Exploring the Pro-Am interface between production and produsage

This conference celebrates the passing of 40 years since the establishment of the Internet (dating this, presumably, to the first connection between two nodes on ARPANET in October 1969). For a gathering of media scholars such as this, however, it may be just as important not only to mark the first testing of the core technologies upon which much of our present-day Net continues to build, but also to reflect on another recent milestone: the 20th anniversary of what is today arguably the chief interface through which billions around the world access and experience the Internet – the World Wide Web, launched by Tim Berners-Lee in 1989.

Quantitative approaches to comparing communication patterns on Twitter

To date, the available literature mainly discusses Twitter activity patterns in the context of individual case studies, while comparative research on a large number of communicative events and their dynamics and patterns is missing. By conducting a comparative study of more than 40 different cases (covering topics such as elections, natural disasters, corporate crises, and televised events) we identify a number of distinct types of discussion that can be observed on Twitter. Drawing on a range of communicative metrics, we show that thematic and contextual factors influence the usage of different communicative tools available to Twitter users, such as original tweets, @replies, retweets, and URLs. Based on this first analysis of the overall metrics of Twitter discussions, we also demonstrate stable patterns in the use of Twitter in the context of major topics and events.

Diversification for sustainable development in rural and regional Australia : how local community leaders conceptualise the impacts and opportunities from agriculture, tourism and mining

Although the multiple economic, environmental and social challenges threatening the viability of rural and regional communities in Australia are well-known, little research has explored how community leaders conceptualise the impact and opportunities associated with economic diversification from agriculture into alternative industries, such as tourism and mining. This qualitative research, utilising the Darling Downs in Queensland as a case study, documents how 28 local community leaders have experienced this economic diversification process. The findings reveal that local community leaders have a deep understanding about the opportunities and challenges presented by diversification, articulating a clear vision about how to achieve the best possible future for their region. Despite excitement about growth, there were concerns about preserving heritage, the increased pressure on local infrastructure and an ageing population. By documenting local leader’s insights, these findings may help inform planning for rural and regional communities and facilitate management of the exciting yet challenging process of growth and diversification

Characterization of sky-region morphological-temporal airborne collision detection

Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

Ambulance use is associated with higher self-rated illness seriousness : user attitudes and perceptions

Objectives The objective was to study the role and effect of patients' perceptions on reasons for using ambulance services in Queensland, Australia. Methods A cross-sectional survey was conducted of patients (n = 911) presenting via ambulance or self-transport at eight public hospital emergency departments (EDs). The survey included perceived illness severity, attitudes toward ambulance, and reasons for using ambulance. A theoretical framework was developed to inform this study. Results Ambulance users had significantly higher self-rated perceived seriousness, urgency, and pain than self-transports. They were also more likely to agree that ambulance services are for everyone to use, regardless of the severity of their conditions. In compared to self-transports, likelihood of using an ambulance increased by 26% for every unit increase in perceived seriousness; and patients who had not used an ambulance in the 6 months prior to the survey were 66% less likely to arrive by ambulance. Patients who had presented via ambulance stated they considered the urgency (87%) or severity (84%) of their conditions as reasons for calling the ambulance. Other reasons included requiring special care (76%), getting higher priority at the ED (34%), not having a car (34%), and financial concerns (17%). Conclusions Understanding patients' perceptions is essential in explaining their actions and developing safe and effective health promotion programs. Individuals use ambulances for various reasons and justifications according to their beliefs, attitudes, and sociodemographic conditions. Policies to reduce and manage demand for such services need to address both general opinions and specific attitudes toward emergency health services to be effective.

Notes towards the scientific study of public communication on Twitter

Twitter is now well-established as an important platform for real-time public communication. Twitter research continues to lag behind these developments, with many studies remaining focused on individual case studies and utilizing home-grown, idiosyncratic, non-repeatable, and non-verifiable research methodologies. While the development of a full-blown “science of Twitter” may remain illusory, it is nonetheless necessary to move beyond such individual scholarship and toward the development of more comprehensive, transferable, and rigorous tools and methods for the study of Twitter on a large scale and in close to real time.

