An analysis of students’ response to changes in financial situation during the pandemic by digital traces in the VKontakte social network

Author(s):  
Е.В. РОМАНОВА ◽  
Т.Ю. КАЛАВРИЙ

В статье представлены результаты исследования круга проблем и вопросов финансового положения студентов в период пандемии по цифровым следам в социальных сети ВКонтакте студенческой аудитории. Для анализа были использованы тексты постов в сообществах студентов и комментарии к ним за период второго учебного года в условиях пандемии. Для оценки контента обсуждаемых тем и вопросов в сообществах использованы результаты НИР Консорциума исследователей больших данных «Образование в условиях коронавируса: большие данные как инструмент измерения реакции общества» за февраль – июнь 2020 г. Подготовка данных для анализа включала выгрузку данных из социальных сетей, отбор релевантных сообщений, выявление категорий и тематических сюжетов, определение тональности сообщений. По предварительно выгруженным с использованием специализированного программного обеспечения (Polyanalyst, библиотек машинного обучения) сообщениям сообществ вузов региона была проведена разметка всех сообщений по релевантности изучаемой темы, что позволило в дальнейшем систематизировать сообщения по тематике и тональности. Контент анализируемых релевантных сообщений позволили выделить четыре основные тематические категории такие, как стипендия и материальная помощь, стоимость образовательных и дополнительных услуг, возможность получения дополнительных доходов, разное. В группе сообщений по вопросам стипендии и материальной помощи были выделены тематические сюжеты о размере и сроках выплаты стипендии и материальной помощи и о процедуре начисления стипендии. В группе сообщений по вопросам стоимость основных и дополнительных услуг были выделены тематические сюжеты о цене-качестве образовательных услуг, возврата стоимости за обучение в условиях дистанционного формата работы, а также ценообразование образовательных услуг. В группе сообщений по возможности получения дополнительных доходов студенты рассуждали преимущественно о размере стипендии в сопоставлении со сложившимися ценами на товары и услуги и о необходимости поиска дополнительных источниках доходов. В группе разное были рассмотрены низкочастотные сообщения по различным тематическим сюжетам. Тональность сообщений, в которых студенты высказывали свое мнение и оценку, преимущественно нейтральная, но негативная тональность доминировала на начало каждого учебного семестра. Полученные результаты исследования на основе выборки данных социальной сети ВКонтакте за анализируемый период могут послужить обоснованием для дальнейшего исследования сообщений в социальных сетях с целью выявления и анализа обратной связи студентов о качестве, эффективности и развитии дистанционного образования в стране, а также мониторинга появления/развития/отмирания проблем и вопросов в сфере финансового состояния студентов. The article presents the results of a survey on the range of problems and questions of students regarding financial situation based on digital traces in the VKontakte social network. The analysis was based on posts in student communities and comments to them during the second academic year during the pandemic. To assess changes in the content of the discussed topics and issues in the communities, the results of research work of the Consortium of Big Data Researchers “Education in the context of coronavirus: big data as a tool for measuring the reaction of society” for February – June 2020 were used. Preparing data for analysis included downloading data from social networks, selecting relevant messages, identifying categories and thematic plots, and determining the sentiment of messages. According to the messages from the communities of the universities in the region, previously unloaded using specialized software (Polyanalyst, machine learning libraries), all messages were marked up according to the relevance of the topic being studied, which made it possible to further systematize messages by topic and tone. The content of the analyzed relevant messages allowed us to single out four main thematic categories such as scholarships and material assistance, the cost of educational and additional services, the possibility of obtaining additional income, and miscellaneous. In the group of presentations on the issues of scholarships and material assistance, thematic stories were highlighted on the amount and timing of payment of the scholarship and material assistance and on the procedure for awarding the scholarship. In the group of messages on the cost of basic and additional services, there were highlighted thematic stories about the price-quality of educational services, the return of the cost of training in a distance format of work, as well as the pricing of educational services. In the group of messages about the possibility of obtaining additional income, students talked mainly about the amount of the scholarship in comparison with the prevailing prices for goods and services and the need to search for additional sources of income. In the Miscellaneous group, low-frequency messages were considered on various thematic topics. The tone of the messages in which the students expressed their opinion and assessment was predominantly neutral, but the negative tone dominated at the beginning of each academic semester. The results of the study based on a sample of data from the VKontakte social network for the analyzed period can serve as a rationale for further research of messages on social networks in order to identify and analyze student feedback on the quality, efficiency and development of distance education in the country, as well as monitor the emergence / development / withering away problems and questions in the field of the financial condition of students.

Author(s):  
A S Mukhin ◽  
I A Rytsarev ◽  
R A Paringer ◽  
A V Kupriyanov ◽  
D V Kirsh

The article is devoted to the definition of such groups in social networks. The object of the study was selected data social network Vk. Text data was collected, processed and analyzed. To solve the problem of obtaining the necessary information, research was conducted in the field of optimization of data collection of the social network Vk. A software tool that provides the collection and subsequent processing of the necessary data from the specified resources has been developed. The existing algorithms of text analysis, mainly of large volume, were investigated and applied.


Author(s):  
Sovan Samanta ◽  
Madhumangal Pal

Social network is a topic of current research. Relations are broken and new relations are increased. This chapter will discuss the scope or predictions of new links in social networks. Here different approaches for link predictions are described. Among them friend recommendation model is latest. There are some other methods like common neighborhood method which is also analyzed here. The comparison among them to predict links in social networks is described. The significance of this research work is to find strong dense networks in future.


