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Highlights: [•] The impact of digital technologies on writing and reading is investigated in Finland. [•] The positive affordances of writing on paper are similar to those found in Italy. [•] Students consider important to write a lot, quickly and instantly without losing time. [•] A keyboard is a point of reference for all comparisons in students’ responses. [Copyright &y& Elsevier]

In the early twenty-first century, women continue to receive substantially less media coverage than men, despite women’s much increased participation in public life. Media scholars argue that actors in news organizations skew news coverage in favor of men and male-related topics. However, no previous study has systematically examined whether such media bias exists beyond gender ratio imbalances in coverage that merely mirror societal-level structural and occupational gender inequalities. Using novel longitudinal data, we empirically isolate media-level factors and examine their effects on women’s coverage rates in hundreds of newspapers. We find that societal-level inequalities are the dominant determinants of continued gender differences in coverage. The media focuses nearly exclusively on the highest strata of occupational and social hierarchies, in which women’s representation has remained poor. We also find that women receive greater exposure in newspaper sections led by female editors, as well as in newspapers whose editorial boards have higher female representation. However, these differences appear to be mostly correlational, as women’s coverage rates do not noticeably improve when male editors are replaced by female editors in a given newspaper. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue including manipulation and bribery in voting rules, matching problems and hedonic games.

Describes the above-named upcoming special issue or section. May include topics to be covered or calls for papers. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic hybrid predator-prey model with Beddington-DeAngelis functional response and Lévy jumps is studied. Firstly, it is proved that the model has a unique global solution. Secondly, sufficient conditions for weak persistence in the mean and extinction of prey and predator populations are established. Finally, sufficient conditions for the existence and uniqueness of ergodic stationary distribution are established. Moreover, several numerical simulations are presented to illustrate the main results. [ABSTRACT FROM AUTHOR]

Vast amounts of news are consumed through algorithmically curated media environments, such as search engines, social networking sites, or news aggregators. This renders algorithmic content curation with much societal relevance and highlights the urgent need for independent and resilient academic research. Therefore, a plethora of methodological approaches have been applied, such as case studies, expert interviews, observations, or agent-based approaches. The paper discusses the applicability of these methodological efforts for journalism studies, showing that all of these approaches face their limitations, especially with regard to external validity, recruitment difficulties, and data reliability. Thereby, agent-based testing represents one of the most promising approaches to overcome plenty of these methodological limitations. Agent-based testing is a systematic and experimental approach that emulates online human behavior to test algorithmically curated media environments under various conditions. For this to be achieved properly, this paper suggests a multitude of settings and requirements to adequately face the technological, legal, and ethical challenges, which come with the empirical investigation of algorithmic content curation. Ultimately, the paper presents both general considerations and practical instructions (using the "ScrapeBot") to employ agent-based testing for journalism studies. [ABSTRACT FROM AUTHOR]

As researchers use computational methods to study complex social behaviors at scale, the validity of this computational social science depends on the integrity of the data. On July 2, 2015, Jason Baumgartner published a dataset advertised to include “every publicly available Reddit comment” which was quickly shared on Bittorrent and the Internet Archive. This data quickly became the basis of many academic papers on topics including machine learning, social behavior, politics, breaking news, and hate speech. We have discovered substantial gaps and limitations in this dataset which may contribute to bias in the findings of that research. In this paper, we document the dataset, substantial missing observations in the dataset, and the risks to research validity from those gaps. In summary, we identify strong risks to research that considers user histories or network analysis, moderate risks to research that compares counts of participation, and lesser risk to machine learning research that avoids making representative claims about behavior and participation on Reddit. [ABSTRACT FROM AUTHOR]

This paper is influenced by the research of Thomas Schelling on spatial segregation; in his seminal work on the subject he used simple simulations to show that even highly tolerant individuals end up being spatially aggregated far beyond the local requirement of their tolerance level. In this paper we are not seeking to find the conditions, in terms of density of population and tolerance level, that lead to a global stable state where all the individuals are satisfied in view of their own neighborhoods. Here the context is: (i) a space full of agents where each individual is in continual contact with a maximum number of neighbors; and (ii) where both a principal and a secondary discrimination criterion compel people to leave their places. As, in general, the first hypothesis does not allow the population to converge within the meaning of Schelling, only incomplete segregation phenomena are observable. So the problematic will be to determine, according to the respective strength of the two discrimination criteria, the spatial repartition of the agents resulting from their moves; in such a general context, we will refer to segregation as being strong or weak or even mixed. [ABSTRACT FROM AUTHOR]

