Using mixed methods to track the growth of the Web: tracing open government data initiatives

In recent years, there have been a rising number of Open Government Data (OGD) initiatives; a political, social and technical movement armed with a common goal of publishing government data in open, re-usable formats in order to improve citizen-to-government transparency, efficiency, and democracy. As a sign of commitment, the Open Government Partnership was formed, comprising of a collection of countries striving to achieve OGD. Since its initial launch, the number of countries committed to adopting an Open Government Data agenda has grown to more than 50; including countries from South America to the Far East.Current approaches to understanding Web initiatives such as OGD are still being developed. Methodologies grounded in multidisciplinarity are still yet to be achieved; typically research follows a social or technological approach underpinned by quantitative or qualitative methods, and rarely combining the two into a single analytical framework. In this paper, a mixed methods approach will be introduced, which uses qualitative data underpinned by sociological theory to complement a quantitative analysis using computer science techniques. This method aims to provide an alternative approach to understanding the socio-technical activities of the Web. To demonstrate this, the activities of the UK Open Government Data initiative will be explored using a range of quantitative and qualitative data, examining the activities of the community, to provide a rich analysis of the formation and development of the UK OGD community

On the Role of Social Identity and Cohesion in Characterizing Online Social Communities

Two prevailing theories for explaining social group or community structure are cohesion and identity. The social cohesion approach posits that social groups arise out of an aggregation of individuals that have mutual interpersonal attraction as they share common characteristics. These characteristics can range from common interests to kinship ties and from social values to ethnic backgrounds. In contrast, the social identity approach posits that an individual is likely to join a group based on an intrinsic self-evaluation at a cognitive or perceptual level. In other words group members typically share an awareness of a common category membership. In this work we seek to understand the role of these two contrasting theories in explaining the behavior and stability of social communities in Twitter. A specific focal point of our work is to understand the role of these theories in disparate contexts ranging from disaster response to socio-political activism. We extract social identity and social cohesion features-of-interest for large scale datasets of five real-world events and examine the effectiveness of such features in capturing behavioral characteristics and the stability of groups. We also propose a novel measure of social group sustainability based on the divergence in group discussion. Our main findings are: 1) Sharing of social identities (especially physical location) among group members has a positive impact on group sustainability, 2) Structural cohesion (represented by high group density and low average shortest path length) is a strong indicator of group sustainability, and 3) Event characteristics play a role in shaping group sustainability, as social groups in transient events behave differently from groups in events that last longer

Dynamics in online social networks

An increasing number of today's social interactions occurs using online social media as communication channels. Some online social networks have become extremely popular in the last decade. They differ among themselves in the character of the service they provide to online users. For instance, Facebook can be seen mainly as a platform for keeping in touch with close friends and relatives, Twitter is used to propagate and receive news, LinkedIn facilitates the maintenance of professional contacts, Flickr gathers amateurs and professionals of photography, etc. Albeit different, all these online platforms share an ingredient that pervades all their applications. There exists an underlying social network that allows their users to keep in touch with each other and helps to engage them in common activities or interactions leading to a better fulfillment of the service's purposes. This is the reason why these platforms share a good number of functionalities, e.g., personal communication channels, broadcasted status updates, easy one-step information sharing, news feeds exposing broadcasted content, etc. As a result, online social networks are an interesting field to study an online social behavior that seems to be generic among the different online services. Since at the bottom of these services lays a network of declared relations and the basic interactions in these platforms tend to be pairwise, a natural methodology for studying these systems is provided by network science. In this chapter we describe some of the results of research studies on the structure, dynamics and social activity in online social networks. We present them in the interdisciplinary context of network science, sociological studies and computer science.Comment: 17 pages, 4 figures, book chapte