Metrics for Understanding Communication on Twitter

As the systematic investigation of Twitter as a communications platform continues, the question of developing reliable comparative metrics for the evaluation of public, communicative phenomena on Twitter becomes paramount. What is necessary here is the establishment of an accepted standard for the quantitative description of user activities on Twitter. This needs to be flexible enough in order to be applied to a wide range of communicative situations, such as the evaluation of individual users’ and groups of users’ Twitter communication strategies, the examination of communicative patterns within hashtags and other identifiable ad hoc publics on Twitter (Bruns & Burgess, 2011), and even the analysis of very large datasets of everyday interactions on the platform. By providing a framework for quantitative analysis on Twitter communication, researchers in different areas (e.g., communication studies, sociology, information systems) are enabled to adapt methodological approaches and to conduct analyses on their own. Besides general findings about communication structure on Twitter, large amounts of data might be used to better understand issues or events retrospectively, detect issues or events in an early stage, or even to predict certain real-world developments (e.g., election results; cf. Tumasjan, Sprenger, Sandner, & Welpe, 2010, for an early attempt to do so).

Crisis Communication in Natural Disasters : The Queensland Floods and Christchurch Earthquakes

Over the past decade, social media have gone through a process of legitimation and official adoption, and they are now becoming embedded as part of the official communications apparatus of many commercial and public-sector organisations— in turn, providing platforms like Twitter with their own sources of legitimacy. Arguably, the demonstrated utility of social media platforms and tools in times of crisis—from civil unrest and violent crime through to natural disasters like bushfires, earthquakes, and floods—has been a crucial driver of this newfound legitimacy. In the mid-2000s, user-created content and ‘Web 2.0’ platforms were known to play a role in crisis communication; back then, the involvement of extra-institutional actors in providing and sharing information around such events involved distributed, ad hoc, or niche platforms (like Flickr), and was more likely to be framed as ‘citizen journalism’ or ‘crowdsourcing’ (see, for example, Liu, Palen, Sutton, Hughes, & Vieweg, 2008, on the then-emerging role of photo-sharing in disasters). Since then, the dramatically increased take-up of mainstream social media platforms like Facebook and Twitter means that the pool of potential participants in online crisis communication has broadened to include a much larger proportion of the general population, as well as traditional media and official emergency response organisations.

From Prosumption to Produsage

Almost a decade after the 2004 O’Reilly Media conference which popularized the term ‘Web 2.0’, the impact of this concept on users and developers of the current generation of Web technology – and by extension, on the digital economy overall – is undeniable. At the time, ‘Web 2.0’ promised an interactive, engaging online space in which users were able to do more than surf from static, fixed Website to static, fixed Website. Although the implicit suggestion that the version change to ‘Web 2.0’ represented a clean break with this inflexible past must be read as mere marketing hype, the core principles which the concept outlined nonetheless form the operational basis for most mainstream Websites of the present day.

A survey of user modelling in social media websites

With the widespread of social media websites in the internet, and the huge number of users participating and generating infinite number of contents in these websites, the need for personalisation increases dramatically to become a necessity. One of the major issues in personalisation is building users’ profiles, which depend on many elements; such as the used data, the application domain they aim to serve, the representation method and the construction methodology. Recently, this area of research has been a focus for many researchers, and hence, the proposed methods are increasing very quickly. This survey aims to discuss the available user modelling techniques for social media websites, and to highlight the weakness and strength of these methods and to provide a vision for future work in user modelling in social media websites.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Humanities and social scientific research methods in porn studies

Porn studies researchers in the humanities have tended to use different research methods from those in social sciences. There has been surprisingly little conversation between the groups about methodology. This article presents a basic introduction to textual analysis and statistical analysis, aiming to provide for all porn studies researchers a familiarity with these two quite distinct traditions of data analysis. Comparing these two approaches, the article suggests that social science approaches are often strongly reliable – but can sacrifice validity to this end. Textual analysis is much less reliable, but has the capacity to be strongly valid. Statistical methods tend to produce a picture of human beings as groups, in terms of what they have in common, whereas humanities approaches often seek out uniqueness. Social science approaches have asked a more limited range of questions than have the humanities. The article ends with a call to mix up the kinds of research methods that are applied to various objects of study.

