Экономические журналы России, их характеристики и сетевой анализ
Methods of network analysis are used in this paper for mapping the local academic community of St. Petersburg sociologists. The survey data on relations between individual scholars serve as a guide in reconstruction of the communitys network history as well as a system of independent variables in accounting for differences between its various natural zones. In this manner, the paper explores the points of convergence between Chicago school social ecology and modern social network analysis.
This volume contains proceedings of the fourth conference on Analysis of Images, Social Networks and Texts (AIST’2015)1 . The first three conferences in 2012–2014 attracted a significant number of students, researchers, academics and engineers working on interdisciplinary data analysis of images, texts, and social networks. The broad scope of AIST makes it an event where researchers from different domains, such as image and text processing, exploiting various data analysis techniques, can meet and exchange ideas. We strongly believe that this may lead to crossfertilisation of ideas between researchers relying on modern data analysis machinery. Therefore, AIST brings together all kinds of applications of data mining and machine learning techniques. The conference allows specialists from different fields to meet each other, present their work, and discuss both theoretical and practical aspects of their data analysis problems. Another important aim of the conference is to stimulate scientists and people from the industry to benefit from the knowledge exchange and identify possible grounds for fruitful collaboration. The conference was held during April 9–11, 2015. Following an already established tradition, the conference was organised in Yekaterinburg, a cross-roads between European and Asian parts of Russia, the capital of Urals region.The key topics of AIST are analysis of images and videos; natural language processing and computational linguistics; social network analysis; pattern recognition, machine learning and data mining; recommender systems and collaborative technologies; semantic web, ontologies and their applications. The Program Committee and the reviewers of the conference included wellknown experts in data mining and machine learning, natural language processing, image processing, social network analysis, and related areas from leading institutions of 22 countries including Australia, Bangladesh, Belgium, Brazil, Cyprus, Egypt, Finland, France, Germany, Greece, India, Ireland, Italy, Luxembourg, Poland, Qatar, Russia, Spain, The Netherlands, UK, USA and Ukraine.
The article introduces a historical-sociological research project reconstructing intellectual and institutional transformations of post-soviet social sciences in the last 25 years. The projects ambition was to achieve this aim via applying classical community study research strategy and various methods derived from social science history to the case of St. Petersburg sociologists. We identified 622 individuals as St. Petersburg sociologists and traced records of their institutional trajectories, appearance in print, citing behaviour, social networks, political attitudes, sources of income, professional authorities, and attention spaces through 25 years.
The monograph is based on a thesis aimed at systematizing of theoretical ideas and practical developments of the network approach in sociology and determining its place and role in the structure of sociological knowledge. The paper analyzes the theoretical and methodological foundations of the three directions of the network approach in sociology - Social Networks Analysis (SNA), Relational Sociology and the Actor-Network Theory (ANT). The results of the research can be useful for a wide range of researchers and academic workers, as well as students of the social sciences departments, and can be used in courses on the history of sociology, modern sociological theory, methodology of sociological research, and in the implementation of empirical research.