Archive for the ‘Social network’ Category
Civic networks of community-based organizations face significant challenges in working together to combat issues facing their community (e.g., gang violence, sex trafficking). In our research, we examined how local organizations tried to build and maintain connectedness over time as a network to fight child sex trafficking. We sought to understand how technology supports the social processes of connectedness in this context. Based on our analysis of the field data from this case study, we identify three categories of activities for building and maintaining connectedness. We also find that while different technologies are suited towards supporting different aspects of connectedness, there may be gaps in how adequately social media tools support connectedness in civic networks.
The findings we present in this paper indicate that there is a critical need for low-cost, more group-centric technologies for maintaining connectedness between community-based organizations over an extended period of time. Our work offers a lens for better understanding a context of an informal civic network where such connectedness needs to be supported as a first step in designing such technologies. This lens can help guide how more group-centric ICTs can be leveraged to create connectedness in civic networks. In future work, we plan to explore design approaches to supporting the processes of awareness-raising in this community-based context.
Modern communities of practice (CoP) built on a foundation of technology and social media are emerging on a global scale. Considering the speed at which technology evolves, best practices also continue to evolve for building, maintaining and measuring the effectiveness of these modern communities. This report attempts to outline and discuss key lessons learned to date and provide several recommendations based upon available evidence and expert opinion. But each CoP – defined here as a group of professionals with similar interests – is unique in purpose and must find its own path to success. While communities once interacted entirely face-to-face, modern communities interact both in person and online, though some purely virtual communities do exist. Typical in-person interaction includes activities such as meetings, seminars, workshops and conferences. Virtual interaction leverages various internet-based social media tools to simulate similar interactions: social networks to link members to each other and interest groups; social media to share content and materials; listservs to facilitate conversation and exchange; and websites to create their “home” on the Web and provide an opportunity for others to learn about them. While face-to-face interactions provide a depth not easily recreated online, virtual ones provide greater access for those unable to attend in-person events. Successful modern communities find a way to integrate both approaches.
Word of mouth has become word of Web. Social networking is here to stay. The reach, benefits, and expectations surrounding social media are endless—matched only by the pitfalls and misconceptions associated with implementing a social media strategy. With social networks blurring the line between business and personal, today’s interactive Web technologies are helping people to connect and share ideas and content with a huge potential audience. What’s more, they’re making this process much faster and more efficient than ever before. Despite the vast reach of social networking, however, most recruiters are facing tremendous pressure to fill open positions from seemingly limited talent pools. As a result, they’re spending more time than ever posting jobs, searching networks, and sifting through résumés for top-quality talent. In fact, most recruiters who have started using social networking tools and technologies have only seen their workloads grow. This white paper demonstrates how you can employ a referral strategy to leverage the power of social networking for measurable ROI.
This paper’s purpose is to review social capital as discussed in the literature, identify controversies and debates, consider some critical issues, and propose conceptual and research strategies in building a theory. I will argue that such a theory and the research enterprise must be based on the fundamental understanding that social capital is captured from embedded resources in social networks . Deviations from this understanding in conceptualization and measurement lead to confusion in analyzing causal mechanisms in the macro- and micro-processes. It is precisely these mechanisms and processes, essential for an interactive theory about structure and action, to which social capital promises to make contributions . By considering social capital as assets in networks, the paper will discuss some issues in conceptualizations, measurements, and causal mechanisms (the factors leading to inequality of social capital and the returns following investments in social capital) . A proposed model will follow . The paper will conclude by calling attention to the rise of a new form of social capital, cybernetworks, and briefly suggesting how research on this topic promises to make important contributions to the research enterprise .
Previous research has focused heavily on community communications as they occur in e.g.
communities of practice. Still, as indicated by the concept of networked individualism, contacts are becoming more networked in nature and group membership is transient. The research presented here yields to the call of Garton et al to move away from the study of communication taking place only in groups and to also investigate the potential of computer-mediated communication to support interaction in unbound and sparsely-knit social networks. As a consequence, in chapters 5 and 6, I’ve adopted a research method which takes the relationship between people as the basic unit of analysis. In conclusion, as work practice in Western economies is evolving towards knowledge work, and knowledge work rests heavily on knowledge sharing, the combination of networked individualism and knowledge sharing seems a relevant subject of study.
