Showing papers by "Nigel Shadbolt published in 2013"

Towards a classification framework for social machines

Abstract: The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as "social machines" exploit the large-scale interaction of humans with machines. Interactions that are motivated by numerous goals and purposes including financial gain, charitable aid, and simply for fun. In this paper we explore the landscape of social machines, both past and present, with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation. We present an initial characterisation of some of the most popular social machines, as demonstration of the use of the identified constructs. We believe that it is important to undertake an analysis of the behaviour and phenomenology of social machines, and of their growth and evolution over time. Our future work will seek to elicit additional opinions, classifications and validation from a wider audience, to produce a comprehensive framework for the description, analysis and comparison of social machines.

Trust among cybercriminals? Carding forums, uncertainty and implications for policing

Abstract: At the beginning of the twenty-first century, before the power of online social networking became apparent, several studies speculated about the likely structure of organised cybercrime. In the light of new data on cybercriminal organisations, this paper sets out to revisit their claims. This paper examines the structure of organised cybercrime by analysing data from online underground markets previously in operation over the Internet. In order to understand the various structures of organised cybercrime which have manifested, theories are drawn from social psychology, organised crime and transaction cost economics (TCE). Since the focus is on how uncertainty is mitigated in trading among cybercriminals, uncertainty is treated as a cost to the transactions and is used as the unit of analysis to examine the mechanisms cybercriminals use to control two key sources of uncertainty: the quality of merchandise and the identity of the trader. The findings indicate that carding forums facilitate organised cybercr...

The Web Science Observatory

Abstract: To understand and enable the evolution of the Web and to help address grand societal challenges, the Web must be observable at scale across space and time. That requires a globally distributed and collaborative Web Observatory.

Why forums?: an empirical analysis into the facilitating factors of carding forums

Abstract: Over the last decade, the nature of cybercrime has transformed from naive vandalism to profit-driven, leading to the emergence of a global underground economy. A noticeable trend which has surfaced in this economy is the repeated use of forums to operate online stolen data markets. Using interaction data from three prominent carding forums: Shadowcrew, Cardersmarket and Darkmarket, this study sets out to understand why forums are repeatedly chosen to operate online stolen data markets despite numerous successful infiltrations by law enforcement in the past. Drawing on theories from criminology, social psychology, economics and network science, this study has identified four fundamental socio-economic mechanisms offered by carding forums: (1) formal control and coordination; (2) social networking; (3) identity uncertainty mitigation; (4) quality uncertainty mitigation. Together, they give rise to a sophisticated underground market regulatory system that facilitates underground trading over the Internet and thus drives the expansion of the underground economy.

Linked Data in Government

Abstract: Government data is powerful, plentiful, and relevant to citizens' concerns. Making it open supports transparency, crowdsourcing data enhancement, and innovative service development. The authors review the state of linked open government data, in the context of the potential for the publishing organizations and the Linked Data Web itself, as well as the administrative and political issues raised.

Knowledge acquisition and the rise of social machines

Abstract: In this issue Brian Gaines (Gaines, 2012) provides a magisterial review of the origins of human kind and human knowledge. It is a reminder that in spite of all our technology it takes a very special type of scholarship to weave such a compelling narrative over such a monumental range of time and material. This article takes a number of strands of Gaines' arguments and presents them in the context of my own, colleagues and the field's research trajectory.

Web science: A new frontier

Abstract: During the past 20 years, humans have built the largest information fabric in history The World Wide Web has been transformational People shop, date, trade and communicate with one another using it Although most people are not formally trained in its use, yet it has assumed a central role in

"the crowd keeps me in shape": social psychology and the present and future of health social machines

Abstract: Can the Web help people live healthier lives? This paper seeks to answer this question through an examination of sites, apps and online communities designed to help people improve their fitness, better manage their disease(s) and conditions, and to solve the often elusive connections between the symptoms they experience, diseases and treatments. These health social machines employ a combination of both simple and complex social and computational processes to provide such support. We first provide a descriptive classification of the kinds of machines currently available, and the support each class offers. We then describe the limitations exhibited by these systems and potential ways around them, towards the design of more effective machines in the future.

