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The purpose of this paper is to investigate the theoretical foundations of the solidarity network concept and its perceived utility as an enabling force for social organizations to influence change. The theoretical framework presented is intended to stimulate dialogue, interest and investigation on the subject of solidarity networks.

The paper adopts a discourse analysis‐type approach to developing a theoretical framework for conceptualizing solidarity networks through an analytical review of existing literature on solidarity and solidarity networks. It is through consideration of this literature that the “threads” of a theoretical model for solidarity networks are “woven” together.

Based on the findings of the analysis the paper asserts that the following characteristics are among the defining elements of solidarity networks and help to form the basis of a theoretical framework that strives to create a more cohesive understanding and an applied exploration for future analytical investigations. These characteristics are: support for “broad” values, anti‐oppression and vision‐based solidarity for the future; the flexibility and adaptability of the network's organizational structure and issue‐area(s) of focus; that network members are motivated by a sense of mutuality, or mutual self‐interest; that network members are motivated by “high‐order” values associated with the “public good”; and that there is a demonstrated ethic of social responsibility and social justice.

The paper represents a theoretically‐based approach to conceptualizing solidarity networks. It adds new dimensions to one's thinking about social networks as a form of social relationship and social network analysis (SNA) as a “tool” for describing social relationships.

There exist large gaps in research about social networking services, for example in their development. Most of these networks lack any scientific or engineered base in their designing and developing processes. In this paper, a holistic model will be described for the development of social network sites and parts of a scientific social network (SSN) will be developed using it. Users of this site are faculties, students and R&D personnel of a university or an enterprise. The paper aims to discuss these issues.

In this paper, a SSN site is designed along with a brief description of a social network site development methodology. The structure of methodology is based on conceptual template for the construction of a methodology. Using this methodology, a group of 50 users (from all three types of end-users) have been chosen to be interviewed about their expectations from the mentioned site.

Based on the interview, it was discovered that their view about social networks is inflexible and they do not have any new visions about functionalities of these networks. Their emphasis was mostly on exchanging and sharing role of this site. Design and development of social network sites based on the proposed methodology is easily understandable because of using state machine notations.

The innovation of this study is to propose a soft model for social network sites design based on these site's special specifications and regarding differences of them with other regular ones. This can pave the way for investors of such sites for setting up distinct social sites with new functionalities in an innovative approach.

The purpose of this paper is to examine how the introduction of new communication channels facilitates interactive information sharing and collaboration between various actors over social networking services and how social networking fits in the existing European legal framework on data protection. The paper also aims to discuss some specific data protection issues, focusing on the role of the relevant actors, using the example of photo tagging.

Privacy in social networks is one of the main concerns for providers and users. This paper examines the role of the main actors in social networking, i.e. the providers and the users, scrutinised under the light of the European data protection legislation. Specifically, how social networking service providers deal with users' privacy and how users handle their personal information, if this manipulation is complied with the respective legislation and how “tagging”, one of the most familiar services provided by the social networking providers, may cause privacy risks.

Social networking is one of the most remarkable cultural phenomena that has blossomed in the Web 2.0 era. They enable the connection of users and they facilitate the exchange of information among them. However, the users reveal vast amounts of personal information over social networking services, without realising the privacy and security risks arising from their actions. The European data protection legislation could be used as a means for protecting the users against the unlawful processing of their personal information, although a number of problems arise regarding its applicability.

The paper discusses some privacy concerns involved in social networks and examines how social networking service providers and users deal with personal information with regard to the European data protection legislation.

The purpose of this paper is to demonstrate novel techniques for exploring relationship data extracted from social media sites for actionable insights by educators, researchers, and administrators.

The paper demonstrates how non‐programmers can use NodeXL, an open source social network analysis tool built into Excel 2007/2010, to collect, analyze, and visualize network data from social media sites like Twitter and YouTube.

Researchers and education professionals can use NodeXL to explore (a) social networks to identify important individuals and subgroups, as well as (b) content networks to map the underlying structure of a domain and find important content. Illustrative examples are provided using NodeXL to examine followers of a Twitter user focused on open education, as well as a content network of YouTube videos about surgery.

Tools like NodeXL are making network analysis accessible to non‐technical researchers in a variety of fields spanning the sciences, social sciences, and the humanities. Despite their value, network analysis techniques are only as good as the data that underlie them, requiring careful assessment of possible selection biases and triangulation of findings.

Educational institutions and educators can benefit from more systematically analyzing their social media initiatives from a network perspective.

This paper describes some of the techniques and tools needed to make sense of the social relationships that underlie social media sites. As relational data are increasingly made public, such techniques will enable more systematic analysis by researchers studying social phenomena and practitioners implementing social media initiatives.

This paper aims to analyze how business units can use their employees’ external social capital to explore and exploit the resources available in their environment. Based on multiple interviews with the employees of the global commodity firm Gamma Chemical (around 50,000 employees), the research aims at gaining an understanding of the contextual conditions required to successfully build and leverage individuals’ external social client network ties for business unit ambidexterity.

