В поисках утраченных профилей: достоверность данных ВКонтакте и их значение для исследований образования
Research on social network sites (SNS) is mainly focused on Facebook, the most popular SNS in the world. The Russian analogue of Facebook is the social network VK with more than 100 million active users. The potential of this site as a data source is now acknowledged in educational research but little is known about the reliability of data obtained from this social network and its sampling bias. Our article investigates the reliability of the VK data on secondary school students from a Russian school (766 students) and bachelor students from selective Russian university (15 757 students). We describe the procedure of matching VK profiles to the students. A direct comparison permitted us to identify profiles of around 18% students. A special technique developed by us increased this number up to 88% for school students and 93% for university students. We compare age, gender and GPA of identified students and students who were not on the VK. We compared the structure of social relationships, retrieved from the VK data, to the expected structure of students’ social ties. We found that the structure of ‘virtual’ social relationships reproduces both the socio-demographic division of students into classes according to their age and spatial division into different school buildings or university campuses. To our knowledge, it is the first study of this kind and scale on VK data. It makes a contribution to the understanding of reliability of the data from this SNS and its potential in educational research.
The existing findings on the relationship between optimism and academic performance are rather contradictory. Two studies were undertaken to investigate thе relationship between attributional style, well-being, and academic performance. A new Russian-language measure of attributional style for positive and negative events (Gordeeva, Osin, Shevyakhova, 2009) with stability, globality, and controllability subscales was used. In the first study, optimistic attributional style for good events was associated with higher academic achievement in high school students (N=225) and mediated the effect of academic performance on self-esteem. In the second study, pessimistic attributional style for negative events predicted success in passing three difficult written entrance examinations in university entrants (N=108), and optimistic attributional style for good events predicted success with success expectations as a mediator. The results indicate that attributional styles for positive and negative events are not uniform in their relationship to performance in different academic settings and to well-being variables.
This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
This article is an expanded version of the report submitted by the author on V scientific and practical conference dedicated to the memory of the first Dean of the Faculty of Sociology HSE Alexander O. Kryshtanovskiy "Sociological research methods in modern practice". The article is based on a study of the quantative data obtained in the course of one of the stages of the study "New social movements of youth" by Center of Youth Studies HSE - SaintPetersburg. At this stage, youth community mapping was conducted and analysis of the data using SNA tools was organised. The issue of this work is related to the specific application of network theory and network analysis methods in the process of discovering relations between various informal organisations on the example of youth communities.
The CCIS series is devoted to the publication of proceedings of computer science conferences. Its aim is to efficiently disseminate original research results in informatics in printed and electronic form. While the focus is on publication of peer-reviewed full papers presenting mature work, inclusion of reviewed short papers reporting on work in progress is welcome, too. Besides globally relevant meetings with internationally representative program committees guaranteeing a strict peer-reviewing and paper selection process, conferences run by societies or of high regional or national relevance are also considered for publication.
Institutions affect investment decisions, including investments in human capital. Hence institutions are relevant for the allocation of talent. Good market-supporting institutions attract talent to productive value-creating activities, whereas poor ones raise the appeal of rent-seeking. We propose a theoretical model that predicts that more talented individuals are particularly sensitive in their career choices to the quality of institutions, and test these predictions on a sample of around 95 countries of the world. We find a strong positive association between the quality of institutions and graduation of college and university students in science, and an even stronger negative correlation with graduation in law. Our findings are robust to various specifications of empirical models, including smaller samples of former colonies and transition countries. The quality of human capital makes the distinction between educational choices under strong and weak institutions particularly sharp. We show that the allocation of talent is an important link between institutions and growth.