scholarly journals Learning in Online Communities: Behavioral Strategies of the Users of Educational Social Networks

2020 ◽  
Vol 10 ◽  
pp. 84-92
Author(s):  
Aleksei N. Sergeev ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Communities ◽  
Behavioral Strategies ◽  
Community Organizers ◽  
Information Consumers ◽  
Further Development ◽  
Inactive Users

The article deals with the results of a study on users’ behavioral strategies in educational social networks as Internet platforms for the communities of students and teachers who collaborate to solve educational problems. According to the analysis of the students and teachers’ activity on the educational social network of the Volgograd State Socio-Pedagogical University, the author has determined the groups of users with similar behavioral strategies, namely: community organizers, activists for communication and document exchange, educational assignment performers, information consumers, and inactive users. The author provides generalized portraits of each group, their numerical composition, as well as comparative characteristics in relation to other groups. The manuscript concludes that the presented groups reveal typical behavioral strategies of the users of educational social networks, which further development of educational platform tools, as well as pedagogical technologies based on their implementation should consider.

scholarly journals The Clubhouse Phenomenon: Do We Need Another Social Network?

2021 ◽  
Author(s):  
Wadim Strielkowski
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Real Time ◽  
Group Psychotherapy ◽  
Text Messages ◽  
Online Video ◽  
Conference Call ◽  
Start Up ◽  
Further Development

Being a combination of the conference call, talkback radio, audio podcast, and an online video chat, Clubhouse is a new social networking app that gained over 10 million users and over $100 in valuation in just 8 months. Unlike other social networks, it offers a real-time streaming audio chat that does not ask users to share any unnecessary information like exchanging text messages, conducting video calls, or sharing photos. Instead, Clubhouse users can listen to real-time conversations, contribute to these conversations and create their own conversations for the others to listen and to interact with. Often nicknamed a “Silicon Valley’s hottest start-up”, Clubhouse positions itself as an “exclusive” and “alternative” social network that attracts various celebrities and people who just want to talk to each other. Launched in March 2020, amidst the COVID-19 pandemic with its social distancing and lockdowns, Clubhouse offered its users a space for the digital group psychotherapy where people could solve their problems by talking them through with strangers. However, it is unclear what is going to happen to this new social network in the post-pandemic world after all of its hype eventually evaporates. This paper discusses the possible underlying motives for the Clubhouse creation and its real purposes. Moreover, it looks at the three possible scenarios of its further development.

A novel genetic algorithm-based improvement model for online communities and trust networks

2021 ◽  
Vol 40 (1) ◽  
pp. 1597-1608
Author(s):  
Ilker Bekmezci ◽  
Murat Ermis ◽  
Egemen Berki Cimen
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Online Communities ◽  
Real Life ◽  
Statistical Properties ◽  
Clustering Coefficient ◽  
Data Sets ◽  
Life Data ◽  
Real Life Data

Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k-nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks.

scholarly journals Network Analysis of Political Internet Communities: from Formalized to «Unobserved» Groups

2021 ◽  
pp. 160-182
Author(s):  
Olga Popova ◽  
Sergey Suslov
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Latent Dirichlet Allocation ◽  
The Political ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Political Communities

The article is dedicated to the development of the political communities in social networks analysis methods. Main stages of network approach in the political science is described in the research. Researchers review the most significant methods and techniques in the political online communities studies for the last decade. The article shows the contemporary Russian scientists contribution in the development of online communities learning techniques. Networks and social network analysis methods and techniques become universal scientific approaches for several scientific fields. Boundary-transcending trends were critical means of science integration. Researchers present the results of experiment in which evaluate the possibilities of study unobserved political groups using latent Dirichlet allocation (LDA) model. The brief LDA foundation history and possible modifications for social topic modeling based on social networks data are discribed in the review. Using sample from one feed aggregator telegram channel in period of 2020 autumn, the authors display the most valuable topics in the Russian segment of political communication. Also it provides communities ideological preferences. Modified qualitative sociological methods can be used in online political communities discursive features research without any specific computer science techniques. Since about 70% of the Internet data are generated in the social networks, velocity and volume data necessitate new data mining techniques, databases capacity and computation processes. In other words, it provides a big data approach in social network analysis.

scholarly journals Hrvatsko rječotvorje na društvenim mrežama

2021 ◽  
pp. 67-94
Author(s):  
Tatjana Pišković
Keyword(s):  
Social Networks ◽  
Social Network ◽  
New Media ◽  
Instant Messaging ◽  
Word Formation ◽  
Communication Style ◽  
Internet Users ◽  
Fixed Set ◽  
Loan Word ◽  
Information Consumers