This study shows how liking politicians’ public Facebook posts can be used as an accurate measure for predicting present-day voter intention in a multiparty system. We highlight that a few, but selective digital traces produce prediction accuracies that are on par or even greater than most current approaches based upon bigger and broader datasets. Combining the online and offline, we connect a subsample of surveyed respondents to their public Facebook activity and apply machine learning classifiers to explore the link between their political liking behaviour and actual voting intention. Through this work, we show that even a single selective Facebook like can reveal as much about political voter intention as hundreds of heterogeneous likes. Further, by including the entire political like history of the respondents, our model reaches prediction accuracies above previous multiparty studies (60–70%). The main contribution of this paper is to show how public like-activity on Facebook allows political profiling of individual users in a multiparty system with accuracies above previous studies. Beside increased accuracies, the paper shows how such parsimonious measures allows us to generalize our findings to the entire population of a country and even across national borders, to other political multiparty systems. The approach in this study relies on data that are publicly available, and the simple setup we propose can with some limitations, be generalized to millions of users in other multiparty systems. [ABSTRACT FROM AUTHOR]

Participation in social sensing applications is challenged by privacy threats. Large-scale access to citizens' data allow surveillance and discriminatory actions that may result in segregation phenomena in society. On the contrary are the benefits of accurate computing analytics required for more informed decision-making, more effective policies and regulation of techno-socio-economic systems supported by 'Internet-of Things' technologies. In contrast to earlier work that either focuses on privacy protection or Big Data analytics, this paper proposes a self-regulatory information sharing system that bridges this gap. This is achieved by modeling information sharing as a supply-demand system run by computational markets. On the supply side lie the citizens that make incentivized but self-determined decisions about the level of information they share. On the demand side stand data aggregators that provide rewards to citizens to receive the required data for accurate analytics. The system is empirically evaluated with two real-world datasets from two application domains: (i) Smart Grids and (ii) mobile phone sensing. Experimental results quantify trade-offs between privacy-preservation, accuracy of analytics and costs from the provided rewards under different experimental settings. Findings show a higher privacy-preservation that depends on the number of participating citizens and the type of data summarized. Moreover, analytics with summarization data tolerate high local errors without a significant influence on the global accuracy. In other words, local errors cancel out. Rewards can be optimized to be fair so that citizens with more significant sharing of information receive higher rewards. All these findings motivate a new paradigm of truly decentralized and ethical data analytics. [ABSTRACT FROM AUTHOR]

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The 57th meeting and conference of the International Society for the Systems Sciences focused on the meta-theme of Curating the Conditions for a Thrivable Planet. The event was conceived as a living learning lab for collective intelligence that aimed to provide its participants with a set of total immersion environments in which to explore our role as systems scientists, and beyond that, as members of a globalizing species at this time in history. As such, the conference provided individual and collective opportunities to foster that basic feeling of being connected, to explore what it means to be appreciative systems (as Sir Geoffrey Vickers would have it) to manifest new levels of community and fundamentally, to evolve the narrative of our role as authors of the conscious evolution of our species. This paper presents the stage-setting remarks presented at the opening of the 57th annual meeting and conference of the ISSS, inviting members and conference participants to address the principal theme of this conference that took place in Vietnam: the search for systemic leverage points for emerging a global eco-civilization. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The quality of collective intelligence flowing in and across systems communities of various disciplines, and the fragmentation or connectedness of their mental models of the world, shape their capacity to assist decision-makers and social movements in defining, mapping, and addressing the world problematique, by identifying policy options and anticipating their outcomes. In their current state of fragmentation, the systems sciences' epistemic communities cannot provide that assistance. Upgrading their collective intelligence is a vital imperative. This paper is suggest the prototyping of a Collective Intelligence Enhancement Lab and describes its core idea as a platform with an innovation architecture that integrates social, electronic, cognitive, and inner technologies and processes. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. [ABSTRACT FROM AUTHOR]