Author(s):  
Mark Alan Underwood

Intranets are almost as old as the concept of a web site. More than twenty-five years ago the text Business Data Communications closed with a discussion of intranets (Stallings, 1990). Underlying technology improvements in intranets have been incremental; intranets were never seen as killer developments. Yet the popularity of Online Social Networks (OSNs) has led to increased interest in the part OSNs play – or could play – in using intranets to foster knowledge management. This chapter reviews research into how social graphs for an enterprise, team or other collaboration group interacts with the ways intranets have been used to display, collect, curate and disseminate information over the knowledge life cycle. Future roles that OSN-aware intranets could play in emerging technologies, such as process mining, elicitation methods, domain-specific intelligent agents, big data, and just-in-time learning are examined.


Author(s):  
Ryan Bigge

The media coverage and resultant discourse surrounding social networking sites such as Facebook, MySpace and Friendster contain narratives of inevitability and technological determinism that require careful explication. Borrowing a tactic from the Russian Futurists, this paper attempts to make strange (that is, to defamiliarize) social network sites and their associated discourses by drawing upon an eclectic but interrelated set of metaphors and theoretical approaches, including: the digital enclosure, network sociality, socio-technical capital and Steven Jones’s recent examination of neo-Luddites. Whenever appropriate, this paper will integrate relevant magazine and newspaper journalism about social networking sites.


Author(s):  
Mahyuddin K. M. Nasution Et.al

In the era of information technology, the two developing sides are data science and artificial intelligence. In terms of scientific data, one of the tasks is the extraction of social networks from information sources that have the nature of big data. Meanwhile, in terms of artificial intelligence, the presence of contradictory methods has an impact on knowledge. This article describes an unsupervised as a stream of methods for extracting social networks from information sources. There are a variety of possible approaches and strategies to superficial methods as a starting concept. Each method has its advantages, but in general, it contributes to the integration of each other, namely simplifying, enriching, and emphasizing the results.


Author(s):  
Yuriy V. Kostyuchenko ◽  
Victor Pushkar ◽  
Olga Malysheva ◽  
Maxim Yuschenko

This chapter aimed to consider of approaches to big data (social network content) utilization for understanding social behavior in the conflict zones, and analysis of dynamics of illegal armed groups. The analysis directed to identify of structure of illegal armed groups, and detection of underage militants. The probabilistic and stochastic methods of analysis and classification of number, composition, and dynamics of illegal armed groups in active conflict areas are proposed. Data of armed conflict in Donbas (Eastern Ukraine) in the period 2014-2015 is used for analysis. The numerical distribution of age, gender composition, origin, social status, and nationality of militants among illegal armed groups has been calculated. Conclusions on the applicability of described method in criminological practice, as well as about the possibilities of interpretation of obtaining results in the context of study of terrorism are proposed.


Author(s):  
Tomás Ruiz Sánchez ◽  
María del Lidón Mars Aicart ◽  
María Rosa Arroyo López ◽  
Ainhoa Serna Nocedal

The characteristics of people who are related or tied to each individual affects her activitytravel behavior. That influence is especially associated to social and recreational activities, which are increasingly important. Collecting high quality data from those social networks is very difficult, because respondents are asked about their general social life, which is most demanding to remember that specific facts. On the other hand, currently there are different potential sources of transport data, which is characterized by the huge amount of information available, the velocity with it is obtained and the variety of format in which is presented. This sort of information is commonly known as Big Data. In this paper we identify potential sources of social network related big data that can be used in Transport Planning. Then, a review of current applications in Transport Planning is presented. Finally, some future prospects of using social network related big data are highlighted.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4251


Author(s):  
Mantian (Mandy) Hu

In the age of Big Data, the social network data collected by telecom operators are growing exponentially. How to exploit these data and mine value from them is an important issue. In this article, an accurate marketing strategy based on social network is proposed. The strategy intends to help telecom operators to improve their marketing efficiency. This method is based on mutual peers' influence in social network, by identifying the influential users (leaders). These users can promote the information diffusion prominently. A precise marketing is realized by taking advantage of the user's influence. Data were collected from China Mobile and analyzed. For the massive datasets, the Apache Spark was chosen for its good scalability, effectiveness and efficiency. The result shows a great increase of the telecom traffic, compared with the result without leader identification.


2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Mohammed Anouar Naoui ◽  
Brahim Lejdel ◽  
Mouloud Ayad ◽  
Riad Belkeiri ◽  
Abd Sattar Khaouazm

AbstractThis paper aims to propose a deep learning model based on big data for the healthcare system to predict social network data. Social network users post large amounts of healthcare information on a daily basis and at the same time hospitals and medical laboratories store very large amounts of healthcare data, such as X-rays. The authors provide an architecture that can integrate deep learning, social networks, and big data. Deep learning is one of the most challenging areas of research and is becoming increasingly popular in the health sector. It uses deep analysis to extract knowledge with optimum precision. The proposed architecture consists of three layers: the deep learning layer, the big data layer, and the social networks layer. The big data layer includes data for health care, such as X-ray images. For the deep learning layer, three Convolution Neuronal Network models are proposed for X-ray image classification. As a result, social network layer users can access the proposed system to predict their X-ray image posts.


Author(s):  
Mohcine Kodad

This paper presents a study that contributes to the existing work on the social diffusion and interaction strategy in social media. The aim is to know the most shared post by some electronic media in the world from end to end social network, and also to know post nature of the most successful one, and the link between different kind of interaction these are main objectives of this study. Our work is also considered as a ground and a base for social network analysis researchers in all social networks in order to allow them to benefit and help in their future research work from all information collected and results found via this study. An empirical analysis using multiple methods is conducted based on 275 Facebook publications gathered from the Facebook pages of 5 electronics journals the best one in its original country represented 5 countries in the world. This contribution discovered a set of important information and it is also projected to confirm hypothesis addressed in pre-existing studies


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