The analysis of social capital in online social communities

Social networks have proven to be an attractive avenue of investigation for researchers since humans are social creatures. Numerous literature have explored the term “social networks” from different perspectives and in diverse research fields. With the popularity of the Internet, social networking has taken on a new dimension. Online social communities therefore have become an emerging social avenue for people to communicate in today’s information age. People use online social communities to share their interests, maintain friendships, and extend their so-called circle of “friends”. Likewise, social capital, also known as human capital, is an important theory in sociology. Researchers usually utilise social capital theory when they investigate the topic relating to social networks. However, there is little literature that can provide an explicit and strong assertion in that research area due to the complexity of social capital. This thesis therefore focuses on the issue related to providing a better understanding about the relationship between social capital and online social communities. To enhance the value within the scope of this analysis, an online survey was conducted to examine the effects of the dimensions of social capital: relational capital, structural capital, and cognitive capital, determining the intensity of using online social communities. The data were derived from a total of 350 self-selected respondents completing an online survey during the research period. The main results indicate that social capital exists in online social communities under normal circumstances. Finally, this thesis also presents three contributions for both theory and practice in Chapter 5. The main results contribute to the understanding of connectivity in the interrelationships between individual social capital exchange within online social networks. Secondly, social trust was found to have a weak effect in influencing the intensity of individuals using online social communities. Third, the perpetual role of information sharing has an indirect influence on individual users participating in online social communities. This study also benefits online marketing consultants as marketers can not only gain consumer information easier from online social communities but also this understanding assists in designing effective communication within online social communities. The cross-sectional study, the reliability of Internet survey data, and sampling issues are the major three limitations in this research. The thesis provides a new research model and recommends that the mediating effects, privacy paradox, and social trust on online social communities should be further explored in future research.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Co-creating games: A co-evolutionary analysis

ABSTRACT. The phenomenon of consumer co-creation is often framed in terms of whether either economic market forces or socio-cultural non-market forces ultimately dominate. We propose an alternate model of consumer co-creation in terms of co-evolution between markets and non-markets. Our model is based on a recent ethnographic study of a massively multiplayer online game through its development, release and ultimate failure, and cast in terms of two explanatory models: multiple games and social network markets. We conclude that consumer co-creation is indeed complex, but in ways that relate to both emergent market expectations and the evolution of markets, not to the transcendence of markets.

Inter- and intra- project knowledge transfer : analysis of knowledge transfer techniques

Many studies in the area of project management and social networks have identified the significance of project knowledge transfer within and between projects. However, only few studies have examined the intra- and inter-projects knowledge transfer activities. Knowledge in projects can be transferred via face-to-face interactions on the one hand, and via IT-based tools on the other. Although companies have allocated many resources to the IT tools, it has been found that they are not always effectively utilised, and people prefer to look for knowledge using social face-to-face interactions. This paper explores how to effectively leverage two alternative knowledge transfer techniques, face-to-face and IT-based tools to facilitate knowledge transfer and enhance knowledge creation for intra- and inter-project knowledge transfer. The paper extends the previous research on the relationships between and within teams by examining the project’s external and internal knowledge networks concurrently. Social network qualitative analysis, using a case study within a small-medium enterprise, was used to examine the knowledge transfer activities within and between projects, and to investigate knowledge transfer techniques. This paper demonstrates the significance of overlapping employees working simultaneously on two or more projects and their impact on facilitating knowledge transfer between projects within a small/medium organisation. This research is also crucial to gaining better understanding of different knowledge transfer techniques used for intra- and inter-project knowledge exchange. The research provides recommendations on how to achieve better knowledge transfer within and between projects in order to fully utilise a project’s knowledge and achieve better project performance.

Do board contacts matter? : an analysis of the relationship between boards of directors’ ties and the performance of Australia’s largest companies.

Boards of directors are thought to provide access to a wealth of knowledge and resources for the companies they serve, and are considered important to corporate governance. Under the Resource Based View (RBV) of the firm (Wernerfelt, 1984) boards are viewed as a strategic resource available to firms. As a consequence there has been a significant research effort aimed at establishing a link between board attributes and company performance. In this thesis I explore and extend the study of interlocking directorships (Mizruchi, 1996; Scott 1991a) by examining the links between directors’ opportunity networks and firm performance. Specifically, I use resource dependence theory (Pfeffer & Salancik, 1978) and social capital theory (Burt, 1980b; Coleman, 1988) as the basis for a new measure of a board’s opportunity network. I contend that both directors’ formal company ties and their social ties determine a director’s opportunity network through which they are able to access and mobilise resources for their firms. This approach is based on recent studies that suggest the measurement of interlocks at the director level, rather than at the firm level, may be a more reliable indicator of this phenomenon. This research uses publicly available data drawn from Australia’s top-105 listed companies and their directors in 1999. I employ Social Network Analysis (SNA) (Scott, 1991b) using the UCINET software to analyse the individual director’s formal and social networks. SNA is used to measure a the number of ties a director has to other directors in the top-105 company director network at both one and two degrees of separation, that is, direct ties and indirect (or ‘friend of a friend’) ties. These individual measures of director connectedness are aggregated to produce a board-level network metric for comparison with measures of a firm’s performance using multiple regression analysis. Performance is measured with accounting-based and market-based measures. Findings indicate that better-connected boards are associated with higher market-based company performance (measured by Tobin’s q). However, weaker and mostly unreliable associations were found for accounting-based performance measure ROA. Furthermore, formal (or corporate) network ties are a stronger predictor of market performance than total network ties (comprising social and corporate ties). Similarly, strong ties (connectedness at degree-1) are better predictors of performance than weak ties (connectedness at degree-2). My research makes four contributions to the literature on director interlocks. First, it extends a new way of measuring a board’s opportunity network based on the director rather than the company as the unit of interlock. Second, it establishes evidence of a relationship between market-based measures of firm performance and the connectedness of that firm’s board. Third, it establishes that director’s formal corporate ties matter more to market-based firm performance than their social ties. Fourth, it establishes that director’s strong direct ties are more important to market-based performance than weak ties. The thesis concludes with implications for research and practice, including a more speculative interpretation of these results. In particular, I raise the possibility of reverse causality – that is networked directors seek to join high-performing companies. Thus, the relationship may be a result of symbolic action by companies seeking to increase the legitimacy of their firms rather than a reflection of the social capital available to the companies. This is an important consideration worthy of future investigation.

