951 resultados para Social systems


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In sustainable development projects, as well as other types of projects, knowledge transfer is important for the organisations managing the project. Nevertheless, knowledge transfer among employees does not happen automatically and it has been found that the lack of social networks and the lack of trust among employees are the major barriers to effective knowledge transfer. Social network analysis has been recognised as a very important tool for improving knowledge transfer in the project environment. Transfer of knowledge is more effective where it depends heavily on social networks and informal dialogue. Based on the theory of social capital, social capital consists of two parts: conduits network and resource exchange network. This research studies the relationships among performance, the resource exchange network (such as the knowledge network) and the relationship network (such as strong ties network, energy network, and trust network) at the individual and project levels. The aim of this chapter is to present an approach to overcoming the lack of social networks and lack of trust to improve knowledge transfer within project-based organisations. This is to be done by identifying the optimum structure of relationship networks and knowledge networks within small and medium projects. The optimal structure of the relationship networks and knowledge networks is measured using two dimensions: intra-project and inter-project. This chapter also outlines an extensive literature review in the areas of social capital, knowledge management and project management, and presents the conceptual model of the research approach.

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Web applications such as blogs, wikis, video and photo sharing sites, and social networking systems have been termed ‘Web 2.0’ to highlight an arguably more open, collaborative, personalisable, and therefore more participatory internet experience than what had previously been possible. Giving rise to a culture of participation, an increasing number of these social applications are now available on mobile phones where they take advantage of device-specific features such as sensors, location and context awareness. This international volume of book chapters will make a contribution towards exploring and better understanding the opportunities and challenges provided by tools, interfaces, methods and practices of social and mobile technology that enable participation and engagement. It brings together an international group of academics and practitioners from a diverse range of disciplines such as computing and engineering, social sciences, digital media and human-computer interaction to critically examine a range of applications of social and mobile technology, such as social networking, mobile interaction, wikis, twitter, blogging, virtual worlds, shared displays and urban sceens, and their impact to foster community activism, civic engagement and cultural citizenship.

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Engineering graduates of today are required to adapt to a rapidly changing work environment. In particular, they are expected to demonstrate enhanced capabilities in both mono-disciplinary and multi-disciplinary teamwork environments. Engineering education needs, as a result, to further focus on developing group work capabilities amongst engineering graduates. Over the last two years, the authors trialed various group work strategies across two engineering disciplines. In particular, the effect of group formation on students' performance, task management, and social loafing was analyzed. A recently developed online teamwork management tool, Teamworker, was used to collect students' experience of the group work. Analysis showed that students who were allowed to freely allocate to any group were less likely to report loafing from other team members, than students who were pre-allocated to a group. It also showed that performance was more affected by the presence or absence of a leader in pre-allocated rather than free-allocated groups.

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Agile ridesharing aims to utilise the capability of social networks and mobile phones to facilitate people to share vehicles and travel in real time. However the application of social networking technologies in local communities to address issues of personal transport faces significant design challenges. In this paper we describe an iterative design-based approach to exploring this problem and discuss findings from the use of an early prototype. The findings focus upon interaction, privacy and profiling. Our early results suggest that explicitly entering information such as ride data and personal profile data into formal fields for explicit computation of matches, as is done in many systems, may not be the best strategy. It might be preferable to support informal communication and negotiation with text search techniques.

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This report analyses the national curriculum and workforce needs of the social work and human services workforce. Australia’s community and health services are among the fastest growing sectors of employment in the nation but the sustainability of an appropriately qualified workforce is threatened. Yet there is little integration of education and workforce planning for the community services sector. This contrasts markedly with the health services sector, where key stakeholders are collaboratively addressing workforce challenges. Our research confirmed rapid growth in the social work and human services workforce and it also identified: • an undersupply of professionally qualified social work and human service practitioners to meet workforce demand; • the rapid ageing of the workforce with many workers approaching retirement; • limited career and salary structures creating disincentives to retention; • a highly diverse qualification base across the workforce. This diversity is inconsistent with the specialist knowledge and skills required of practitioners in many domains of community service provision. Our study revealed a lack of co-ordination across VET and higher education to meet the educational needs of the social work and human services workforce. Our analysis identified: • strong representation of equity groups in social work and related human service programs, although further participation of these groups is still needed; • the absence of clear articulation pathways between VET and higher education programs due the absence of co-ordination and planning between these sectors; • substantial variation in the content of the diverse range of social work and human service programs, with accredited programs conforming to national standards and some others in social and behavioural sciences lacking any external validation; • financial obstacles and disincentives to social work and human service practitioners in achieving postgraduate level qualifications. We recommend that: • DEEWR identify accredited social work and human services courses as a national education priority (similar to education and nursing). This will help ensure the supply of professional workers to this sector; • VET and higher education providers are encouraged to collaboratively develop clear and accessible educational pathways across the educational sectors; • DEEWR undertake a national workforce analysis and planning processes in collaboration with CSDMAC, and all social and community services stakeholders, to ensure workforce sustainability; and • COAG develop a national regulation framework for the social and community services workforce. This would provide sound accountability systems, and rigorous practice and educational standards necessary for quality service provision. It will also ensure much needed public confidence in this workforce.

