Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Underlying beliefs influencing Vietnamese nurses and doctors in screening for victims of domestic violence: An exploratory study

Many health professionals in Vietnam have limited knowledge and experience in coordinating care for victims of Domestic Violence (DV). This qualitative study aimed to elicit the beliefs of nurses and doctors that are influencing the care of victims of DV. Data were collected by semistructured interviews with nineteen nurses and doctors. Data were analyzed by content analysis and organized by three main themes; behavioral beliefs, normative beliefs and control beliefs. The outcomes of this study will inform the development of intervention strategies that will enable health professionals to better respond to and manage care for women who experience domestic violence in Vietnam.

The value of respect in human research ethics: A conceptual analysis and a practical guide

In order to continue to maintain public trust and confidence in human research, participants must be treated with respect. Researchers and Human Research Ethics Committee members need to be aware that modern considerations of this value include: the need for a valid consenting process, the protection of participants who have their capacity for consent compromised; the promotion of dignity for participants; and the effects that human research may have on cultures and communities. This paper explains the prominence of respect as a value when considering the ethics of human research and provides practical advice for both researchers and Human Research Ethics Committee members in developing respectful research practices.

Outback institutions : an application of the Institutional Analysis and Development (IAD) framework to four case studies in Australia’s Outback -- Part 4 : Incentives for community participation and land use decisions in Etheridge Shire, Queensland

Natural resource management planning in the Northern Gulf region of Queensland is concerned with ‘how [natural assets] and community aspirations can be protected and enhanced to provide the Northern Gulf community with the economic, social and environmental means to meet the continuing growth of the region in an ecological and economically sustainable way’ (McDonald & Dawson 2004). In the Etheridge Shire, located in the tropical savanna of the Northern Gulf region, two of the activities that influence the balance between economic growth and long-term sustainable development are: 1. the land-use decisions people in the Shire make with regards to their own enterprises. 2. their decisions to engage in civically-minded activities aimed at improving conditions in the region. Land-use decision and engagement in community development activities were chosen for detailed analysis because they are activities for which policies can be devised to improve economic and sustainable development outcomes. Changing the formal and informal rules that guide and govern these two different kinds of decisions that people can make in the Etheridge Shire – the decision to improve one’s own situation and the decision to improve the situation for others in the community – may expand the set of available options for people in the Shire to achieve their goals and aspirations. Identifying appropriate and effective changes in rules requires, first, an understanding of the ‘action arena’, in this case comprised of a diversity of ‘participants’ from both within and outside the Etheridge Shire, and secondly knowledge of ‘action situations’ (land-use decisions and engagement in community development activities) in which stakeholders are involved and/or have a stake. These discussions are presented in sections 4.1.1.1 and 4.1.1.2.

Directing experience : an exploration of active analysis and visual cognition theory in the training of contemporary directors

The focus of this research is the creation of a stage-directing training manual on the researcher's site at the National Institute of Dramatic Art. The directing procedures build on the work of Stanislavski's Active Analysis and findings from present-day visual cognition studies. Action research methodology and evidence-based data collection are employed to improve the efficacy of both the directing procedures and the pedagogical manual. The manual serves as a supplement to director training and a toolkit for the more experienced practitioner. The manual and research findings provide a unique and innovative contribution to the field of theatre directing.

Analysis and modelling of the hydraulic conductivity in aquitards : application to the Galilee Basin and the Great Artesian Basin, Australia

In large sedimentary basins with layers of different rocks, the groundwater flow between aquifers depends on the hydraulic conductivity (K) of the separating low-permeable rocks, or aquitards. Three methods were developed to evaluate K in aquitards for areas with limited field data: • Coherence and harmonic analysis: estimates the regional-scale K based on water-level fluctuations in adjacent aquifers. • Cokriging and Bayes' rule: infers K from downhole geophysical logs. • Fluvial process model: reproduces the lithology architecture of sediment formations which can be converted to K. These proposed methods enable good estimates of K and better planning of further drillholes.

Improving the railway’s understanding of accident causation through an integrated approach to human factors analysis and technical safety data recording

This paper describes a safety data recording and analysis system that has been developed to capture safety occurrences including precursors using high-definition forward-facing video from train cabs and data from other train-borne systems. The paper describes the data processing model and how events detected through data analysis are related to an underlying socio-technical model of accident causation. The integrated approach to safety data recording and analysis insures systemic factors that condition, influence or potentially contribute to an occurrence are captured both for safety occurrences and precursor events, providing a rich tapestry of antecedent causal factors that can significantly improve learning around accident causation. This can ultimately provide benefit to railways through the development of targeted and more effective countermeasures, better risk models and more effective use and prioritization of safety funds. Level crossing occurrences are a key focus in this paper with data analysis scenarios describing causal factors around near-miss occurrences. The paper concludes with a discussion on how the system can also be applied to other types of railway safety occurrences.

The importance of good data, analysis and interpretation for showing the economics of reducing healthcare-associated infection

To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

Productive inefficiency analysis and toxic chemical substances in US and Japanese manufacturing sectors

Corporate social responsibility is imperative for manufacturing companies to achieve sustainable development. Under a strong environmental information disclosure system, polluting companies are disadvantaged in terms of market competitiveness, because they lack an environmentally friendly image. The objective of this study is to analyze productive inefficiency change in relation to toxic chemical substance emissions for the United States and Japan and their corresponding policies. We apply the weighted Russell directional distance model to measure companies productive inefficiency, which represents their production technology. The data encompass 330 US manufacturing firms observed from 1999 to 2007, and 466 Japanese manufacturing firms observed from 2001 to 2008. The article focuses on nine high-pollution industries (rubber and plastics; chemicals and allied products; paper and pulp; steel and non-ferrous metal; fabricated metal; industrial machinery; electrical products; transportation equipment; precision instruments) categorized into two industry groups: basic materials industries and processing and assembly industries. The results show that productive inefficiency decreased in all industrial sectors in the United States and Japan from 2001 to 2007. In particular, that of the electrical products industry decreased rapidly after 2002 for both countries, possibly because of the enforcement of strict environmental regulations for electrical products exported to European markets.

