Reflective learning through social network sites in design education

Reflective learning is vital for successful practice-led education such as animation, multimedia design and graphic design, and social network sites can accommodate various learning styles for effective reflective learning. In this paper, the researcher studies reflective learning through social network sites with two animation units. These units aim to provide students with an understanding of the tasks and workflows involved in the production of style sheets, character sheets and motion graphics for use in 3D productions for film and television and game design. In particular, an assessment in these units requires students to complete their online reflective journals throughout the semester. The reflective learning has been integrated within the unit design and students are encouraged to reflect weekly learning processes and outcomes. A survey evaluating for students’ learning experience was conducted, and its outcomes indicate that social network site based reflective learning will not be effective without considering students’ learning circumstances and designing peer-to-peer interactions.

User-Created Content and Online Social Networks

Traditional media are under assault from digital technologies. Online advertising is eroding the financial basis of newspapers and television, demarcations between different forms of media are fading, and audiences are fragmenting. We can podcast our favourite radio show, data accompanies television programs, and we catch up with newspaper stories on our laptops. Yet mainstream media remain enormously powerful. The Media and Communications in Australia offers a systematic introduction to this dynamic field. Fully updated and revised to take account of recent developments, this third edition outlines the key media industries and explains how communications technologies are impacting on them. It provides a thorough overview of the main approaches taken in studying the media, and includes new chapters on social media, gaming, telecommunications, sport and cultural diversity. With contributions from some of Australia's best researchers and teachers in the field, The Media and Communications in Australia is the most comprehensive and reliable introduction to media and communications available. It is an ideal student text, and a reference for teachers of media and anyone interested in this influential industry.

Improving matching process in social network

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.

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).

Expression and connection : the integration of the reflective learning process and the writing process into social network sites

A number of instructors have recently adopted social network sites (SNSs) for learning. However, the learning design of SNSs often remains at a preliminary level similar to a personal log book because it does not properly include reflective learning elements such as individual reflection and collaboration. This article looks at the reflective learning process and the public writing process as a way of improving the quality of reflective learning on SNSs. It proposes a reflective learning model on SNSs based on two key pedagogical concepts for social networking: individual expression and collaborative connection. It is expected that the model would be helpful for instructors in designing a reflective learning process on SNSs in an effective and flexible way.

Social network market : storytelling on a Web 2.0 original literature site

This article looks at a Chinese Web 2.0 original literature site, Qidian, in order to show the coevolution of market and non-market initiatives. The analytic framework of social network markets (Potts et al., 2008) is employed to analyse the motivations of publishing original literature works online and to understand the support mechanisms of the site, which encourage readers’ willingness to pay for user-generated content. The co-existence of socio-cultural and commercial economies and their impact on the successful business model of the site are illustrated in this case. This article extends the concept of social network markets by proposing the existence of a ripple effect of social network markets through convergence between PC and mobile internet, traditional and internet publishing, and between publishing and other cultural industries. It also examines the side effects of social network markets, and the role of market and non-market strategies in addressing the issues.

A survey on the relationship between trust and interest similarity in online social networks

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.

Managing Trust in Online Social Networks

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.

Trust and reputation management in web-based social network

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.

Social network and aesthetic reflexivity in the creative industries

This article reviews some key critical writing about the commodification or exploitation of networked social relations in the creative industries. Through a comparative case study of networks in fashion and new media industries in the city of Manchester, UK, the article draws attention to the social, cultural and aesthetic aspects of the networks among creative practitioners. It argues that within the increasing commercialisation in the creative industries there are networked spaces within which non-instrumental values are created. The building of social networks reflects on the issue of how creatives perceive their work in these industries both economically and socially/culturally.

An exploration of the technical, social and macro-societal pressures influencing the adoption of online social networking services by organisations

Measuring the business value that Internet technologies deliver for organisations has proven to be a difficult and elusive task, given their complexity and increased embeddedness within the value chain. Yet, despite the lack of empirical evidence that links the adoption of Information Technology (IT) with increased financial performance, many organisations continue to adopt new technologies at a rapid rate. This is evident in the widespread adoption of Web 2.0 online Social Networking Services (SNSs) such as Facebook, Twitter and YouTube. These new Internet based technologies, widely used for social purposes, are being employed by organisations to enhance their business communication processes. However, their use is yet to be correlated with an increase in business performance. Owing to the conflicting empirical evidence that links prior IT applications with increased business performance, IT, Information Systems (IS), and E-Business Model (EBM) research has increasingly looked to broader social and environmental factors as a means for examining and understanding the broader influences shaping IT, IS and E-Business (EB) adoption behaviour. Findings from these studies suggest that organisations adopt new technologies as a result of strong external pressures, rather than a clear measure of enhanced business value. In order to ascertain if this is the case with the adoption of SNSs, this study explores how organisations are creating value (and measuring that value) with the use of SNSs for business purposes, and the external pressures influencing their adoption. In doing so, it seeks to address two research questions: 1. What are the external pressures influencing organisations to adopt SNSs for business communication purposes? 2. Are SNSs providing increased business value for organisations, and if so, how is that value being captured and measured? Informed by the background literature fields of IT, IS, EBM, and Web 2.0, a three-tiered theoretical framework is developed that combines macro-societal, social and technological perspectives as possible causal mechanisms influencing the SNS adoption event. The macro societal view draws on the concept of Castells. (1996) network society and the behaviour of crowds, herds and swarms, to formulate a new explanatory concept of the network vortex. The social perspective draws on key components of institutional theory (DiMaggio & Powell, 1983, 1991), and the technical view draws from the organising vision concept developed by Swanson and Ramiller (1997). The study takes a critical realist approach, and conducts four stages of data collection and one stage of data coding and analysis. Stage 1 consisted of content analysis of websites and SNSs of many organisations, to identify the types of business purposes SNSs are being used for. Stage 2 also involved content analysis of organisational websites, in order to identify suitable sample organisations in which to conduct telephone interviews. Stage 3 consisted of conducting 18 in-depth, semi-structured telephone interviews within eight Australian organisations from the Media/Publishing and Galleries, Libraries, Archives and Museum (GLAM) industries. These sample organisations were considered leaders in the use of SNSs technologies. Stage 4 involved an SNS activity count of the organisations interviewed in Stage 3, in order to rate them as either Advanced Innovator (AI) organisations, or Learning Focussed (LF) organisations. A fifth stage of data coding and analysis of all four data collection stages was conducted, based on the theoretical framework developed for the study, and using QSR NVivo 8 software. The findings from this study reveal that SNSs have been adopted by organisations for the purpose of increasing business value, and as a result of strong social and macro-societal pressures. SNSs offer organisations a wide range of value enhancing opportunities that have broader benefits for customers and society. However, measuring the increased business value is difficult with traditional Return On Investment (ROI) mechanisms, ascertaining the need for new value capture and measurement rationales, to support the accountability of SNS adoption practices. The study also identified the presence of technical, social and macro-societal pressures, all of which influenced SNS adoption by organisations. These findings contribute important theoretical insight into the increased complexity of pressures influencing technology adoption rationales by organisations, and have important practical implications for practice, by reflecting the expanded global online networks in which organisations now operate. The limitations of the study include the small number of sample organisations in which interviews were conducted, its limited generalisability, and the small range of SNSs selected for the study. However, these were compensated in part by the expertise of the interviewees, and the global significance of the SNSs that were chosen. Future research could replicate the study to a larger sample from different industries, sectors and countries. It could also explore the life cycle of SNSs in a longitudinal study, and map how the technical, social and macro-societal pressures are emphasised through stages of the life cycle. The theoretical framework could also be applied to other social fad technology adoption studies.

ACE research vignette 003 : different strokes for different folks - classification of entrepreneurial musicians and their use of online social networks

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international entrepreneurship researchers. In this vignette Dr Maria Kaya and Associate Professor Paul Steffens consider both the classification of musicians and their use of online social networks.

Social network media and political activism: a growing challenge for law enforcement

The use of the internet for political purposes is not new; however, the introduction of social media tools has opened new avenues for political activists. In an era where social media has been credited as playing a critical role in the success of revolutions (Earl & Kimport, 2011; Papic & Noonan, 2011; Wooley, Limperos & 10 Beth, 2010), governments, law enforcement and intelligence agencies need to develop a deeper understanding of the broader capabilities of this emerging social and political environment. This can be achieved by increasing their online presence and through the application of proactive social media strategies to identify and manage potential threats. Analysis of current literature shows a gap 15 in the research regarding the connection between the theoretical understanding and practical implications of social media when exploited by political activists,and the efficacy of existing strategies designed to manage this growing challenge. This paper explores these issues by looking specifically at the use of three popular social media tools: Facebook; Twitter; and YouTube. Through the examination of 20 recent political protests in Iran, the UK and Egypt from 2009�2011, these case studies and research in the use of the three social media tools by political groups, the authors discuss inherent weaknesses in online political movements and discuss strategies for law enforcement and intelligence agencies to monitor these activities.

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.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.