We present a study on co-authorship network representation based on network embedding together with additional information on topic modeling of research papers and new edge embedding operator. We use the link prediction (LP) model for constructing a recommender system for searching collaborators with similar research interests. Extracting topics for each paper, we construct keywords co-occurrence network and use its embedding for further generalizing author attributes. Standard graph feature engineering and network embedding methods were combined for constructing co-author recommender system formulated as LP problem and prediction of future graph structure. We evaluate our survey on the dataset containing temporal information on National Research University Higher School of Economics over 25 years of research articles indexed in Russian Science Citation Index and Scopus. Our model of network representation shows better performance for stated binary classification tasks on several co-authorship networks.
Theories and concepts developed and empirically tested in the context of North American and Western European countries do not always easily transfer to another political landscape. The concept of “policy advisory system” is not an exception. On the one hand, policy processes and policy styles are not unique for each country; therefore, some generalizations can be made. On the other hand, studding particularities of policy process in a specific country can enrich theories, developed for general cases. Applying existing theories to a new context also goes a long way in verification and potential falsification – the fundamental requirement for a scientific process. This article aims to contribute to the debate on the topic of policy advisory system by comparing the development of three policies in Russia, each involving policy advisors to some extent. Based on this analysis, lessons are drawn regarding the conditions under which policy advisors can impact policy changes in an environment, alternative to “western.”
This chapter analyses the nature of protests in Iceland, the United Kingdom and the United States in America from 2008 to 2016. We focus on the nature of these protests, forms of collective actions, main drivers of the protests and the resulting political changes. It allows us to determine that protests played the role of the challengers of the status quo — protested against the current political state in their countries and tried to develop alternatives by revoking practices of direct democ- racy, creating public spaces for discussions and promote their ideas among the broad public.
This book examines the waves of protest that broke out in the 2010s as the collective actions of self-organized publics. Drawing on theories of publics/counter-publics and developing an analytical framework that allows the comparison of different country cases, this volume explores the transformation from spontaneous demonstrations, driven by civic outrage against injustice to more institutionalized forms of protest. Presenting comparative research and case studies on e.g. the Portuguese Generation in Trouble, the Arab Spring in Northern Africa, or Occupy Wall Street in the USA, the authors explore how protest publics emerge and evolve in very different ways – from creating many small citizen groups focused on particular projects to more articulated political agendas for both state and society. These protest publics have provoked and legitimized concrete socio-political changes, altering the balance of power in specific political spaces, and in some cases generating profound moments of instability that can lead both to revolutions and to peaceful transformations of political institutions.
The authors argue that this recent wave of protests is driven by a new type of social actor: self-organized publics. In some cases these protest publics can lead to democratic reform and redistributive policies, while in others they can produce destabilization, ethnic and nationalist populism, and authoritarianism. This book will help readers to better understand how seemingly spontaneous public events and protests evolve into meaningful, well-structured collective action and come to shape political processes in diverse regions of the globe.
In this paper we show that for a given co-authorship network we could construct a recommender system for searching collaborators with similar research interests defined via keywords and topic modelling. We suggest new link embedding method and evaluate our model on National Research University Higher School of Economics (NRU HSE) co-authorship network.
Co-authorship networks contain invisible patterns of collaboration among researchers. The process of writing joint paper can depend of different factors, such as friendship, common interests, and policy of university. We show that, having a temporal co-authorship network, it is possible to predict future publications. We solve the problem of recommending collaborators from the point of link prediction using graph embedding, obtained from co-authorship network. We run experiments on data from HSE publications graph and compare it with relevant models.
One of the major problem of recommendation services is commercial astroturfing. This work is devoted to constructing a model capable of detecting astroturfing based on network analysis. The main idea of the model is projecting a multipartite network to a unipartite and detecting communities in it representing actors with falsified opinions.
We consider the problem of depth reconstruction from downsampled sparse depth values. We compare our approach with semi-dense depth map interpolation and direct RGB-to-Depth reconstruction solutions on several datasets, including Matterport 3D dataset containing RGB and depth images of 90 building-scale scenes. We demonstrate that the proposed model can produce approximate depth map for over two hundreds images per second.
Definitions: State is a type of polity that is characterized by two main dimensions: “statehood” and “stateness.” Statehood is the recognition of the state by other states as independent nation, equal to others to participate on international arena; receiving and having the “statehood” for country mean that it is a part of the “concert of nations,” such as the member of the United Nations organization. Stateness is a state capacity to sustain its territory, nation, and citizens’ welfare; it is not enough being recognized by other states as such, but also important to support this status in time
In this paper, we study style transfer applications for the photo-realistic image processing tasks. First, we present the results on image quality improvement based with photo style transfer. Second, we describe the problems of learning style transfer under geometrical constraints for processing portrait images and multi-style transfer. Finally, we give a short glimpse on application of image-to-image translation methods for updating realistic graphics for video games.
Online social networks play major role in the spread of information on a very large scale. One of the major problems is to predict information propagation using social network interactions. The main purpose of this paper is to construct heuristic model of weighted graph based on empirical data that can outperform the existing models. We suggest a new approach of constructing the model of information based on matching specific weights to a given network.