An Abstract Formal Basis for Digital Crowds

Crowdsourcing, together with its related approaches, has become very popular in recent years. All crowdsourcing processes involve the participation of a digital crowd, a large number of people that access a single Internet platform or shared service. In this paper we explore the possibility of applying formal methods, typically used for the verification of software and hardware systems, in analysing the behaviour of a digital crowd. More precisely, we provide a formal description language for specifying digital crowds. We represent digital crowds in which the agents do not directly communicate with each other. We further show how this specification can provide the basis for sophisticated formal methods, in particular formal verification.Comment: 32 pages, 4 figure

Crisis Analytics: Big Data Driven Crisis Response

Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools can be leveraged to process the large amounts of crisis-related data (in the form of user generated data in addition to the traditional humanitarian data) to provide an insight into the fast-changing situation and help drive an effective disaster response. This article introduces the history and the future of big crisis data analytics, along with a discussion on its promise, challenges, and pitfalls

'The Greek Fall: Simulacral Thanatotourism in Europe'

The paper explores the socio-cultural dynamics of Greek demonstrations in 2011, suggesting that their function exceeds that of social movements as we know them. A form of what I term ‘simulacral thanatotourism’, including marches and demonstrations to Greek cities in protest for austerity measures, actualised in this context a form of mourning about the end of Greece’s place in European polity. This mourning, which places Greece at the centre of a withering European democratic cosmos, inspires in today’s dystopian Greek Raum two conflicting forms of social action: one is geared towards consumption of the country’s political history in terms similar to those we examine as ‘tourism’. This symbolic consumption of history re-writes the European past from a Greek standpoint while simultaneously promoting relevant entrepreneurial initiatives – in particular, the global circulation of imagery linked to riots and protests and thus the movement of the abject aspects of Greek culture in global spaces. The second form of action is directed against the image of contemporary Greece as a corrupt topos that does not deserve a place in Europe’s political Paradise; this places the blame for the nation’s demise on its political factions. The two forms of action may be antithetical but do coexist in Greek social movements to the date, articulating a cosmology of nostalgia for Greece as an idyllic tourist object. The paper explores these themes through the proliferation of imagery in recent demonstrations, highlighting how a tourist-like marketing of activist visual culture partakes in reproductions of theological ideas rooted in Europeanist discourse

Counterexample Generation in Probabilistic Model Checking

Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulae in discrete-time Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) k-shortest (hop-constrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that typically the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol

Towards Smarter Management of Overtourism in Historic Centres Through Visitor-Flow Monitoring

Historic centres are highly regarded destinations for watching and even participating in diverse and unique forms of cultural expression. Cultural tourism, according to the World Tourism Organization (UNWTO), is an important and consolidated tourism sector and its strong growth is expected to continue over the coming years. Tourism, the much dreamt of redeemer for historic centres, also represents one of the main threats to heritage conservation: visitors can dynamize an economy, yet the rapid growth of tourism often has negative effects on both built heritage and the lives of local inhabitants. Knowledge of occupancy levels and flows of visiting tourists is key to the efficient management of tourism; the new technologies—the Internet of Things (IoT), big data, and geographic information systems (GIS)—when combined in interconnected networks represent a qualitative leap forward, compared to traditional methods of estimating locations and flows. A methodology is described in this paper for the management of tourism flows that is designed to promote sustainable tourism in historic centres through intelligent support mechanisms. As part of the Smart Heritage City (SHCITY) project, a collection system for visitors is developed. Following data collection via monitoring equipment, the analysis of a set of quantitative indicators yields information that can then be used to analyse visitor flows; enabling city managers to make management decisions when the tourism-carrying capacity is exceeded and gives way to overtourism.Funded by the Interreg Sudoe Programme of the European Regional Development Funds (ERDF

Learning from Digital Natives: Bridging Formal and Informal Learning. Final Report