Transactional memory programs may have dynamic available parallelism, which is defined as the number of transactions that can be committed concurrently. Prior work presented adaptive concurrency control, which adapts the number of active threads at runtime, and thus the number of concurrently executing transactions, based on available parallelism. Reducing threads when available parallelism is low, and vice versa, improved speedup and reduced wasted work (in aborted transactions). However, prior work did not consider the case where individual threads exhibit dynamic available parallelism. Deactivating threads with low available parallelism, and vice versa, may improve speedup and reduce wasted work further. This paper introduces weighted adaptive concurrency control to exploit the variance in available parallelism between threads. Four algorithms are designed, implemented, and evaluated. They improve speedup and reduce wasted work over prior non-weighted algorithms in applications whose threads exhibit such variance, while maintaining performance parity in applications whose threads do not. [ABSTRACT FROM AUTHOR]

This paper describes how the EPparallel tool splits a single annual simulation into 12 simulations of one month each and runs them in parallel. The paper also describes the methodology to prepare input files, enable file sharing between nodes, collate results generated by the nodes, and ensure quality check on the simulations. The EPparallel tool uses Message Passing Interface library and runs on Linux. The tool has been tested on 16 commercial reference buildings over 16 US weather files. The results of these 256 runs which include the run times, computing time overheads, speed gains and accuracy of results are presented in this paper. The speed gain ranged from 2.9×to 7.8×and deviation (percentage of output values obtained in parallel simulation which were off by more than 1% as compared to output values obtained in annual simulation) ranged from 0% to 4%. [ABSTRACT FROM PUBLISHER]

There is an increased use of public e-services integrating citizens into public administration through electronic interfaces. On-line interaction among public organizations and citizens is one core relation in e-government that hereby becomes embedded into daily practices. A safe entry into e-governmental systems is essential for security and trust in the e-governmental systems and schools as well as public services in general. This paper addresses how electronic identification has been used for access to public e-services in schools in a Swedish municipality. This paper draws on a case study of use of ICT platforms in education administration in order to study the implementation of secure login process and factors that may have implications upon trust in-and legitimacy of public e-services at local e-government level. Besides describing the implementation process and analyzing security and organizational arrangements connected to the use of the platform, the paper address the argument that secure identification tools are essential for increased use of e-services and lead to greater legitimacy of the public (e)services. The analysis focuses on information security, organization set-up and potential development of the platforms, contributing with empirical findings and conceptual applications. A key finding was that the organization of identification and access to public e-services seemed highly dependent of the organizational structure of the public schools. The more general implication of the findings was that safe and well organized identification systems that were considered as trustworthy and useful among citizens were essential for increased use of the services and legitimate public e-services in general. [ABSTRACT FROM AUTHOR]

Computational social science provides an innovative set of methodological tools that can help answer questions of substantive interest to migration and integration research. In this introductory article, we first provide a brief history of how computational approaches have already enriched migration and integration research. Second, we identify several key promises of computational migration research (e.g. better access to hard-to-reach populations, cost reductions and time savings, better detection of causal mechanisms, avoidance of response biases and methodological nationalism through fine-grained, time-stamped, live digital trace data) and key challenges (e.g. missing categories, sampling issues, ethical concerns). Third, we illustrate how the contributions of this special issue fulfil some of these promises – as well as deal with the challenges – to gain new insights into key questions of migration and integration research that address why people emigrate, what the evolution of structural patterns in migration networks is, whether refugee movements can be predicted, how host communities respond to the influx of refugees, how people interpret, frame, and discuss these arrivals, how migration-related discourse responds to external shocks, and how spatial segregation patterns of migrants and ethnic minorities emerge. [ABSTRACT FROM AUTHOR]

In 1947 Jerzy Łoś proposed a positional logic based on the re- alization operator. We follow his work and present it in the context of fundamental challenges of sociology such as the complexity of social reality and reflexivity of social agents. The paper is an outline of the general concept, as it opens a discussion and sets ground for future elaborations. In this paper, we are considering the concept according to which the ex- pressions put forward by Łoś's system might be indexed not only by spatial and temporal variables, but also by social contexts. And as such Łoś's system might be a significant improvement, a valuable addition for social simulations and computational sociology, which use multi-agent systems and agent-based modeling. We consider how Łoś's operator might be useful for these disciplines, as it gives a chance to combine of formalization with the humanistic coefficient, which represents the issues of complexity and reflexivity of social agents. [ABSTRACT FROM AUTHOR]