The role of social capital in reducing negative health outcomes among police officers

This paper investigates the role of social capital on the reduction of short and long run negative health effects associated with stress, as well as indicators of burnout among police officers. Despite the large volume of research on either social capital or the health effects of stress, the interaction of these factors remains an underexplored topic. In this empirical analysis we aim to reduce such a shortcoming focusing on a highly stressful and emotionally draining work environment, namely law enforcement agents who perform as an essential part of maintaining modern society. Using a multivariate regression analysis focusing on three different proxies of health and three proxies for social capital conducting also several robustness checks, we find strong evidence that increased levels of social capital is highly correlated with better health outcomes. Additionally we observe that while social capital at work is very important, social capital in the home environment and work-life balance are even more important. From a policy perspective, our findings suggest that work and stress programs should actively encourage employees to build stronger social networks as well as incorporate better working/home life arrangements.

Settlement geography of African refugee communities in Southeast Queensland : an analysis of residential distribution and secondary migration

Before 2001, most Africans immigrating to Australia were white South Africans and Zimbabweans who arrived as economic and family-reunion migrants (Cox, Cooper & Adepoju, 1999). Black African communities are a more recent addition to the Australian landscape, with most entering Australia as refugees after 2001. African refugees are a particularly disadvantaged immigrant group, which the Department of Immigration and Multicultural Affairs (in the Community Relations Commission of New South Wales, 2006) suggests require high levels of settlement support (p.23). Decision makers and settlement service providers need to have settlement data on the communities so that they can be effective in planning, budgeting and delivering support where it is most needed. Settlement data are also useful for determining the challenges that these communities face in trying to establish themselves in resettlement. There has been no verification of existing secondary data sources, however, or previous formal study of African refugee settlement geography in Southeast Queensland. This research addresses the knowledge gap by using a mixed-method approach to identify and describe the distribution and population size of eight African communities in Southeast Queensland, examine secondary migration patterns in these communities and assess the relationship between these geographic features and housing, a critical factor in successful settlement. Significant discrepancies exist between the primary data gathered in the study and existing secondary data relating to population size and distribution of the communities. Results also reveal a tension between the socio-cultural forces and the housing and economic imperatives driving secondary migration in the communities, and a general lack of engagement by African refugees with structured support networks. These findings have a wide range of implications for policy and for groups that provide settlement support to these communities.

A social matching system for an online dating network : a preliminary study

Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.

Education for the creative economy : innovation, transdisciplinarity, and networks

The question posed in this chapter is: To what extent does current education theory and practice prepare graduates for the creative economy? We first define what we mean by the term creative economy, explain why we think it is a significant point of focus, derive its key features, describe the human capital requirements of these features, and then discuss whether current education theory and practice are producing these human capital requirements. The term creative economy can be critiqued as a shibboleth, but as a high level metaphor, it nevertheless has value in directing us away from certain sorts of economic activity and toward other kinds. Much economic activity is in no way creative. If I have a monopoly on some valued resource, I do not need to be creative. Other forms of economic activity are intensely creative. If I have no valued resources, I must create something that is valued. At its simplest and yet most profound, the idea of a creative economy suggests a capacity to compete based on engaging in a gainful activity that is different from everyone else’s, rather than pursuing the same endeavor more competitively than everyone else. The ability to differentiate on novelty is key to the concept of creative economy and key to our analysis of education for this economy. Therefore, we follow Potts and Cunningham (2008, p. 18) and Potts, Cunningham, Hartley, and Ormerod (2008) in their discussion of the economic significance of the creative industries and see the creative economy not as a sector but as a set of economic processes that act on the economy as a whole to invigorate innovation based growth. We see the creative economy as suffused with all industry rather than as a sector in its own right. These economic processes are essentially concerned with the production of new ideas that ultimately become new products, service, industry sectors, or, in some cases, process or product innovations in older sectors. Therefore, our starting point is that modern economies depend on innovation, and we see the core of innovation as new knowledge of some kind. We commence with some observations about innovation.

Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

Corrupt police networks : uncovering hidden relationship patterns, functions and roles

This article applies social network analysis techniques to a case study of police corruption in order to produce findings which will assist in corruption prevention and investigation. Police corruption is commonly studied but rarely are sophisticated tools of analyse engaged to add rigour to the field of study. This article analyses the ‘First Joke’ a systemic and long lasting corruption network in the Queensland Police Force, a state police agency in Australia. It uses the data obtained from a commission of inquiry which exposed the network and develops hypotheses as to the nature of the networks structure based on existing literature into dark networks and criminal networks. These hypotheses are tested by entering the data into UCINET and analysing the outcomes through social network analysis measures of average path distance, centrality and density. The conclusions reached show that the network has characteristics not predicted by the literature.

Challenges of tracking topical discussion networks online

Attempts to map online networks, representing relationships between people and sites, have covered sites including Facebook, Twitter, and blogs. However, the predominant approach of static network visualization, treating months of data as a single case rather than depicting changes over time or between topics, remains a flawed process. As different events and themes provoke varying interactions and conversations, it is proposed that case-by-case analysis would aid studies of online social networks by further examining the dynamics of links and information flows. This study uses hyperlink analysis of a population of French political blogs to compare connections between sites from January to August 2009. Themes discussed in this period were identified for subsequent analysis of topic-oriented networks. By comparing static blogrolls with topical citations within posts, this research addresses challenges and methods in mapping online networks, providing new information on temporal aspects of linking behaviors and information flows within these systems.

Leveraging social network data for analytical CRM strategies : the introduction of social BI

The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

The governance of inter-organisational decision-making : understanding the impacts of informal networks on formal decision-making regimes in the Brisbane Airport region

Airports and cities inevitably recognise the value that each brings the other; however, the separation in decision-making authority for what to build, where, when and how provides a conundrum for both parties. Airports often want a say in what is developed outside of the airport fence, and cities often want a say in what is developed inside the airport fence. Defining how much of a say airports and cities have in decisions beyond their jurisdictional control is likely to be a topic that continues so long as airports and cities maintain separate formal decision-making processes for what to build, where, when and how. However, the recent Green and White Papers for a new National Aviation Policy have made early inroads to formalising relationships between Australia’s major airports and their host cities. At present, no clear indication (within practice or literature) is evident to the appropriateness of different governance arrangements for decisions to develop in situations that bring together the opposing strategic interests of airports and cities; thus leaving decisions for infrastructure development as complex decision-making spaces that hold airport and city/regional interests at stake. The line of enquiry is motivated by a lack of empirical research on networked decision-making domains outside of the realm of institutional theorists (Agranoff & McGuire, 2001; Provan, Fish & Sydow, 2007). That is, governance literature has remained focused towards abstract conceptualisations of organisation, without focusing on the minutia of how organisation influences action in real-world applications. A recent study by Black (2008) has provided an initial foothold for governance researchers into networked decision-making domains. This study builds upon Black’s (2008) work by aiming to explore and understand the problem space of making decisions subjected to complex jurisdictional and relational interdependencies. That is, the research examines the formal and informal structures, relationships, and forums that operationalise debates and interactions between decision-making actors as they vie for influence over deciding what to build, where, when and how in airport-proximal development projects. The research mobilises a mixture of qualitative and quantitative methods to examine three embedded cases of airport-proximal development from a network governance perspective. Findings from the research provide a new understanding to the ways in which informal actor networks underpin and combine with formal decision-making networks to create new (or realigned) governance spaces that facilitate decision-making during complex phases of development planning. The research is timely, and responds well to Isett, Mergel, LeRoux, Mischen and Rethemeyer’s (2011) recent critique of limitations within current network governance literature, specifically to their noted absence of empirical studies that acknowledge and interrogate the simultaneity of formal and informal network structures within network governance arrangements (Isett et al., 2011, pp. 162-166). The combination of social network analysis (SNA) techniques and thematic enquiry has enabled findings to document and interpret the ways in which decision-making actors organise to overcome complex problems for planning infrastructure. An innovative approach to using association networks has been used to provide insights to the importance of the different ways actors interact with one another, thus providing a simple yet valuable addition to the increasingly popular discipline of SNA. The research also identifies when and how different types of networks (i.e. formal and informal) are able to overcome currently known limitations to network governance (see McGuire & Agranoff, 2011), thus adding depth to the emerging body of network governance literature surrounding limitations to network ways of working (i.e. Rhodes, 1997a; Keast & Brown, 2002; Rethemeyer & Hatmaker, 2008; McGuire & Agranoff, 2011). Contributions are made to practice via the provision of a timely understanding of how horizontal fora between airports and their regions are used, particularly in the context of how they reframe the governance of decision-making for airport-proximal infrastructure development. This new understanding will enable government and industry actors to better understand the structural impacts of governance arrangements before they design or adopt them, particularly for factors such as efficiency of information, oversight, and responsiveness to change.