Learning personalized tag ontology from user tagging information

The cross-sections of the Social Web and the Semantic Web has put folksonomy in the spot light for its potential in overcoming knowledge acquisition bottleneck and providing insight for "wisdom of the crowds". Folksonomy which comes as the results of collaborative tagging activities has provided insight into user's understanding about Web resources which might be useful for searching and organizing purposes. However, collaborative tagging vocabulary poses some challenges since tags are freely chosen by users and may exhibit synonymy and polysemy problem. In order to overcome these challenges and boost the potential of folksonomy as emergence semantics we propose to consolidate the diverse vocabulary into a consolidated entities and concepts. We propose to extract a tag ontology by ontology learning process to represent the semantics of a tagging community. This paper presents a novel approach to learn the ontology based on the widely used lexical database WordNet. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. We provide empirical evaluations by using the semantic information contained in the ontology in a tag recommendation experiment. The results show that by using the semantic relationships on the ontology the accuracy of the tag recommender has been improved.

Personalization in tag ontology learning for recommendation making

Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.

Towards distributed citizen participation : lessons from WikiLeaks and the Queensland floods

This paper examines the rapid and ad hoc development and interactions of participative citizen communities during acute events, using the examples of the 2011 floods in Queensland, Australia, and the global controversy surrounding Wikileaks and its spokesman, Julian Assange. The self-organising community responses to such events which can be observed in these cases bypass or leapfrog, at least temporarily, most organisational or administrative hurdles which may otherwise frustrate the establishment of online communities; they fast-track the processes of community development and structuration. By understanding them as a form of rapid prototyping, e-democracy initiatives can draw important lessons from observing the community activities around such acute events.

Twitter as a technology for audiencing and fandom : the #Eurovision phenomenon

Amongst the most prominent uses of Twitter at present is its role in the discussion of widely televised events: Twitter’s own statistics for 2011, for example, list major entertainment spectacles (the MTV Music Awards, the BET Awards) and sports matches (the UEFA Champions League final, the FIFA Women’s World Cup final) amongst the events generating the most tweets per second during the year (Twitter, 2011). User activities during such televised events constitute a specific, unique category of Twitter use, which differs clearly from the other major events which generate a high rate of tweets per second (such as crises and breaking news, from the Japanese earthquake and tsunami to the death of Steve Jobs), as preliminary research has shown. During such major media events, by contrast, Twitter is used most predominantly as a technology of fandom instead: it serves in the first place as a backchannel to television and other streaming audiovisual media, enabling users offer their own running commentary on the universally shared media text of the event broadcast as it unfolds live. Centrally, this communion of fans around the shared text is facilitated by the use of Twitter hashtags – unifying textual markers which are now often promoted to prospective audiences by the broadcasters well in advance of the live event itself. This paper examines the use of Twitter as a technology for the expression of shared fandom in the context of a major, internationally televised annual media event: the Eurovision Song Contest. It constitutes a highly publicised, highly choreographed media spectacle whose eventual outcomes are unknown ahead of time and attracts a diverse international audience. Our analysis draws on comprehensive datasets for the ‘official’ event hashtags, #eurovision, #esc, and #sbseurovision. Using innovative methods which combine qualitative and quantitative approaches to the analysis of Twitter datasets containing several hundreds of thousands, we examine overall patterns of participation to discover how audiences express their fandom throughout the event. Minute-by-minute tracking of Twitter activity during the live broadcasts enables us to identify the most resonant moments during each event; we also examine the networks of interaction between participants to detect thematically or geographically determined clusters of interaction, and to identify the most visible and influential participants in each network. Such analysis is able to provide a unique insight into the use of Twitter as a technology for fandom and for what in cultural studies research is called ‘audiencing’: the public performance of belonging to the distributed audience for a shared media event. Our work thus contributes to the examination of fandom practices led by Henry Jenkins (2006) and other scholars, and points to Twitter as an important new medium facilitating the connection and communion of such fans.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.