Schulze and ranked-pairs elections have received much attention recently, and the former has quickly become a quite widely used election system. For many cases these systems have been proven resistant to bribery, control, or manipulation, with ranked pairs being particularly praised for being NP-hard for all three of those. Nonetheless, the present paper shows that with respect to the number of candidates, Schulze and ranked-pairs elections are fixed-parameter tractable to bribe, control, and manipulate: we obtain uniform, polynomial-time algorithms whose running times' degrees do not depend on the number of candidates. We also provide such algorithms for some weighted variants of these problems. [ABSTRACT FROM AUTHOR]

This paper addresses the topic ‘Is Open Channel Worth the Effort?’ both with respect to the seminal book by Professor Henderson and the discipline of open channel flow. The writer’s early contact with Professor Frank Henderson is described. The paper then addresses the topic of open channel flow by reviewing selectively the history of the development of open channel flow and current practice. It is noted that the fundamental principles of continuity, energy and momentum, although developed several 100 years ago, have underpinned the study of open channel flow since their development, and will continue to do so. Over the last 50 years, massive increases in computing power have contributed to very significant advances in our ability to model and understand open channel flow. It is argued that indiscriminant reliance on these models can lead to a reduction, or even total loss, in an understanding of the underlying hydraulic principles. In looking to the future, it is noted that change will continue and that our ability to respond constructively to this change will define our relevance as professionals. It is concluded that both the study of open channel flow and the book by Professor Henderson continue to be very much worth the effort. [ABSTRACT FROM AUTHOR]

In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process. [ABSTRACT FROM AUTHOR]

The role of the Internet in connecting citizens and the state at the extreme poles of the democratic continuum has been the subject of great scrutiny. Orthodoxy suggests online platforms may engage apathetic voters in mature democracies like the US, and embolden the protest of activists living under autocracies such as Iran, but what of the political impact on citizens living in "emerging democracies"? Such a question has been largely neglected, yet this tier of polities represents fertile ground for innovations in democratic communication. In this paper I survey three episodes of contestatory politics 'from below' in Brazil, Chile and India and examine the use of social media platforms to petition the state. I use the compelling parallels between these events and Habermas' classic account of public sphere formation in bourgeois Europe as an entry point to explore how social media may form the architecture for a public sphere in emerging democracies that negates both strong media concentration and weak representative institutions. In so doing I propose three theoretical scenarios that constitute the range of possible state responses to the emergence of online public spheres: 'threat repression', 'polity absorption' and 'elite tokenism'. [ABSTRACT FROM AUTHOR]

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. [ABSTRACT FROM AUTHOR]

It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appeareance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-stucture, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms. [ABSTRACT FROM AUTHOR]

Background: Living systems are associated with Social networks — networks made up of nodes, some of which may be more important in various aspects as compared to others. While different quantitative measures labeled as “centralities” have previously been used in the network analysis community to find out influential nodes in a network, it is debatable how valid the centrality measures actually are. In other words, the research question that remains unanswered is: how exactly do these measures perform in the real world? So, as an example, if a centrality of a particular node identifies it to be important, is the node actually important? Purpose: The goal of this paper is not just to perform a traditional social network analysis but rather to evaluate different centrality measures by conducting an empirical study analyzing exactly how do network centralities correlate with data from published multidisciplinary network data sets. Method: We take standard published network data sets while using a random network to establish a baseline. These data sets included the Zachary's Karate Club network, dolphin social network and a neural network of nematode Caenorhabditis elegans. Each of the data sets was analyzed in terms of different centrality measures and compared with existing knowledge from associated published articles to review the role of each centrality measure in the determination of influential nodes. Results: Our empirical analysis demonstrates that in the chosen network data sets, nodes which had a high Closeness Centrality also had a high Eccentricity Centrality. Likewise high Degree Centrality also correlated closely with a high Eigenvector Centrality. Whereas Betweenness Centrality varied according to network topology and did not demonstrate any noticeable pattern. In terms of identification of key nodes, we discovered that as compared with other centrality measures, Eigenvector and Eccentricity Centralities were better able to identify important nodes. [ABSTRACT FROM AUTHOR]

In this paper, we present algorithms to find near-optimal sets of epidemic spreaders in complex networks. We extend the notion of local-centrality, a centrality measure previously shown to correspond with a node's ability to spread an epidemic, to sets of nodes by introducing combinatorial local centrality. Though we prove that finding a set of nodes that maximizes this new measure is NP-hard, good approximations are available. We show that a strictly greedy approach obtains the best approximation ratio unless P = NP and then formulate a modified version of this approach that leverages qualities of the network to achieve a faster runtime while maintaining this theoretical guarantee. We perform an experimental evaluation on samples from several different network structures which demonstrate that our algorithm maximizes combinatorial local centrality and consistently chooses the most effective set of nodes to spread infection under the SIR model, relative to selecting the top nodes using many common centrality measures. We also demonstrate that the optimized algorithm we develop scales effectively. [ABSTRACT FROM AUTHOR]

An understanding of how individuals shape and impact the evolution of society is vastly limited due to the unavailability of large-scale reliable datasets that can simultaneously capture information regarding individual movements and social interactions. We believe that the popular Indian film industry, “Bollywood”, can provide a social network apt for such a study. Bollywood provides massive amounts of real, unbiased data that spans more than 100 years, and hence this network has been used as a model for the present paper. The nodes which maintain a moderate degree or widely cooperate with the other nodes of the network tend to be more fit (measured as the success of the node in the industry) in comparison to the other nodes. The analysis carried forth in the current work, using a conjoined framework of complex network theory and random matrix theory, aims to quantify the elements that determine the fitness of an individual node and the factors that contribute to the robustness of a network. The authors of this paper believe that the method of study used in the current paper can be extended to study various other industries and organizations. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present in a current, synthetic and graphic form, the concepts specific to the field of system theory. System categories, from the literature, are presented in their dynamics and their particulates. At the same time, we naturally proposed a non-exhaustive classification of systems, depending on linearity, time behavior, number of input-output variables, interaction with the environment, ecological, technological and social aspects. Our research also tracks the behavior of vibration-induced mechanical structures even during their operation. These requests are nonlinear and involve, as a rule, many variables; as such, the graphical representations of their behavior are particularly complex. Current work techniques - program sequences, software, applications - allow for the realization of such representations with increasing fidelity, and the results. with proven applicability, increase the interest of research for dynamic systems in various fields of activity. [ABSTRACT FROM AUTHOR]

Water engineering is an amalgam of engineering (e.g., hydraulics, hydrology, irrigation, ecosystems, environment, water resources) and non-engineering (e.g., social, economic, political) aspects that are needed for planning, designing and managing water systems. These aspects and the associated issues have been dealt with in the literature using different techniques that are based on different concepts and assumptions. A fundamental question that still remains is: Can we develop a unifying theory for addressing these? The second law of thermodynamics permits us to develop a theory that helps address these in a unified manner. This theory can be referred to as the entropy theory. The thermodynamic entropy theory is analogous to the Shannon entropy or the information theory. Perhaps, the most popular generalization of the Shannon entropy is the Tsallis entropy. The Tsallis entropy has been applied to a wide spectrum of problems in water engineering. This paper provides an overview of Tsallis entropy theory in water engineering. After some basic description of entropy and Tsallis entropy, a review of its applications in water engineering is presented, based on three types of problems: (1) problems requiring entropy maximization; (2) problems requiring coupling Tsallis entropy theory with another theory; and (3) problems involving physical relations. [ABSTRACT FROM AUTHOR]

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, “Interdisciplinary Insights into Group and Team Dynamics,” which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges. [ABSTRACT FROM AUTHOR]

This paper deals with how to recognise if the patterns of homophily found in a social network are resilient to small disturbances that may occur in that network. Data from a survey of students in a secondary school in the Canary Islands were replicated using an agent-based model. The model calculated homophily indices and their statistical significance and then simulated small alterations in the distribution of links. The results clearly show that some homophily indices resist these kinds of perturbations and others do not. Evidence suggests that the distribution of individuals across the social network communities is a key factor in explaining why certain patterns of relationships are more resilient than others. [ABSTRACT FROM AUTHOR]

Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a “hopping” behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems. [ABSTRACT FROM AUTHOR]