Innovation – the process of obtaining, understanding, applying, transforming, managing and transferring knowledge – is a result of human collaboration, but it has become an increasingly complex process, with a growing number of interacting parties involved. Lack of innovation is not necessarily caused by lack of technology or lack of will to innovate, but often by social and cultural forces that jeopardize the cognitive processes and prevent potential innovation. This book focuses on the rule of social capital in the process of innovation: the social networks and the norms; values and attitudes (such as trust) of the actors; social capital as both bonding and bridging links between actors; and social capital as a feature at all spatial levels, from the single inventor to the transnational corporation. Contributors from a wide variety of countries and disciplines explore the cultural framework of innovation through empirics, case studies and examination of conceptual and methodological dilemmas.
Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks, although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others’ positive experiences constitutes a positive experience for people.
The purpose of this chapter is to apply new theoretical constructions to the unique situation of online social networks by investigating the issue of personal and collective empowerment. To better illustrate the applicability of the new theoretical constructions, ideas of identity, false consciousness, and collective intelligence are addressed to demonstrate the tensions in and among the realities of online social networks and their ability to empower individuals and collectivities or to delude those same people into thinking that online social networks enable empowerment.
Social networking is no doubt an important component in empowering individuals, collectivities, and communities – but, while social networks constitute an interesting wedge by which to examine notions of personal or collective power, we need to see that this type of empowerment can only take place if supported by multiple agents in the process of change. Contemporary theories like web theory, network theory, and systems theory all help us understand the relationships between and among human users and technologies – particularly when examined from perspectives of architecture and control (including control by corporations, governments, and other institutions), but the empowerment of the individual is analogous to the power of digital communication, conveying a temporary or ephemeral way of knowing, unless the larger cybernetic system is constantly reinforced by multiple lenses of interpretation. Only then, over time, can we attempt to know or evaluate whether our consciousness has been changed by or through empowerment – or whether we fall into a false consciousness that eludes and deludes our true understanding of meaning.
Collective intelligence can be defined, very broadly, as groups of individuals that do things collectively, and that seem to be intelligent. Collective intelligence has existed for ages. Families, tribes, companies, countries, etc., are all groups of individuals doing things collectively, and that seem to be intelligent. However, over the past two decades, the rise of the Internet has given upturn to new types of collective intelligence. Companies can take advantage from the so-called Web enabled collective intelligence. Web-enabled collective intelligence is based on linking knowledge workers through social media. That means that companies can hire geographically dispersed knowledge workers and create so-called virtual teams of these knowledge workers (members of the virtual teams are connected only via the Internet and do not meet face to face). By providing an online social network, the companies can achieve significant growth of collective intelligence. But to create and use an online social network within a company in a really efficient way, the managers need to have a deep understanding of how such a system works.Thusthe purpose of this paper is to share the knowledge about effective use of social networks in organizations. The main objectives of this paper are as follows: to introduce some good practices of the use of social media in organizations, to analyze these practices and to generalize recommendations for a successful introduction and use of social media to increase collective intelligence of a company.
When making decisions, humans can observe many kinds of information about others’ activities, but their effects on performance are not well understood. We investigated social learning strategies using a simple problem-solving task in which participants search a complex space, and each can view and imitate others’ solutions. Results showed that participants combined multiple sources of information to guide learning, including payoffs of peers’ solutions, popularity of solution elements among peers, similarity of peers’ solutions to their own, and relative payoffs from individual exploration. Furthermore, performance was positively associated with imitation rates at both the individual and group levels. When peers’ payoffs were hidden, popularity and similarity biases reversed, participants searched more broadly and randomly, and both quality and equity of exploration suffered. We conclude that when peers’ solutions can be effectively compared, imitation does not simply permit scrounging, but it can also facilitate propagation of good solutions for further cumulative exploration.