Overview This report suggests that students are increasingly making use of a variety of etools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) to support their informal learning within formalised educational settings, and that they use the tools that they have available if none are provided for them. Therefore, higher education institutions should encourage the use of these tools. Aims and background This study aimed to explore how e-tools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) and the processes that underpin their use can support learning within educational institutions and help improve the quality of students’ experiences of learning in higher education (pgs 9-11). Methodology The study entailed: (i) desk research to identify related international research and practice and examples of integration of e-tools and learning processes in formal educational settings; (ii) a survey of 160 engineering and social work students across two contrasting Scottish universities (pre- and post-1992) – the University of Strathclyde and Glasgow Caledonian University – and follow-up interviews with eight students across the two subject areas to explore which technologies students were using for both learning and leisure activities within and outside the formal educational settings and how they would like to use such technologies to support their learning in both formal and informal settings; and (iii) interviews with eight members of staff from across the institutions and two subject areas to identify their perceptions of the educational value of the e-tools. (pgs 24-27). Key findings • Students reported making extensive use of a variety of both e-tools (such as mobile phones, email, MSN, digital cameras) and social networking tools (such as Bebo, MySpace, Wikipedia and YouTube) for informal socialisation, communication, information gathering, content creation and sharing, alongside using the institutionally provided technologies and learning environments. • Most of the students owned their own computer or had access to a sibling or parent’s computer. Many students owned a laptop but preferred not to bring it onto campus due to security concerns and because they found it too heavy to carry about. • Ownership of mobile phones was ubiquitous. • Whilst the students’ information searching literacy seemed adequate, the ability of these students to harness the power of social networking tools and informal processes for their learning was low. Staff reported using a few Web 2.0 and social software tools but they were generally less familiar with how these could be used to support learning and teaching. There were misconceptions surrounding the affordances of the tools and fears expressed about security and invasion of personal space. Considerations of the costs and the time it would take staff to develop their skills meant that there was a reluctance to take up new technologies at an institutional level. • Subject differences emerged in both staff and student perceptions as to which type of tools they would find most useful. Attitudes to Web 2.0 tools were different. Engineers were concerned with reliability, using institutional systems and inter-operability. Social workers were more flexible because they were focused on communication and professional needs. • The study concluded that digital tools, personal devices, social networking software and many of the other tools explored all have a large educational potential to support learning processing and teaching practices. Therefore, use of these tools and processes within institutions, amongst staff and students should be encouraged. • The report goes on to suggest ways in which the use of such technologies can help strengthen the links between informal and formal learning in higher education. The recommendations are grouped under four areas – pedagogical, socio-cultural, organisational and technological

The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades

Small-scale spatial events are situations in which elements or objects vary in such away that temporal dynamics is intrinsic to their representation and explanation. Someof the clearest examples involve local movement from conventional traffic modelingto disaster evacuation where congestion, crowding, panic, and related safety issue arekey features of such events. We propose that such events can be simulated using newvariants of pedestrian model, which embody ideas about how behavior emerges fromthe accumulated interactions between small-scale objects. We present a model inwhich the event space is first explored by agents using ?swarm intelligence?. Armedwith information about the space, agents then move in an unobstructed fashion to theevent. Congestion and problems over safety are then resolved through introducingcontrols in an iterative fashion and rerunning the model until a ?safe solution? isreached. The model has been developed to simulate the effect of changing the route ofthe Notting Hill Carnival, an annual event held in west central London over 2 days inAugust each year. One of the key issues in using such simulation is how the processof modeling interacts with those who manage and control the event. As such, thischanges the nature of the modeling problem from one where control and optimizationis external to the model to one where this is intrinsic to the simulation

Masses, crowds, communities, movements: collective formations in the digital age

From prosumers to swarms, crowds, e-movements and e-communities, the Internet allows for new forms of collective behavior and action anywhere on the spectrum between individ- uals and organizations. In all of these cases, online technologies function as connectivity- enhancing tools and have prompted the search for novel or inherently different collective formations and actors on the web. However, research to date on these new collective formations on the web lacks a sociologi- cally informed and theoretical focus. Instead, loosely defined terms such as “swarm”, “crowd” or “network” are readily used as a catch-all for any formation that cannot be characterized as a stable corporate actor. Such terms contribute little to an understanding of the vast range of collective activities on the Internet, namely because the various collective formations differ significantly from each other with regard to their size, internal structure, interaction, institutional dynamics, stability and strategic capability. In order to bridge this gap, this study investigates two questions: One, how might the very differently structured collectives on the Internet be classified and distinguished along actor- or action-centered theory? And two, what influence do the technological infrastructures in which they operate have on their formation, structure and activities? For this we distinguish between two main types of collectives: non-organized collectives, which exhibit loosely-coupled col- lective behavior, and collective actors with a separate identity and strategic capability. Further, we examine the newness, or distinctive traits, of online-based collectives, which we identify as being the strong and hitherto non-existent interplay between the technological infrastruc- tures that these collectives are embedded in and the social processes of coordination and institutionalization they must engage in in order to maintain their viability over time. Conventional patterns of social dynamics in the development and stabilization of collective action are now systematically intertwined with technology-induced processes of structuration.Dieses Discussion Paper geht den beiden Fragen nach, wie sich die sehr unterschiedlich strukturierten kollektiven Gebilde im Internet - beispielsweise Swarms, Crowds, Social Networks, E-Communities, E-Movements - akteur- bzw. handlungstheoretisch einordnen und voneinander abgrenzen lassen und welchen Einfluss die technologischen Infrastrukturen, in denen sie sich bewegen, auf ihre Entstehung, Strukturierung und Aktivität haben. Dazu wird zunächst zwischen zwei wesentlichen Varianten kollektiver Formationen unterschieden, die als nicht-organisierte Kollektive und als strategiefähige kollektive Akteure charakterisiert werden. Daran anknüpfend wird herausgearbeitet, was das Neue ist, das kollektive Formationen im Internet auszeichnet: Es besteht in einer so zuvor nicht gekannten Verschränkung nach wie vor unverzichtbarer sozialer Konstitutions-, Koordinations- und Institutionalisierungsprozesse mit den technischen Infrastrukturen, die das Netz bietet. Klassische soziale Entstehungs- und Organisierungsmuster kollektiven Verhaltens bzw. Handelns mischen sich im Online-Kontext systematisch mit eigenständigen technischen Strukturierungsleistungen