This paper attempts a preliminary analysis of the global desirability of different forms of openness in AI development (including openness about source code, science, data, safety techniques, capabilities, and goals). Short-term impacts of increased openness appear mostly socially beneficial in expectation. The strategic implications of medium and long-term impacts are complex. The evaluation of long-term impacts, in particular, may depend on whether the objective is to benefit the present generation or to promote a time-neutral aggregate of well-being of future generations. Some forms of openness are plausibly positive on both counts (openness about safety measures, openness about goals). Others (openness about source code, science, and possibly capability) could lead to a tightening of the competitive situation around the time of the introduction of advanced AI, increasing the probability that winning the AI race is incompatible with using any safety method that incurs a delay or limits performance. We identify several key factors that must be taken into account by any well-founded opinion on the matter. [ABSTRACT FROM AUTHOR]

This paper presents a preparation strategy for ethnographic field stays that seeks to speed up the process of gaining social access (after physical access) to the participants in the field by a thematic preparation for the stay. We build on our experiences of an ethnographic inquiry as well as on autopoietic systems theory by Niklas Luhmann. We shall argue that so far, little attention has been given to possibilities of preparation of topics of communication with field participants in the foregoing of a stay. However, the existing methodological literature in this respect so far focuses mainly on the preparation of professional topics for communication. We want to add to these strategies and propose to gain knowledge about possibly acceptable topics for sociable communication in the field by conducting ex ante interviews with existing gatekeepers. Researchers can therefore prepare those topics to quickly gain social access in the field. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Technology plays a prominent role in configuring the way we live and work. In this paper we go further and think that it is a first level driver in the configuration of our deepest perceptions and has a paramount influence on shaping our worldviews and metaphors, though this aspect goes unnoticed for most of the population. In this paper we analyze how metaphors take action in the characterization of technologies, mainly emerging technologies, and in their evolution, and furthermore the impact of technologies and metaphors on the way we perceive our daily life. We analyze metaphors underlying brain nature and artificial intelligence, raising the connections between them and showing how metaphors in one of these fields impact on the way we understand the other. This fact has important consequences, for instance it conditions the evolution of computational systems, and we propose two scenarios for this evolution. This paper relies on the conceptual model and classification of metaphors proposed by Lakoff and Johnson in “Metaphors we live by”, from the orientational metaphors that show values and mantras, to the deepest structural metaphors that are reconfiguring how life is conceived. It also relies on CLA (Causal Layered Analysis) and to its reference book “CLA 2.0” in order to insert this analysis in a wider and future oriented framework and to analyze scenarios. [ABSTRACT FROM AUTHOR]

We use a mechanized verification system, PVS, to examine the argument from Anselm's Proslogion Chapter III, the so-called "Modal Ontological Argument." We consider several published formalizations for the argument and show they are all essentially similar. Furthermore, we show that the argument is trivial once the modal axioms are taken into account. This work is an illustration of Computational Philiosophy and, in addition, shows how these methods can help detect and rectify errors in modal reasoning. [ABSTRACT FROM AUTHOR]

The paper presents a focused survey about the presence and the use of the concept of 'preferences' in Artificial Intelligence. Preferences are a central concept for decision making and have extensively been studied in disciplines such as economy, operational research, decision analysis, psychology and philosophy. However, in the recent years it has also become an important topic both for research and applications in Computer Science and more specifically in Artificial Intelligence, in fields spanning from recommender systems to automatic planning, from non monotonic reasoning to computational social choice and algorithmic decision theory. The survey essentially covers the basics of preference modelling, the use of preference in reasoning and argumentation, the problem of compact representations of preferences, preference learning and the use of non conventional preference models based on extended logical languages. It aims at providing a general reference for all researchers both in Artificial Intelligence and Decision Analysis interested in this exciting interdisciplinary topic. [ABSTRACT FROM AUTHOR]

This paper presents some models and algorithms for social choice in agent networks. Agent networks are graphical models used to represent systems involving multiple, locally interacting, agents. They allow the representation of complex decision-making situations where the utility function of every agent depends on the actions of its neighbors. In this context, coordination requires some optimization method able to determine a combination of individual actions that maximizes social efficiency. We study here the maximization of different social welfare functions covering various attitudes ranging from utilitarianism to egalitarianism. For all these models we propose graph-based algorithms as well as MIP formulations to find optimal sets of actions. We also provide numerical tests to assess their practical efficiency. [ABSTRACT FROM AUTHOR]