Since the first decade of the 21st century, when social networks have become a part of everyday life, socially-oriented activities of Internet users have been on the continual rise. By creating a profile on social networks, Internet users cease to be passive Internet content and information consumers, but rather turn into creators, who shape a dynamic space of new media by virtue of their activities and personal contribution. One of the most significant areas in which social network users introduce numerous changes and innovative contents is most certainly communication and language practices. Each and every social network most often ground their recognizability on a fixed set of communication genres available to their members and in that way determine how the members are going to communicate with each other. This has made all the polyfunctional languages, Croatian among them, respond with a rather swift expansion of the existing vocabulary. In my paper, I will be presenting most productive word formation methods in which Croatian language makes up for social networks lexical gaps and shapes the communication style on social networks and instant messaging services. The first is a semantic loan from the English or neosemanticism word formation (e.g. profil, prijatelj, status, zid, dodati, blokirati, notifikacija); the second is a lexical loan word (e.g. lajkati, postati, šerati, atendati, hejtati, trolati, folover, selfi), and the third is creation of abbreviations (pozz, nezz, bmk, jbt, dns, fkt). Emergence of this new and abundant lexical layer in Croatian language requires from us to register a number of new entry units in general dictionaries of Croatian language.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

Social Networks and Business Performance of Igbo Migrant Traders in Ibadan, South-West Nigeria

2014 ◽  
Vol 12 (2) ◽  
Author(s):  
Deborah O. Obor ◽  
Emeka E. Okafor
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Social Exchange ◽  
Business Performance ◽  
Exploratory Research ◽  
Business Growth ◽  
South West ◽  
Key Informant ◽  
Depth Interviews

This study focused on social networks and business performance among Igbo businessmen in Ibadan, South-west Nigeria through the exploratory research design. Social exchange, social network and social capital theories were employed as theoretical framework. Twenty-six in-depth interviews, key informant interviews and case studies were conducted with purposively selected respondents in four business locations in Ibadan. The results showed that among the factors that facilitated migration of the Igbo to Ibadan were their interest to learn a trade, their inability to attain higher education, and having a relative in Ibadan. The types of social networks available showed that social network was not location bound, as all the respondents belonged to town progressive unions and mutual benefits/cooperative associations. Social networks played vital roles in business performance, including social support, access to loan, business growth and expansion. The main challenges to maintaining adequate social network in business were distrust, envy, unbridled competition, dishonesty and inability to keep terms of agreement. The study concludes that social networks have positively influenced the business performance of migrant Igbo in Ibadan. There is need for the Igbo to strengthen their social networks through honesty, forthrightness, and transparency in all their dealings.

Online Communities and Social Network Structure

2019 ◽  
Author(s):  
Yanhao Wei ◽  
Wensi Zhang ◽  
Sha Yang ◽  
Xi Chen
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Online Communities ◽  
Social Network Structure

Networks

2020 ◽  
pp. 534-562
Author(s):  
Matthew O. Jackson ◽  
Brian W. Rogers ◽  
Yves Zenou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Statistical Analysis ◽  
Labor Markets ◽  
Network Formation ◽  
Labor Market Outcomes ◽  
Negative Consequences ◽  
Social Scientists ◽  
Market Outcomes

What is the role of social networks in driving persistent differences between races and genders in education and labor market outcomes? What is the role of homophily in such differences? Why is such homophily seen even if it ends up with negative consequences in terms of labor markets? This chapter discusses social network analysis from the perspective of economics. The chapter is organized around the theme of externalities: the effects that one’s behavior has on others’ welfare. Externalities underlie the interdependencies that make networks interesting to social scientists. This chapter discusses network formation, as well as interactions between people’s behaviors within a given network, and the implications in a variety of settings. Finally, the chapter highlights some empirical challenges inherent in the statistical analysis of network-based data.

Introduction

2020 ◽  
pp. xxii-13
Author(s):  
Ryan Light ◽  
James Moody
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Bibliometric Analysis ◽  
Social Life ◽  
New Directions ◽  
Central Paradigm

This chapter provides an introduction to this volume on social networks. It argues that social network analysis is greater than a method or data, but serves as a central paradigm for understanding social life. The chapter offers evidence of the influence of social network analysis with a bibliometric analysis of research on social networks. This analysis underscores how pervasive network analysis has become and highlights key theoretical and methodological concerns. It also introduces the sections of the volume broadly structured around theory, methods, broad conceptualizations like culture and temporality, and disciplinary contributions. The chapter concludes by discussing several promising new directions in the field of social network analysis.

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