Insights into a multidrug resistant Escherichia coli pathogen of the globally disseminated ST131 lineage : genome analysis and virulence mechanisms

Escherichia coli strains causing urinary tract infection (UTI) are increasingly recognized as belonging to specific clones. E. coli clone O25b:H4-ST131 has recently emerged globally as a leading multi-drug resistant pathogen causing urinary tract and bloodstream infections in hospitals and the community. While most molecular studies to date examine the mechanisms conferring multi-drug resistance in E. coli ST131, relatively little is known about their virulence potential. Here we examined E. coli ST131 clinical isolates from two geographically diverse collections, one representing the major pathogenic lineages causing UTI across the United Kingdom and a second representing UTI isolates from patients presenting at two large hospitals in Australia. We determined a draft genome sequence for one representative isolate, E. coli EC958, which produced CTX-M-15 extended-spectrum β-lactamase, CMY-23 type AmpC cephalosporinase and was resistant to ciprofloxacin. Comparative genome analysis indicated that EC958 encodes virulence genes commonly associated with uropathogenic E. coli (UPEC). The genome sequence of EC958 revealed a transposon insertion in the fimB gene encoding the activator of type 1 fimbriae, an important UPEC bladder colonization factor. We identified the same fimB transposon insertion in 59% of the ST131 UK isolates, as well as 71% of ST131 isolates from Australia, suggesting this mutation is common among E. coli ST131 strains. Insertional inactivation of fimB resulted in a phenotype resembling a slower off-to-on switching for type 1 fimbriae. Type 1 fimbriae expression could still be induced in fimB-null isolates; this correlated strongly with adherence to and invasion of human bladder cells and bladder colonisation in a mouse UTI model. We conclude that E. coli ST131 is a geographically widespread, antibiotic resistant clone that has the capacity to produce numerous virulence factors associated with UTI.

Analysis of risk management disclosures by Australian publicly listed companies

In the aftermath of the global financial crisis, effective risk management (RM) and its communication to stakeholders are now considered essential components in corporate governance. However, despite the importance of RM communication, it is still unclear how and to what extent disclosures in financial reports can achieve effective communication of RM activities. The situation is hampered by the paucity of international RM Research that captures institution differences in corporate governance standards. The Australian setting provides an ideal environment in which to examine RM communication because the Australian Securities Exchange (ASX) has since 2007 recommended RM disclosures under its principle-based governance rules. The recommendations are contained in Principle 7 of the Corporate Governance Principles and recommendations (ASX CGPR). Accordingly, to assess the effectiveness of the AXS's RM governance principle, this study examines the nature and extent of RM disclosures reported by major ASX-listed firms. Using a mixed method approach (thematic content analysis and a series of regression analysis) we find widespread divergence in disclosure practices and low conformance with the Principle 7 recommendations. Certain corporate governance mechanisms appear to influence some categories of RM dislcosure but equity risk has surprisingly little explanatory power. These results suggest that the RM disclosures practices observed in the Australian setting may not be meeting the objectives of regulators and the needs of stakeholders.

Content creation and curation

Platforms for content created by web users have been associated with some of the most significant economic paradigm shifts in digital media. At the same time, user created content has often been at the center of heated scholarly debates around the democratization of media production, cultural participation, and public communication. In this entry, we provide an overview of such debates within media and communication research, particularly in relation to the evolution of mainstream platforms for content creation, curation, and sharing.

Confirmatory factor analysis and invariance testing of the Young Carer of Parents Inventory (YCOPI)

Objective Research into youth caregiving in families where a parent experiences a significant medical condition has been hampered by a lack of contextually sensitive measures of the nature and breadth of young caregiving experiences. This study examined the factor structure and measurement invariance of such a measure called the Young Carer of Parents Inventory (YCOPI; Pakenham et al., 2006) using confirmatory factor analysis across 3 groups of youth. The YCOPI has 2 parts: YCOPI-A with 5 factors assessing caregiving experiences that are applicable to all caregiving contexts; YCOPI-B with 4 factors that tap dimensions related to youth caregiving in the context of parent illness. Design Two samples (ages 9–20 years) were recruited: a community sample of 2,429 youth from which 2 groups were derived (“healthy” family [HF], n = 1760; parental illness [PI], n = 446), and a sample of 130 youth of a parent with multiple sclerosis). Results With some modification, the YCOPI-A demonstrated a replicable factor structure across 3 groups, and exhibited only partial measurement invariance across the HF and PI groups. The impact of assuming full measurement invariance on latent mean differences appeared small, supporting use of the measure in research and applied settings when estimated using latent factors and controlling for measurement invariance. PI youth reported significantly higher scores than did HF youth on all YCOPI-A subscales. The YCOPI-B requires some modifications, and further development work is recommended. Conclusion The factor structure that emerged and the addition of new items constitutes the YCOPI-Revised. Findings support the use of the YCOPI-Revised in research and applied settings.