The authors conducted a single-case study at Gamma Chemical that entailed 33 semi-directive interviews, each of which lasted 1-4 h, at different organizational levels (ranging from top-level management to production workers). We had access to three regional business units. The interviews addressed the links between the individuals in the business units and external actors. The authors also collected information about the company’s strategic objectives, the local competitive environment and work organization. Open-ended questions were used to allow the interviewees to freely relate anecdotes about their own network development. In particular, the authors asked the respondents to identify business contacts with whom they interacted privately and to describe the relationships.

The research findings are two-fold. First, and contrary to prior studies, the authors find that individuals’ social capital contributes to both exploration and exploitation at the business unit level. Second, developing and leveraging individuals’ external social capital requires a specific organizational context at the business unit level that allows employees to develop and nurture their personal business relationships with clients.

The study is limited by the scope of the sample (a study of one large multinational firm). Further research conducted in similar contexts may therefore be useful for comparability purposes and to generalize the results.

Several practical recommendations describe how managers can effectively make use of their employees’ social connections with clients. In particular, the results suggest that managers should seek business unit flexibility on the basis of team-based structures, an autonomous leadership style and by actively creating a degree of critical social network tie redundancy, encouraging a shared network culture. These three specific conditions allow employees’ personal client networks to not only flourish but also contribute to business unit ambidexterity.

Prior social capital studies have analyzed intra-firm and inter-firm relationships in terms of contributing to firm ambidexterity. However, these findings have often been difficult to translate into specific organizational levels. Given business units’ critical role in identifying and implementing business opportunities for a firm, the authors focus on the micro-foundations of exploratory and exploitative learning by using a social capital perspective to explore the link between employees’ private external social relationships with clients and business unit ambidexterity. In this way, we contribute to the social capital literature and research on business unit ambidexterity and to extant contextual ambidexterity research by specifying the conditions that help firms develop and leverage their employees’ own external social capital for exploration and exploitation.

The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.

The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.

Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.

To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.

This paper aims to conceptualize a framework drawn upon the self-regulation theory to study the effect of system quality features on the continuous usage intention of social network users. The study explores the relationship among the selected variables and identifies the determinants of continuous usage intention of social networks.

A survey method was used to collect data from 301 male and 311 female social network users to test the research model with the help of the structural equation modelling technique.

The results show a difference between male and female social media users for the continuous usage intention of social networks. A substantial difference in the relationship was seen between the attitude and continuous usage intention, where female social network users had a more robust and significant relationship than their male counterparts.

This study uses the self-regulation theory to understand the continuous usage intention of social networks in the Indian context. This research study contributes to the existing literature on social networks/social media and the adoption intention.

The study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.

Social network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.

The results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.

The study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

Online social networks can bridge the gap between distant individuals by simulating online experiences that closely resemble physical interactions. While people have positive experiences, such as joy, in a physical relationship and would like to enjoy those experiences online, they also have negative experiences, such as being subject to a lie. An online social network may allow users to lie to simulate a real-world social group better. However, lying must be prevented on social networks as unethical behavior. Thus, this study aims to investigate an ethical dilemma raised due to the two abovementioned perspectives.

This paper examines different aspects of lying in social networks, using a comprehensive descriptive literature review approach and a classification scheme.

Contrary to their initial intent, social networks are disrupting the traditional notion of human interaction, either by disregarding the presence of dishonesty or by attempting to regulate relationships. In this research, the authors examine the challenges of these two perspectives by identifying enablers, consequences and control measures of lying on social networks at the individual, social and technological levels. The authors also develop a framework to facilitate investigating this dilemma.

This paper examines a controversial topic. Although lying is unethical, allowing users to lie may be considered an appealing feature of social network platforms. This paper offers a framework to propose several research directions for future studies. This study’s examination focuses on the challenges associated with deception on social networks, prompting the formulation of three crucial questions regarding the potential impact of technology on such behavior.

Social information is crucial to credit ratings and can improve the accuracy of the traditional credit assessment model. Drawing on the resource-based view (RBV) and social capital theory (SCT), this research explores the relationships between corporate social activities, network centrality and corporate credit behavior.

The authors used social network analysis (SNA) and regression analysis to analyze the data collected from 14,544 enterprises on the Alibaba platform.

The results indicate that among the four types of social activities, the number of corporate questions and posts shows a positive relationship with credit behavior; while the number of corporate comments has negative relationship with credit behavior. Further, degree and betweenness centralities mediate the relationship between the number of corporate questions, posts and comments with credit behavior.

This study contributes to the literature on non-financial factors (soft information) by exploring the social behavioral factors related to corporate credit. In addition, this study offers a new theoretical lens and reasonable explanations for investigating the relationship between corporate social activities, network centrality and credit behavior from the perspective of the resource-based view, while most studies are predictive and methodological. Moreover, this study provides new insights for platforms to evaluate enterprise credit and for managers to improve credit behavior.