Enhancing Online Communities with Cycle-Sharing for Social Networks

2012 ◽  
pp. 161-195 ◽  
Author(s):  
Nuno Apolónia ◽  
Paulo Ferreira ◽  
Luís Veiga
Keyword(s):  
Social Networks ◽  
Online Communities

Social Identities, Group Formation, and the Analysis of Online Communities

2010 ◽  
pp. 1346-1361 ◽  
Author(s):  
Jillianne R. Code ◽  
Nicholas E. Zaparyniuk
Keyword(s):  
Social Networks ◽  
Social Identity ◽  
Online Communities ◽  
Collective Identity ◽  
Online Social Networks ◽  
Online Social Network ◽  
Group Formation ◽  
Social Identities ◽  
New Members ◽  
The Individual

Central to research in social psychology is the means in which communities form, attract new members, and develop over time. Research has found that the relative anonymity of Internet communication encourages self-expression and facilitates the formation of relationships based on shared values and beliefs. Self-expression in online social networks enables identity experimentation and development. As identities are fluid, situationally contingent, and are the perpetual subject and object of negotiation within the individual, the presented and perceived identity of the individual may not match reality. In this chapter, the authors consider the psychological challenges unique to understanding the dynamics of social identity formation and strategic interaction in online social networks. The psychological development of social identities in online social network interaction is discussed, highlighting how collective identity and self-categorization associates social identity to online group formation. The overall aim of this chapter is to explore how social identity affects the formation and development of online communities, how to analyze the development of these communities, and the implications such social networks have within education.

Social Identities, Group Formation, and the Analysis of Online Communities

2010 ◽  
pp. 86-101 ◽  
Author(s):  
Jillianne R. Code ◽  
Nicholas E. Zaparyniuk
Keyword(s):  
Social Networks ◽  
Social Identity ◽  
Online Communities ◽  
Collective Identity ◽  
Online Social Networks ◽  
Online Social Network ◽  
Group Formation ◽  
Social Identities ◽  
New Members ◽  
The Individual

Central to research in social psychology is the means in which communities form, attract new members, and develop over time. Research has found that the relative anonymity of Internet communication encourages self-expression and facilitates the formation of relationships based on shared values and beliefs. Self-expression in online social networks enables identity experimentation and development. As identities are fluid, situationally contingent, and are the perpetual subject and object of negotiation within the individual, the presented and perceived identity of the individual may not match reality. In this chapter, the authors consider the psychological challenges unique to understanding the dynamics of social identity formation and strategic interaction in online social networks. The psychological development of social identities in online social network interaction is discussed, highlighting how collective identity and self-categorization associates social identity to online group formation. The overall aim of this chapter is to explore how social identity affects the formation and development of online communities, how to analyze the development of these communities, and the implications such social networks have within education.

The Influence of Social Networks on E-Reputation

2014 ◽  
Vol 10 (4) ◽  
pp. 65-79 ◽  
Author(s):  
Sylvaine Castellano ◽  
Insaf Khelladi ◽  
Amélie Chipaux ◽  
Célia Kupferminc
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Communities ◽  
The Internet ◽  
Use Of Social Media ◽  
Online Reputation ◽  
The Relationship

With the increased importance of the Internet and the use of social media, new opportunities and challenges emerge to manage the relationship with audiences and online communities. While the professional world already acknowledged such dynamics, further analysis is needed in the academic scene. A survey conducted in the sports setting shows that the perception of social networks influences athletes' e-reputation. However, the motives for following athletes online have no influence on their e-reputation. Finally, the results highlight that e-reputation is not affected by negative content on the internet. This research has both academic and managerial contributions regarding online reputation and social media.

scholarly journals A poststructuralist review of selfies: Moving beyond heteronormative visual rhetoric

2016 ◽  
Vol 1 (1) ◽  
pp. 4-14
Author(s):  
Patricia Routh
Keyword(s):  
Social Networks ◽  
Gender Identity ◽  
Mobile Devices ◽  
Online Communities ◽  
Visual Rhetoric ◽  
Human Subject ◽  
Deleuze And Guattari ◽  
Specific Focus ◽  
Starting Point ◽  
Production And Distribution

Mobile devices can instantly create and distribute a digital self-portrait, or ‘selfie’ across a myriad of social networks. The word ‘selfie’ summarises a particular kind of cultural and photographic practice that is motivated by a combination of the agency and aspirational biases of the selfie producer and where they prefer to share on social networks. With a specific focus on gendered selfie production, this paper aims to explore the relevant theories for gender identity within online communities in which selfies are shared. From a theoretical starting point, firstly this paper employs the poststructuralist theories (Deleuze and Guattari, 1980) as interpretative filters for a decisive understanding of the inner “rhizome” of an individual’s ideal of “becoming”. This paper argues that the embodied human subject is transformed by self-exploration with the production and distribution of their selfies.

scholarly journals Virtual Goods: Good for Business?

1970 ◽  
Vol 2 (4) ◽  
Author(s):  
Nic Mitham
Keyword(s):  
Social Networks ◽  
User Experience ◽  
Virtual Worlds ◽  
Online Communities ◽  
Virtual World ◽  
The Internet ◽  
Good For ◽  
Mini Games

Whilst 2008 saw the emergence of the virtual worlds sector, 2009 has to be called the year of the virtual good. With online destinations such as social networks seeing a creation of brand-new revenue steams and virtual worlds ‘giving the users want they want’, the virtual goods sector is one of the fastest growing areas of the Internet. In its most popular form, virtual goods relate to accessories for avatars–clothing, hair and other person-related apparel. These are purchased by users to customize their appearance and are popular across all types of virtual worlds, from kids and tweens right through grown-up worlds and also apply across all genres. There is an incumbent demand for users to want to change andcontrol how they are seen in virtual worlds. But virtual goods don’t just include avatar appearance customization. Online communities are learning how to monetize all aspects of the user experience, including the ability, for example, to buy a bespoke user name or access specific areas inside a virtual world. On the SocNet side, virtual goods are being used to great effect with social/mini-games, providing ‘tools’ to complete a game faster/level-up.

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.

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