Exploring schema-driven differences in situation awareness between road users : an on-road study of driver, cyclist and motorcyclist situation awareness

Collisions between different road users make a substantial contribution to road trauma. Although evidence suggests that different road users interpret the same road situations differently, it is not clear how road users' situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study conducted to examine driver, motorcyclist and cyclist situation awareness in different road environments. The findings suggest that, in addition to minor differences in the structure of different road users' situation awareness (i.e. amount of information and how it is integrated), the actual content of situation awareness in terms of road user schemata, the resulting interaction with the world and the information underpinning situation awareness is markedly different. Further examination indicates that the differences are likely to be compatible along arterial roads, shopping strips and at roundabouts, but that they may create conflicts between different road users at intersections. Interventions designed to support compatible situation awareness and behaviour between different road users are discussed. Practitioner Summary: Incompatible situation awareness plays a key role in collisions between different road users (e.g. drivers and motorcyclists). This on-road study examined situation awareness in drivers, motorcyclists and cyclists, identifying the key differences and potential conflicts that arise. The findings are used to propose interventions designed to enhance the compatibility of situation awareness between road users.

Broadcasting digital stories on Australian community television : the Digistories Anthology

Community-based arts and media movements have been intsrumental in building population-wide creative capacity for cultural development, social participation and social transformation in many parts of the world. Digital storytelling is a form of media practice that was pioneered in the United States at the intersection of these movements. It is described here as a ‘co-creative’ media production method. This description aims to differentiate the approaches to collaborative content creation that are used in community cultural development (CCD) and community media movements from those valued in professional and consumer modes of media production. Yet, the products of co-creative practices, such as digital stories, do not circulate widely through existing media networks or through the newer social media networks that Australian CCD and community media movements anticipated by at least twenty years. The complex politics of story ownership are one of a number of factors that often render ‘publication’ a secondary consideration in the making of digital stories. The possibility of ‘downstream’ use and re-use of stories in other networks is not usually considered in initial planning and development processes. As landmark projects such as Capture Wales indicate, even where stories are made for broadcast outcomes, television can be a problematic window for exhibiting digital stories. Scepticism about the brave new world of reality television and user generated content also circulates in digital storytelling networks, especially when it comes to ethical concerns for managing the risks of harm associated with widespread distribution of digital stories to indiscriminate publics. This publication reports on a collaborative action research project that took a closer look at some of the constraints relating to the problems of re-purposing digital stories for television. It focussed on ‘best practice’ for managing the risks of harm to storytellers in the process of re-purposing digital stories for broadcast on community television.

How accurate is the identification of serious traffic injuries by Police? The concordance between Police and hospital reported traffic injuries

Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

Cinema studies : Women's Experimental Cinema edited by Robin Blaetz

Women’s Experimental Cinema provides lively introductions to the work of fifteen avant-garde women filmmakers, some of whom worked as early as the 1950s and many of whom are still working today. In each essay in this collection, a leading film scholar considers a single filmmaker, supplying biographical information, analyzing various influences on her work, examining the development of her corpus, and interpreting a significant number of individual films. The essays rescue the work of critically neglected but influential women filmmakers for teaching, further study, and, hopefully, restoration and preservation. Just as importantly, they enrich the understanding of feminism in cinema and expand the terrain of film history, particularly the history of the American avant-garde.

Gender studies : Intersex by Catherine Harper

Intersex is the condition whereby an individual is born with biological features that are simultaneously perceived as male and female. Ranging from the ambiguous genitalia of the true 'hermaphrodite' to the 'mildly or internally intersexed', the condition may be as common as cleft palate. Like cleft palate, it is hidden and surgically altered, but for very different reasons. Intersex draws heavily on the personal testimony of intersexed individuals, their loved ones and medical carers. The impact of early sex-assignment surgery on an individual's later life is examined within the context of ethical and clinical questions. Harper challenges the conventional and radical 'treatment' of intersexuality through non-consensual infant sex-assignment surgery. In doing so, she exposes powerful myths, taboos and constructions of gender - the perfect phallus, a bi-polar model of gender and the infallibility of medical decisions. Handling sensitive material with care, this book deepens our understanding of a condition that has itself only been medically understood in recent years.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

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.