Carpé data: supporting serendipitous data integration in personal information management

Abstract: The information processing capabilities of humans enable them to opportunistically draw and integrate knowledge from nearly any information source. However, the integration of digital, structured data from diverse sources remains difficult, due to problems of heterogeneity that arise when data modelled separately are brought together. In this paper, we present an investigation of the feasibility of extending Personal Information Management (PIM) tools to support lightweight, user-driven mixing of previously un-integrated data, with the objective of allowing users to take advantage of the emerging ecosystems of structured data currently becoming available. In this study, we conducted an exploratory, sequential, mixed-method investigation, starting with two pre-studies of the data integration needs and challenges, respectively, of Web-based data sources. Observations from these pre-studies led to DataPalette, an interface that introduced simple co-reference and group multi-path-selection mechanisms for working with terminologically and structurally heterogeneous data. Our lab study showed that participants readily understood the new interaction mechanisms which were introduced. Participants made more carefully justified decisions, even while weighing a greater number of factors, moreover expending less effort, during subjective-choice tasks when using DataPalette, than with a control set-up.

Midata: Towards a Personal Information Revolution

Abstract: There has been an explosion of data on the Web. Much of this data is generated by or else refers to individuals. This emerging area of personal information assets is presenting new opportunities and challenges for all of us. This paper reviews a UK Government initiative called midata’. The midata programme of work is being undertaken with leading businesses and consumer groups in order to give consumers access to their personal data in a portable and electronic format. Consumers can then use this data to help them better understand their own consumption behaviours and patterns, as well as make more informed and appropriate purchasing and other decisions. The paper reviews the history and context, principles and progress behind midata. It describes concrete examples and examines some of the challenges in making personal information assets available in this way. The paper reviews some of the key tools and technologies available for managing personal information assets. We also summarise the legislative landscape and various legal proposals under development that are relevant to midata. We review similar efforts elsewhere in particular those underway in the US under a programme of work called Smart Disclosure. This work seeks to release personal information held by government and business back to citizens and consumers. Finally we discuss likely future developments.

Linked data in crowdsourcing purposive social network

Abstract: Internet is an easy medium for people to collaborate and crowdsourcing is an efficient feature of social web where people with common interest and expertise come together to solve specific problems by collective thinking and create a community. It can also be used to filter out important information from large data, remove spams, and gamification techniques are used to reward the users for their contribution and keep a sustainable environment for the growth of the community. Semantic web technologies can be used to structure the community data so it can be combined, decentralized and be used across platform. Using such tools knowledge can be enhanced and easily discovered and merged together. This paper discusses the concept of a purposive social network where people with similar interest and varied expertise come together, use crowdsourcing technique to solve a common problem and build tools for common purpose. The StackOverflow website is chosen to study the purposive network, different network ties and roles of user is studied. Linked Data is used for name disambiguation of keywords and topics for easier search and discovery of experts in a field and provide useful information that is otherwise unavailable in the website.

Reliability analyses of open government data

Abstract: Public authorities are increasingly sharing sets of open data. These data are often preprocessed (e.g. smoothened, aggregated) to avoid to expose sensible data, while trying to preserve their reliability. We present two procedures for tackling the lack of methods for measuring the open data reliability. The first procedure is based on a comparison between open and closed data, and the second derives reliability estimates from the analysis of open data only. We evaluate these two procedures over data from the data.police.uk website and from the Hampshire Police Constabulary in the UK. With the first procedure we show that the open data reliability is high despite preprocessing, while with the second one we show how it is possible to achieve interesting results concerning the open data reliability estimation when analyzing open data alone.

An Approach to Building High-Quality Tag Hierarchies from Crowdsourced Taxonomic Tag Pairs

Abstract: Building taxonomies for web content is costly. An alternative is to allow users to create folksonomies, collective social classifications. However, folksonomies lack structure and their use for searching and browsing is limited. Current approaches for acquiring latent hierarchical structures from folksonomies have had limited success. We explore whether asking users for tag pairs, rather than individual tags, can increase the quality of derived tag hierarchies. We measure the usability cost, and in particular cognitive effort required to create tag pairs rather than individual tags. Our results show that when applied to tag pairs a hierarchy creation algorithm (Heymann-Benz) has superior performance than when applied to individual tags, and with little impact on usability. However, the resulting hierarchies lack richness, and could be seen as less expressive than those derived from individual tags. This indicates that expressivity, not usability, is the limiting factor for collective tagging approaches aimed at crowdsourcing taxonomies.

