, simple, easy-to-read visual formats, for example, looped Coub microfilms.
Political Internet memes are an underresearched phenomenon situated at the intersection of digital and political communication. Regarded as a unit of cultural information transmitted online, such a meme can be considered as both a manifestation of anonymous networked creativity and a mechanism of political participation. The article presents the results of an investigation into Internet memes generated by protest discourses on Runet (Russian Internet). The examination of Internet content allows us to draw conclusions as to the thematic emphases of protest actions represented in Runet’s memosphere and the specifics of the image of Russian protest as reflected in memes.
How do journalists make news in Russian newspapers and what journalistic roles emerge from news content? We conducted a study of the news content of two general interest newspapers: Rossiiskaia Gazeta (RG), official organ of the Russian government, and Moskovskii Komsomolets (MK), a private newspaper oriented to a mass readership. Despite their different orientations and ownership, both newspapers relied mostly on government/party sources and prioritized the voices of the authorities and of the journalist—typical characteristics of a Soviet newspaper.
How do nonprofit organizations (NPOs) engage in advocacy in closed political regimes? This article studies nonprofit advocacy in Russia by focusing on strategies and explanatory factors. We argue that Russian NPOs rely on collaborative rather than confrontational strategies. They use official channels, personal contact with state officials, strategies for resource exchange and evidence-based advocacy. Based on empirical research in eight regions, we show that nonprofit advocacy depends on both external (contextual) and internal (organizational) factors. NPOs have greater opportunity to engage in advocacy when the subnational institutional context and the policy field allow for their active participation in policy formation and implementation. Moreover, NPOs are more successful in their advocacy when they strategically use their capabilities (e.g., knowledge, expertise and skills) and emphasize mutual trust, loyalty and readiness to compromise. Our findings point to the relevance of collaborative forms of advocacy, particularly in constrained political environments such as Russia.
Despite recent achievements in predicting personality traits and some other human psychological features with digital traces, prediction of subjective well-being (SWB) appears to be a relatively new task with few solutions. COVID-19 pandemic has added both a stronger need for rapid SWB screening and new opportunities for it, with online mental health applications gaining popularity and accumulating large and diverse user data. Nevertheless, the few existing works so far have aimed at predicting SWB, and have done so only in terms of Diener’s Satisfaction with Life Scale. None of them analyzes the scale developed by the World Health Organization, known as WHO-5 – a widely accepted tool for screening mental well-being and, specifically, for depression risk detection. Moreover, existing research is limited to English-speaking populations, and tend to use text, network and app usage types of data separately. In the current work, we cover these gaps by predicting both mentioned SWB scales on a sample of Russian mental health app users who represent a population with high risk of mental health problems. In doing so, we employ a unique combination of phone application usage data with private messaging and networking digital traces from VKontakte, the most popular social media platform in Russia. As a result, we predict Diener’s SWB scale with the state-of-the-art quality, introduce the first predictive models for WHO-5, with similar quality, and reach high accuracy in the prediction of clinically meaningful classes of the latter scale. Moreover, our feature analysis sheds light on the interrelated nature of the two studied scales: they are both characterized by negative sentiment expressed in text messages and by phone application usage in the morning hours, confirming some previous findings on subjective well-being manifestations. At the same time, SWB measured by Diener’s scale is reflected mostly in lexical features referring to social and affective interactions, while mental well-being is characterized by objective features that reflect physiological functioning, circadian rhythms and somatic conditions, thus saliently demonstrating the underlying theoretical differences between the two scales.
The present research studies the process of digital transformation in the heritage institutions. With the COVID-19 pandemic and constant development of modern digital technologies museums are forced to build their unique representation in the digital environment and keep the legacy and established functions simultaneously. At the same time, museums assume that this transformation will not only ruin the classical understanding of the museums but also make the institutions a form of mass-entertainment. The usage of both qualitative and quantitative methods aims to create a theoretical framework that will determine the possible tools and areas of the museums’ digitization. The evolution of cultural institutions can be seen as a primary indicator of global development.
How the COVID-19 pandemic affected the attitudes of Russians towards political institutions? The aggregate data of public opinion polls suggest that, according to various available indicators, the level of political support in Russia has slightly dropped, compared to the pre-pandemic period. Yet, this kind of data does not allow one to infer what aspects of the pandemic experience are the most important predictors of individual assessments of the government's performance. The article presents the results of the analysis of the data from the first two Russian waves of the international online panel survey ‘Values in Crisis’ (ViC). The first wave was carried out in Jun 2020; the second – in April-May 2021. The sample size was 1,527 and 1,199 respectively; 1,014 respondents participated in both waves. The main dependent variable is an integral index of political support that includes indicators of both diffuse and specific support. Regression modeling demonstrates that during the first wave of the pandemic in Russia (spring 2020) the direct experience of the disease and COVIDrelated anxiety were positively correlated with political support, while anxiety over economic losses showed negative correlation. A decrease in economic well-being had no effect on political support. Other significant predictors included right-wing political views and trust in traditional media (leading to an increase in support) and propensity to share COVID-skepticism (leading to a decrease in support). One year later, in the first half of 2021, the situation has somewhat changed: neither experiencing COVID, nor COVID-related anxiety were no longer associated with support, while the effect of economic factors became more prominent.