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.

Video analytics for the detection of near-miss incidents on approach to railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.

#ausvotes Mark Two : Twitter in the 2013 Australian Federal Election

In this paper, we explore the use of Twitter as a political tool in the 2013 Australian Federal Election. We employ a ‘big data’ approach that combines qualitative and quantitative methods of analysis. By tracking the accounts of politicians and parties, and the tweeting activity to and around these accounts, as well as conversations on particular hashtagged topics, we gain a comprehensive insight into the ways in which Twitter is employed in the campaigning strategies of different parties. We compare and contrast the use of Twitter by political actors with its adoption by citizens as a tool for political conversation and participation. Our study provides an important longitudinal counterpoint, and opportunity for comparison, to the use of Twitter in previous Australian federal and state elections. Furthermore, we offer innovative methodologies for data gathering and evaluation that can contribute to the comparative study of the political uses of Twitter across diverse national media and political systems.

#Pontiff-Ex : the Twitter community’s reaction to the Papal resignation

In this paper, we provide an account-centric analysis of the tweeting activity of, and public response to, Pope Benedict XVI via the @pontifex Twitter account(s). We focus our investigation on the particular phase around Pope Benedict XVI’s resignation to generate insights into the use of Twitter in response to a celebrity crisis event. Through a combined qualitative and quantitative methodological approach we generate an overview of the follower-base and tweeting activity of the @pontifex account. We identify a very one-directional communication pattern (many @mentions by followers yet zero @replies from the papal account itself), which prompts us to enquire further into what the public resonance of the @pontifex account is. We also examine reactions to the resurrection of the papal Twitter account by Pope Benedict XVI’s successor. In this way, we provide a comprehensive analysis of the public response to the immediate events around the crisis event of Pope Benedict XVI’s resignation and its aftermath via the network of users involved in the @pontifex account.

Exploring emotions on #auspol : polarity, conservativism and public performance in the Twitter debate on Australian politics

The affective communication patterns of conversations on Twitter can provide insights into the culture of online communities. In this paper we apply a combined quantitative and qualitative approach to investigate the structural make-up and emotional content of tweeting activity around the hashtag #auspol (for Australian politics) in order to highlight the polarity and conservativism that characterise this highly active community of politically engaged individuals. We document the centralised structure of this particular community, which is based around a deeply committed core of contributors. Through in-depth content analysis of the tweets of participants to the online debate we explore the communicative tone, patterns of engagement and thematic drivers that shape the affective character of the community and their effect on its cohesiveness. In this way we provide a comprehensive account of the complex techno-social, linguistic and cultural factors involved in conversations that are shaped in the Twittersphere.

Friends or followers? The relations between German soccer clubs and their fans on Twitter

This paper shows how soccer clubs from Germany’s first division have started to use Twitter. Analysis is based on tweets from and to club accounts as well as on follower numbers, and specific clubs are selected for case studies. This approach reveals that Twitter mirrors the conflicts between professional sports and traditional fandom.

Polarized infrared absorption spectrum of matrix-isolated methylperoxyl radicals, CH3OO (X)over-tilde 2A ''

We have used a tandem pair of supersonic nozzles to produce clean samples of CH3OO radicals in cryogenic matrices. One hyperthermal nozzle decomposes azomethane (CH3NNCH3) to generate intense pulses of CH3 radicals, While the second nozzle alternately fires a burst Of O-2/Ar at the 20 K matrix. The CH3/O-2/20 K argon radical sandwich acts to produce target methylperoxyl radicals: CH3 + O-2 --> CH3OO. The absorption spectra of the radicals are monitored with a Fourier transform infrared spectrometer. We report 10 of the 12 fundamental infrared bands of the methylperoxyl radical CH3OO, (X) over tilde (2)A", in an argon matrix at 20 K. The experimental frequencies (cm(-1)) and polarizations follow: the a' modes are 3032, 2957, 1448, 1410, 1180, 1109, 90, 492, while the a" modes are 3024 and 1434. We cannot detect the asymmetric CH3 rocking mode, nu(11), nor the torsion, nu(12). The infrared spectra of (CH3OO)-O-18-O-18, (CH3OO)-C-13, and CD3OO have been measured as well in order to determine the isotopic shifts. The experimental frequencies, {nu}, for the methylperoxyl radicals are compared to harmonic frequencies, {omega}, resulting from a UB3LYP/6-311G(d,p) electronic structure calculation. Linear dichroism spectra were measured with photooriented radical samples in order to establish the experimental polarizations of most vibrational bands. The methylperoxyl radical matrix frequencies listed above are within +/-2% of the gas-phase vibrational frequencies. A final set of vibrational frequencies for the H radical, are recommended. See also http://ellison.colorado.edu/methylperoxyl.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Low-cost railway level crossings - breaking down the barriers

