Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

Correlated dynamics in egocentric communication networks

We investigate the communication sequences of millions of people through two different channels and analyze the fine grained temporal structure of correlated event trains induced by single individuals. By focusing on correlations between the heterogeneous dynamics and the topology of egocentric networks we find that the bursty trains usually evolve for pairs of individuals rather than for the ego and his/her several neighbors thus burstiness is a property of the links rather than of the nodes. We compare the directional balance of calls and short messages within bursty trains to the average on the actual link and show that for the trains of voice calls the imbalance is significantly enhanced, while for short messages the balance within the trains increases. These effects can be partly traced back to the technological constrains (for short messages) and partly to the human behavioral features (voice calls). We define a model that is able to reproduce the empirical results and may help us to understand better the mechanisms driving technology mediated human communication dynamics.Comment: 7 pages, 6 figure

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework

[EN] The number of people and organizations using online social networks as a new way of communication is continually increasing. Messages that users write in networks and their interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary systems that collect, process, and analyze the information generated. The majority of existing tools analyze information related to an online event once it has finished or in a specific point of time (i.e., without considering an in-depth analysis of the evolution of users activity during the event). They focus on an analysis based on statistics about the quantity of information generated in an event. In this article, we present a multi-agent system that automates the process of gathering data from users activity in social networks and performs an in-depth analysis of the evolution of social behavior at different levels of granularity in online events based on network theory metrics. We evaluated its functionality analyzing users activity in events on Twitter.This work is partially supported by the PROME-TEOII/2013/019, TIN2014-55206-R, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095.Del Val Noguera, E.; Martínez, C.; Botti, V. (2016). Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework. Soft Computing. 20(11):4331-4345. https://doi.org/10.1007/s00500-016-2301-0S433143452011Ahn Y-Y, Han S, Kwak H, Moon S, Jeong H (2007) Analysis of topological characteristics of huge online social networking services. 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In: CHI’11, pp 253–262Guimerà R, Llorente A, Moro E, Sales-Pardo M (2012) Predicting human preferences using the block structure of complex social networks. PloS One 7(9):e44620Huberman BA, Romero DM, Wu F (2008) Social networks that matter: Twitter under the microscope. arXiv preprint arXiv:0812.1045Jamali M, Abolhassani H (2006) Different aspects of social network analysis. In: 2006 IEEE/WIC/ACM international conference on web intelligence (WI 2006 main conference proceedings)(WI’06). IEEE, pp 66–72Jiang Y, Jiang J (2014) Understanding social networks from a multiagent perspective. Parallel Distrib Syst IEEE Trans 25(10):2743–2759Kossinets G, Watts D (2006) Empirical analysis of an evolving social network. Science 311(5757):88–90Kumar R, Novak J, Tomkins A (2010) Structure and evolution of online social networks. In: Yu PS, Han J, Faloutsos C (eds) Link mining: models, algorithms, and applications. 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Deciphering Network Community Structure by Surprise

The analysis of complex networks permeates all sciences, from biology to sociology. A fundamental, unsolved problem is how to characterize the community structure of a network. Here, using both standard and novel benchmarks, we show that maximization of a simple global parameter, which we call Surprise (S), leads to a very efficient characterization of the community structure of complex synthetic networks. Particularly, S qualitatively outperforms the most commonly used criterion to define communities, Newman and Girvan's modularity (Q). Applying S maximization to real networks often provides natural, well-supported partitions, but also sometimes counterintuitive solutions that expose the limitations of our previous knowledge. These results indicate that it is possible to define an effective global criterion for community structure and open new routes for the understanding of complex networks.Comment: 7 pages, 5 figure

Towards a new philosophy of engineering: structuring the complex problems from the sustainability discourse

This dissertation considers three broad issues which emerge from the sustainability discourse. First is the nature of the discourse itself, particularly the underlying philosophical positions which are represented. Second, is the nature of the highly complex types of problem which the discourse exposes. And third is whether the engineering profession, as it is practised currently, is adequate to deal with such problems. The sustainability discourse exposes two distinct, fundamentally irreconcilable philosophical positions. The first, “sustainable development”, considers humanity to be privileged in relation to all other species and ecosystems. It is only incumbent upon us to look after the environment to the extent to which it is in our interests to do so. The second, “sustainability”, sees humanity as having no special moral privilege and recognises the moral status of other species, ecosystems, and even wilderness areas. Thus, sustainability imposes upon us a moral obligation to take their status into account and not to degrade or to destroy them. These two conflicting positions give rise to extremely complex problems. An innovative taxonomy of problem complexity has been developed which identifies three broad categories of problem. Of particular interest in this dissertation is the most complex of these, referred to here as the Type 3 problem. The Type 3 problem recognises the systemic complexity of the problem situation but also includes differences of the domain of interests as a fundamental, constituent part of the problem itself. Hence, established systems analysis techniques and reductionist approaches do not work. The domain of interests will typically have disparate ideas and positions, which may be entirely irreconcilable. The dissertation explores the development of philosophy of science, particularly in the last 70 years. It is noted that, unlike the philosophy of science, the philosophy of engineering has not been influenced by developments of critical theory, cultural theory, and postmodernism, which have had significant impact in late 20th-century Western society. This is seen as a constraint on the practice of engineering. Thus, a set of philosophical principles for sustainable engineering practice is developed. Such a change in the philosophy underlying the practice of engineering is seen as necessary if engineers are to engage with and contribute to the resolution of Type 3 problems. Two particular challenges must be overcome, if Type 3 problems are to be satisfactorily resolved. First, issues of belief, values, and morals are central to this problem type and must be included in problem consideration. And second, the problem situation is usually so complex that it challenges the capacity of human cognition to deal with it. Consequently, extensive consideration is given to cognitive and behavioural psychology, in particular to choice, judgement and decision-making in uncertainty. A novel problem-structuring approach is developed on three levels. A set philosophical foundation is established; a theoretical framework, based on general systems theory and established behavioural and cognitive psychological theory, is devised; and a set of tools is proposed to model Type 3 complex problems as a dynamic systems. The approach is different to other systems approaches, in that it enables qualitative exploration of the system to plausible, hypothetical disturbances. The problem-structuring approach is applied in a case study, which relates to the development of a water subsystem for a major metropolis (Sydney, Australia). The technique is also used to critique existing infrastructure planning processes and to propose an alternative approach

Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Suicide prevention for youth - a mental health awareness program: lessons learned from the Saving and Empowering Young Lives in Europe (SEYLE) intervention study.

ABSTRACT: BACKGROUND: The Awareness program was designed as a part of the EU-funded Saving and Empowering Young Lives in Europe (SEYLE) intervention study to promote mental health of adolescents in 11 European countries by helping them to develop problem-solving skills and encouraging them to self-recognize the need for help as well as how to help peers in need. METHODS: For this descriptive study all coordinators of the SEYLE Awareness program answered an open-ended evaluation questionnaire at the end of the project implementation. Their answers were synthesized and analyzed and are presented here. RESULTS: The results show that the program cultivated peer understanding and support. Adolescents not only learned about mental health by participating in the Awareness program, but the majority of them also greatly enjoyed the experience. CONCLUSIONS: Recommendations for enhancing the successes of mental health awareness programs are presented. Help and cooperation from schools, teachers, local politicians and other stakeholders will lead to more efficacious future programs

Standardizing effect size from linear regression models with log-transformed variables for meta-analysis

Background: Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. Methods: We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. Results: In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. Conclusions: The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables