Privacy by design for social networks

This research has established a new privacy framework, privacy model, and privacy architecture to create more transparent privacy for social networking users. The architecture is designed into three levels: Business, Data, and Technology, which is based on The Open Group Architecture Framework (TOGAF®). This framework and architecture provides a novel platform for investigating privacy in Social Networks (SNs). This approach mitigates many current SN privacy issues, and leads to a more controlled form of privacy assessment. Ultimately, more privacy will encourage more connections between people across SN services.

Knowledge ecosystems of early career academics : a grounded theory of experiencing information use for learning in developmental networks

This study explored early career academics' experiences in using information to learn while building their networks for professional development. A 'knowledge ecosystem' model was developed consisting of informal learning interactions such as relating to information to create knowledge and engaging in mutually supportive relationships. Findings from this study present an alternative interpretation of information use for learning that is focused on processes manifesting as human interactions with informing entities revolving around the contexts of reciprocal human relationships.

The Arab Spring and its social media audiences : English and Arabic Twitter users and their networks

2011 ‘Arab Spring’ are likely to overstate the impact of Facebook and Twitter on these uprisings, it is nonetheless true that protests and unrest in countries from Tunisia to Syria generated a substantial amount of social media activity. On Twitter alone, several millions of tweets containing the hashtags #libya or #egypt were generated during 2011, both by directly affected citizens of these countries, and by onlookers from further afield. What remains unclear, though, is the extent to which there was any direct interaction between these two groups (especially considering potential language barriers between them). Building on hashtag datasets gathered between January and November 2011, this paper compares patterns of Twitter usage during the popular revolution in Egypt and the civil war in Libya. Using custom-made tools for processing ‘big data’, we examine the volume of tweets sent by English-, Arabic-, and mixed-language Twitter users over time, and examine the networks of interaction (variously through @replying, retweeting, or both) between these groups as they developed and shifted over the course of these uprisings. Examining @reply and retweet traffic, we identify general patterns of information flow between the English- and Arabic-speaking sides of the Twittersphere, and highlight the roles played by users bridging both language spheres.

Professional development and social networks in digital content industry micro businesses

This study explores the professional development strategies of digital content professionals in Australian micro businesses. This thesis presents the argument that as these professionals are working in cutting edge creative fields where digital technology drives ongoing change, formal education experiences may be less important than for other professionals, and that specific types of online and face-to-face socially mediated informal learning strategies may be critical to currency. This thesis documents the findings of a broad survey of industry professionals' learning needs and development strategies, in conjunction with rich data from in-depth interviews and social network analyses.

Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

Mechanics of microfilaments networks : a cross-scales study

The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

The role and future challenges of wireless communication networks for cooperative autonomous city vehicles

This paper elaborates on the use of future wireless communication networks for autonomous city vehicles. After addressing the state of technology, the paper explains the autonomous vehicle control system architecture and the Cybercars-2 communication framework; it presents experimental tests of communication-based real-time decision making; and discusses potential applications for communication in order to improve the localization and perception abilities of autonomous vehicles in urban environments.

Nowhere to hide: informal disease surveillance networks tracing state behaviour

Since the revisions to the International Health Regulations (IHR) in 2005, much attention has turned to how states, particularly developing states, will address core capacity requirements attached to the revised IHR. Primarily, how will states strengthen their capacity to identify and verify public health emergencies of international concern (PHEIC)? Another important but under-examined aspect of the revised IHR is the empowerment of the World Health Organization (WHO) to act upon non-governmental reports of disease outbreaks. The revised IHR potentially marks a new chapter in the powers of ‘disease intelligence’ and how the WHO may press states to verify an outbreak event. This article seeks to understand whether internet surveillance response programs (ISRPs) are effective in ‘naming and shaming’ states into reporting disease outbreaks.

Applying Enterprise Architecture to Business Networks

Globalization, financial deregulation, economic turmoil, and technology breakthroughs are profoundly exposing organizations to business networks. Engaging these networks requires explicit planning from the strategic level down to the operational level of an organization, which significantly affects organizational artefacts such as business services, processes, and resources. Although enterprise architecture (EA) aligns business and IT aspects of organizational systems, previous applications of EA have not comprehensively addressed a methodological framework for planning. In the context of business networks, this study seeks to explore the application of EA for business network planning where it builds upon relevant and well-established prescriptive and descriptive aspects of EA. Prescriptive aspects include integrated models of services, business processes, and resources among other organizational artefacts, at both business and IT levels. Descriptive aspects include ontological classifications of business functionality, which allow EA models to be aligned semantically to organizational artefacts and, ultimately higher-level business strategy. A prominent approach for capturing descriptive aspects of EA is business capability modelling. In order to explore and develop the illustrative extensions of EA through capability modelling, a list of requirements (capability dimensions) for business network planning will be identified and validated through a revelatory case study encompassing different business network manifestations, or situations. These include virtual organization, liquid workforce, business network orchestration, and headquarters-subsidiary. The use of artefacts, conventionally, modelled through EA will be considered in these network situations. Two general considerations for EA extensions are explored for the identified requirements at the level of the network: extension of artefacts through the network and alignment of network level artefacts with individual organization artefacts. The list of requirements provides the basis for a constructivist extension of EA in the following ways. Firstly, for descriptive aspects, it offers constructivist insights to guide extensions for particular EA techniques and concepts. Secondly, for prescriptive aspects it defines a set of capability dimensions, which improve the analysis and assessment of organization capabilities for business network situations.

Audiencing through social media : a brief overview

Notwithstanding the problems with identifying audiences (c.f. Hartley, 1987), nor with sampling them (c.f. Turner, 2005), we contend that by using social media, it is at least possible to gain an understanding of the habits of those who chose to engage with content through social media. In this chapter, we will broadly outline the ways in which networks such as Twitter and Facebook can stand as proxies for audiences in a number of scenarios, and enable content creators, networks and researchers to understand the ways in which audiences come into existence, change over time, and engage with content. Beginning with the classic audience – television – we will consider the evolution of metrics from baseline volume metrics to the more sophisticated ‘telemetrics’ that are the focus of our current work. We discuss the evolution of these metrics, from principles developed in the field of ‘sabermetrics’, and highlight their effectiveness as both a predictor and a baseline for producers and networks to measure the success of their social media campaigns. Moving beyond the evaluation of the audiences engagement, we then move to consider the ‘audiences’ themselves. Building on Hartley’s argument that audiences are “imagined” constructs (1987, p. 125), we demonstrate the continual shift of Australian television audiences, from episode to episode and series to series, demonstrating through our map of the Australian Twittersphere (Bruns, Burgess & Highfield, 2014) both the variation amongst those who directly engage with television content, and those who are exposed to it through their social media networks. Finally, by exploring overlaps between sporting events (such as the NRL and AFL Grand Finals), reality TV (such as Big Brother, My Kitchen Rules & Biggest Loser), soaps (e.g. Bold & The Beautiful, Home & Away), and current affairs programming (e.g. Morning Television & A Current Affair), we discuss to what extent it is possible to profile and categorize Australian television audiences. Finally, we move beyond television audiences to consider audiences around social media platforms themselves. Building on our map of the Australian Twittersphere (Bruns, Burgess & Highfield, 2014), and a pool of 5000 active Australian accounts, we discuss the interconnectedness of audiences around particular subjects, and how specific topics spread throughout the Twitter Userbase. Also, by using Twitter as a proxy, we consider the career of a number of popular YouTuber’s, utilizing a method we refer to as Twitter Accession charts (Bruns & Woodford, 2014) to identify the growth curves, and relate them to specific events in the YouTubers career, be that ‘viral’ videos or collaborations, to discuss how audiences form around specific content creators.

Everyone’s watching it : the role of hype in television engagement through social media

Social media is playing an ever-increasing role in both viewers engagement with television and in the television industries evaluation of programming, in Australia – which is the focus of our study - and beyond. Twitter hashtags and viewer comments are increasingly incorporated into broadcasts, while Facebook fan pages provide a means of marketing upcoming shows and television personalities directly into the social media feed of millions of users. Additionally, bespoke applications such as FanGo and ZeeBox, which interact with the mainstream social networks, are increasingly being utilized by broadcasters for interactive elements of programming (c.f. Harrington, Highfield and Bruns, 2012). However, both the academic and industry study of these platforms has focused on the measure of content during the specific broadcast of the show, or a period surrounding it (e.g. 3 hours before until 3 am the next day, in the case of 2013 Nielsen SocialGuide reports). In this paper, we argue that this focus ignores a significant period for both television producers and advertisers; the lead-up to the program. If, as we argue elsewhere (Bruns, Woodford, Highfield & Prowd, forthcoming), users are persuaded to engage with content both by advertising of the Twitter hash-tag or Facebook page and by observing their network connections engaging with such content, the period before and between shows may have a significant impact on a viewers likelihood to watch a show. The significance of this period for broadcasters is clearly highlighted by the efforts they afford to advertising forthcoming shows through several channels, including television and social media, but also more widely. Biltereyst (2004, p.123) has argued that reality television generates controversy to receive media attention, and our previous small-scale work on reality shows during 2013 and 2014 supports the theory that promoting controversial behavior is likely to lead to increased viewing (Woodford & Prowd, 2014a). It remains unclear, however, to what extent this applies to other television genres. Similarly, while networks use of social media has been increasing, best practices remain unclear. Thus, by applying our telemetrics, that is social media metrics for television based on sabermetric approaches (Woodford, Prowd & Bruns, forthcoming; c.f. Woodford & Prowd, 2014b), to the period between shows, we are able to better understand the period when key viewing decisions may be made, to establish the significance of observing discussions within your network during the period between shows, and identify best practice examples of promoting a show using social media.

Large networks of vertical multi-layer graphenes with morphology-tunable magnetoresistance

We report on the comparative study of magnetotransport properties of large-area vertical few-layer graphene networks with different morphologies, measured in a strong (up to 10 T) magnetic field over a wide temperature range. The petal-like and tree-like graphene networks grown by a plasma enhanced CVD process on a thin (500 nm) silicon oxide layer supported by a silicon wafer demonstrate a significant difference in the resistance-magnetic field dependencies at temperatures ranging from 2 to 200 K. This behaviour is explained in terms of the effect of electron scattering at ultra-long reactive edges and ultra-dense boundaries of the graphene nanowalls. Our results pave a way towards three-dimensional vertical graphene-based magnetoelectronic nanodevices with morphology-tuneable anisotropic magnetic properties. © The Royal Society of Chemistry 2013.

Deterministic control of structural and optical properties of plasma-grown vertical graphene nanosheet networks via nitrogen gas variation

The effect of nitrogen on the growth of vertically oriented graphene nanosheets on catalyst-free silicon and glass substrates in a plasma-assisted process is studied. Different concentrations of nitrogen were found to act as versatile control knobs that could be used to tailor the length, number density and structural properties of the nanosheets. Nanosheets with different structural characteristics exhibit markedly different optical properties. The nanosheet samples were treated with a bovine serum albumin protein solution to investigate the effects of this variation on the optical properties for biosensing through confocal micro-Raman spectroscopy and UV-Vis spectrophotometry. © 2012 Optical Society of America.