Level crossing risk continues to be a significant safety concern for the security of rail operations around the world. Over the last decade or so, a third of railway related fatalities occurred as a direct result of collisions between road and rail vehicles in Australia. Importantly, nearly half of these collisions occurred at railway level crossings with no active protection, such as flashing lights or boom barriers. Current practice is to upgrade level crossings that have no active protection. However, the total number of level crossings found across Australia exceed 23,500, and targeting the proportion of these that are considered high risk (e.g. public crossings with passive controls) would cost in excess of AU$3.25 billion based on equipment, installation and commissioning costs of warning devices that are currently type approved. Level crossing warning devices that are low-cost provide a potentially effective control for reducing risk; however, over the last decade, there have been significant barriers and legal issues in both Australia and the US that have foreshadowed their adoption. These devices are designed to have significantly lower lifecycle costs compared with traditional warning devices. They often make use of use of alternative technologies for train detection, wireless connectivity and solar energy supply. This paper describes the barriers that have been encountered for the adoption of these devices in Australia, including the challenges associated with: (1) determining requisite safety levels for such devices; (2) legal issues relating to duty of care obligations of railway operators; and (3) issues of Tort liability around the use of less than fail-safe equipment. This paper provides an overview of a comprehensive safety justification that was developed as part of a project funded by a collaborative rail research initiative established by the Australian government, and describes the conceptual framework and processes being used to justify its adoption. The paper provides a summary of key points from peer review and discusses prospective barriers that may need to be overcome for future adoption. A successful outcome from this process would result in the development of a guideline for decision-making, providing a precedence for adopting low-cost level crossing warning devices in other parts of the world. The framework described in this paper also provides relevance to the review and adoption of analogous technologies in rail and other safety critical industries.

Coping strategies used by ballet dancers : effects of individual differences in competitive trait anxiety

The world of classical ballet exerts considerable physical and psychological stress upon those who participate, and yet the process of coping with such stressors is not well understood. The purpose of the present investigation was to examine relationships between coping strategies and competitive trait anxiety among ballet dancers. Participants were 104 classical dancers (81 females and 23 males) ranging in age from 15 to 35 years (M = 19.4 yr., SD = 3.8 yr.) from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Participants had a mean of 11.5 years of classical dance training (SD = 5.2 yr.), having started dance training at 6.6 years of age (SD = 3.4 yr.). Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), a 48-item measure comprising 12 coping subscales (Seeking Social Support for Instrumental Reasons, Seeking Social Support for Emotional Reasons, Behavioral Disengagement, Planning, Suppression of Competing Activities, Venting of Emotions, Humor, Active Coping, Denial, Self-Blame, Effort, and Wishful Thinking). Competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990), a 21-item measure comprising three anxiety subscales (Somatic Anxiety, Worry, Concentration Disruption). Standard multiple regression analyses showed that trait anxiety scores, in particular for Somatic Anxiety and Worry, were significant predictors of seven of the 12 coping strategies (Suppression of Competing Activities: R2 = 27.1%; Venting of Emotions: R2 = 23.2%; Active Coping: R2 = 14.3%; Denial: R2 = 17.7%; Self-Blame: R2 = 35.7%; Effort: R2 = 16.6%; Wishful Thinking: R2 = 42.3%). High trait anxious dancers reported more frequent use of all categories of coping strategies. A separate two-way MANOVA showed no significant main effect for gender nor status (professional versus students) and no significant interaction effect. The present findings are generally consistent with previous research in the sport psychology domain (Crocker & Graham, 1995; Giacobbi & Weinberg, 2000) which has shown that high trait anxious athletes tend, in particular, to use more maladaptive, emotion-focused coping strategies when compared to low trait anxious athletes; a tendency which has been proposed to lead to negative performance effects. The present results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet. In particular, the results suggest that dancers who are, by nature, anxious about performance may need special attention to help them to learn to cope with performance-related stress. Given the absence of differences in coping strategies between student and professional dancers and between males and females, it appears that such educational efforts should begin at an early career stage for all dancers.

Learning about and taking action for the environment : child and teacher experiences in a preschool water education program

Water education and conservation programs have grown exponentially in Australian primary and secondary schools and, although early childhood services have been slower to respond to the challenges of sustainability, they are catching up fast. One early program targeted at preschools was the Water Aware Centre Program in northern New South Wales developed by the local water supply authority. This paper reports on a qualitative study of children’s and teachers’ experiences of the program in three preschools. The study’s aim was to identify program attributes and pedagogies that supported learning and action taking for water conservation, and to investigate if and how the program influenced children’s and teachers’practices. Data were collected through an interview with the program designer, conversations with child participants of the program, and a qualitative survey with early childhood staff. A three-step thematic analysis was conducted on the children’s and teachers’ data. Findings revealed that the program expanded children and teachers’ ideas about water conservation and increased their water conservation practices. The children were found to influence the water conservation practices of the adults around them, thus changing practices at school and at home.

The Sawa World model : addressing extreme poverty through local solutions and youth empowerment

With an estimated 1.2 billion people worldwide living in extreme poverty, it is critical to find effective long-term solutions. Sawa World is a non-profit organization founded by Daphne Nederhorst in 2005 to empower marginalized youth to document simple, locally created solutions that address this pressing issue. Currently working primarily in Uganda, Sawa World has created a unique model that celebrates powerful solutions generated from within the community to help people living in poverty help themselves. Using inspiring local leaders who themselves come from extreme poverty, Sawa World aims to end extreme poverty from the ground up.

Design for Kids

Exley, Sharon and Exley, Peter (2007). The Images Publishing Group Pty Ltd.; 275 pages. $60. ISBN 1864701803.

Enriques' Journey: The Story of a Boy's Dangerous Odyssey to Reunite with his Mother

Nazario, Sonia (2006). New York: Random House, Inc.; 294 pages. $26.95. ISBN 1400062055.