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Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

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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%.

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Comparison is widely used in research projects and commercial products whose goal is to motivate energy saving at home. This research builds on fundamental theories from social psychology in an attempt to shed light on how to motivate consumers to conserve energy by providing relevant people for social comparison depending on consumer’s motivation to compare. To support the research process, the mobile application EnergyWiz was developed through a theory-driven design approach. Along with other features EnergyWiz provides users with three types of social comparison – normative, one-on-one and ranking. The results of interviews with prospective users are used to derive design suggestions for relevant people for comparison (comparison subjects).

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In this chapter, we describe and explore social relationship patterns associated with outstanding innovation. In doing so, we draw upon the findings of 16 in-depth interviews with award-winning Australian innovators from science & technology and the creative industries. The interviews covered topics relating to various influences on individual innovation capacity and career development. We found that for all of the participants, innovation was a highly social process. Although each had been recognised individually for their innovative success, none worked in isolation. The ability to generate innovative outcomes was grounded in certain types of interaction and collaboration. We outline the distinctive features of the social relationships which seem to be important to innovation, and ask which ‘social network capabilities’ might underlie the ability to create an optimal pattern of interpersonal relationships. We discuss the implications of these findings for universities, which we argue play a key role in the development of nascent innovators.

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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).

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This thesis articulates a methodology that can be applied to the analysis and design of underlying organisational structures and processes that will consistently and effectively address ‘wicked problems’ (the most difficult class of problems that we can conceptualise: problems which consist of ‘clusters’ of problems; problems within these clusters cannot be solved in isolation from one another, and include sociopolitical and moral-spiritual issues (Rittel and Webber 1973)) in forestry. This transdisciplinary methodology has been developed from the perspective of institutional economics synthesised with perspectives from ecological economics and system dynamics. The institutionalist policymaking framework provides an approach for the explicit development of holistic policy. An illustrative application of this framework has been applied to the wicked problem of forestry in southern Tasmania as an example of the applicability of the approach in the Australian context. To date all attempts to seek solutions to that prevailing wicked problem set have relied on non-reflexive, partial and highly reductionist thinking. A formal assessment of prevailing governance and process arrangements applying to that particular forestry industry has been undertaken using the social fabric matrix. This methodology lies at the heart of the institutionalist policymaking framework, and allows for the systematic exploration of elaborately complex causal links and relationships, such as are present in southern Tasmania. Some possible attributes of an alternative approach to forest management that sustains ecological, social and economic values of forests have been articulated as indicative of the alternative policy and management outcomes that real-world application of this transdisciplinary, discursive and reflexive framework may crystallise. Substantive and lasting solutions to wicked problems need to be formed endogenously, that is, from within the system. The institutionalist policymaking framework is a vehicle through which this endogenous creation of solutions to wicked problems may be realised.

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A remarkable growth in quantity and popularity of online social networks has been observed in recent years. There is a good number of online social networks exists which have over 100 million registered users. Many of these popular social networks offer automated recommendations to their users. This automated recommendations are normally generated using collaborative filtering systems based on the past ratings or opinions of the similar users. Alternatively, trust among the users in the network also can be used to find the neighbors while making recommendations. To obtain the optimum result, there must be a positive correlation exists between trust and interest similarity. Though the positive relations between trust and interest similarity are assumed and adopted by many researchers; no survey work on real life people’s opinion to support this hypothesis is found. In this paper, we have reviewed the state-of-the-art research work on trust in online social networks and have presented the result of the survey on the relationship between trust and interest similarity. Our result supports the assumed hypothesis of positive relationship between the trust and interest similarity of the users.

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In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

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know personally. They also communicate with other members of the network who are the friends of their friends and may be friends of their friend’s network. They share their experiences and opinions within the social network about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Opinions, reputations and ecommendations will influence users' choice and usage of online resources. Recommendations may be received through a chain of friends of friends, so the problem for the user is to be able to evaluate various types of trust recommendations and reputations. This opinion or ecommendation has a great influence to choose to use or enjoy the item by the other user of the community. Users share information on the level of trust they explicitly assign to other users. This trust can be used to determine while taking decision based on any recommendation. In case of the absence of direct connection of the recommender user, propagated trust could be useful.