Linked Nomenclature of Territorial Units for Statistics

Abstract: The publication of public sector information PSI data sets has brought to the attention of the scientific community the redundant presence of location based context. At the same time it stresses the inadequacy of current Linked Data services for exploiting the semantics of such contextual dimensions for easing entity retrieval and browsing. In this paper we describe our Linked Data representation of the NUTS European statistical subdivision, created to support the e-government and public sector in publishing their data sets. The topological knowledge published in the Linked NUTS can be reused in order to enrich the geographical context of other data sets, in particular in a scenario where statistical data sets describe information that have strong ties with the territory, and therefore with its geography.

Creating an open data application for sustainability education: Globe-Town

Abstract: Globe-Town.org is an information visualisation using open data, designed to convey the connections between economics, society and environment in a globalising world. It informs about global challenges whilst being easy and enjoyable to use. It aims to motivate to act by showing how an intensifying network of linkages connects global sustainability issues to the home country of the user, and the topics that they care about. GlobeTown’s central innovation in interaction design is how it combines visualisation of the properties of the individual country with a listing of the countries that are most strongly connected to it by a chosen type of relationship. This shows how ties of trade, migration, communication and culture increasingly connect countries, sharing the risks, responsibilities and opportunities of issues like climate change. Globe-Town takes a domain-specific storytelling approach to information visualisation, co-creating hypermedia narratives of sustainability and globalisation along with the user. Having sufficient open data availability is found to be highly valuable, as it prevents understanding of these expansive interdisciplinary problems being stymied by arbitrary limits of data access. Globe-Town has won second place in the Linked Up Veni Open Education competition and third place in the finals of the World Bank's Apps for Climate competition. This article describes the GlobeTown application in detail, along with the numerous online data resources that have enabled it, and the design and development process through which it was created

Leveraging social network analysis with topic models and the Semantic Web extended

Abstract: Research in the Semantic Web, especially in modeling virtual communities, has provided models useful to represent the richness of these social network interactions. The SIOC Semantically-Interlinked Online Communities vocabulary provides concepts and properties that can be used to describe information from online communities e.g., message boards, wikis, weblogs, etc.. However, the SIOC ontology does not consider social aspects nor the higher order semantics hidden in linkages between community members. This paper describes SIOC-SNA-DM, an extension of the SIOC vocabulary. SIOC-SNA-DM's model is tri-partite, consisting of People, Policies, and Purposes which are social aspects observable in most social communities. A challenge to using our model is how to populate these aspects, since higher order semantics from interactions need to be extracted. Thus, we explain how this population is done with advanced text mining using a latent semantic technique over a large virtual community called Plexilandia.cl with more than 2500 musicians working on the site.Our previous work, in this area, has shown how including these social aspects help to outperform results generated by state-of-the-art techniques. One of the novelties of this present work is the introduction and the elucidation of SIOC-SNA-DM, and how to populate the ontology in order to support the social aspects needed to enhance results of Social Network Mining techniques.

Using Personal Activity Diaries to Enhance Electronic Health Records

Abstract: Copyright is held by the author/owner(s) CHI’13, April 27 – May 2, 2013, Paris, France ACM 978-1-XXXX-XXXX-X/XX/XX Abstract We posit that significant gains in patient-clinician communications can be made by helping clinicians to better understand a patient’s life between their visits to the doctor In this paper, we propose a mechanism for augmenting electronic health records with personal activity diaries, high-resolution records of a patient’s daily life, derived automatically from personal activity sensors These activity diaries establish a shared context for discussing the patient’s lifestyle and condition

Investigating The Use Of Semantic Technologies In Spatial Mapping Applications.

Abstract: Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend.