Creating context for social influence processes in multiplex networks

Complex networks recently opened new ways for investigating how language use is influenced by the mental representation of word similarities. This work adopts the framework of multiplex lexical networks for investigating lexical retrieval from memory. The focus is on priming, i.e., exposure to a given stimulus facilitating or inhibiting retrieval of a given lexical item. Supported by recent findings of network distance influencing lexical retrieval, the multiplex network approach tests how the layout of hundreds of thousands of word‐word similarities in the mental lexicon can lead to priming effects on multiple combined semantic and phonological levels. Results provide quantitative evidence that phonological priming effects are encoded directly in the multiplex structure of the mental representation of words sharing phonemes either in their onsets (cohort priming) or at their ends (rhyme priming). By comparison with randomised null models, both cohort and rhyming effects are found to be emerging properties of the mental lexicon arising from its multiplexity. These priming effects are absent on individual layers but become prominent on the combined multiplex structure. The emergence of priming effects is displayed both when only semantic layers are considered, an approximated representation of the so‐called semantic memory, and when semantics is enriched with phonological similarities, an approximated representation of the lexical‐auditory nature of the mental lexicon. Multiplex lexical networks can account for connections between semantic and phonological information in the mental lexicon and hence represent a promising modelling route for shedding light on the interplay between multiple aspects of language and human cognition in synergy with experimental psycholinguistic data.

A social network perspective on health communication emphasizes the relational characteristic of health communication and health behavior. The relevancy of this relational perspective is most evident regarding communicable diseases such as infections. However, empirical evidence shows that the same social structures and dynamics are of relevance for physical activity, substance use, mental well‐being, and most other health‐related issues. Even though these behaviors are not contagious in a biological sense, they are transmitted by the means of various forms of communication. Social networks are defined as a set of nodes and their relations (ties). With respect to health communication, the most important social networks encompass people and their communicative actions. But also healthcare organisations and their information exchange can be studied as a social network. Hence, social networks are by no means limited to online networks. Among the most important insight of network analytical studies is the distinction of social selection and influence processes. An increasing body of literature suggests that the selection of similar others may have a stronger effect on the network structure than social influence processes. This means that the similarity of health behavior within a social group (for example, social norms regarding substance use) is caused by the creation of friendship ties among like‐minded persons and is less the result of a diffusion process by opinion leaders and peer influence. Such insights not only help to understand the relational nature of health behavior but are crucial to inform (communicative) intervention strategies.

Meta-path infomax joint structure enhancement for multiplex network representation learning

Research on Instagram addiction (IA) has examined a range of psychological and socio-relational factors to explain the addiction, including personality traits, self-esteem, mental health, social approval, and fear of missing out (FoMO), among others. However, no study has integrated both social influence processes (subjective norms, group norms, and social identity) and meaningful relationships (attachment, dyadic, and friendship ties) with FoMO in relation to IA. This study examined the interplay among social influence processes, meaningful relationships, and FoMO on IA, as well as the moderating roles of subjective and group norms on the indirect effect of anxious attachment on IA via FoMO. The sample consisted of 180 Italian young adults (aged 18-30) who completed validated questionnaires on IA, social influence, relationships, and FoMO after providing consent. Social media use was also explored through an open-ended question. Results indicate that FoMO, social and group norms, and group identification significantly contribute to IA. Anxious attachment had a significant indirect effect on IA via FoMO, with subjective and group norms moderating this association. Qualitative analysis of open-ended responses enriched the understanding of young adults' social media use. These findings highlight the importance of social influence, relationships, and FoMO in young adults' Instagram engagement and suggest directions for addressing problematic use in this group.

High-centrality nodes have disproportionate influence on the behavior of a network; therefore controlling such nodes can efficiently steer the system to a desired state. Existing multiplex centrality measures typically rank nodes assuming the layers are qualitatively similar. Many real systems, however, are comprised of networks heterogeneous in nature, for example, social networks may have both agnostic and affiliative layers. Here, we use rank aggregation methods to identify intervention targets in multiplex networks when the structure, the dynamics, and our intervention goals are qualitatively different for each layer. Our approach is to rank the nodes separately in each layer considering their different function and desired outcome, and then we use Borda count or Kemeny aggregation to identify a consensus ranking—top nodes in the consensus ranking are expected to effectively balance the competing goals simultaneously among all layers. To demonstrate the effectiveness of consensus ranking, we apply our method to a degree-based node removal procedure such that we aim to destroy the largest component in some layers, while maintaining large-scale connectivity in others. For any multi-objective intervention, optimal targets only exist in the Pareto-sense; we, therefore, use a weighted generalization of consensus ranking to investigate the trade-off between the competing objectives. We use a collection of model and real networks to systematically investigate how this trade-off is affected by multiplex network structure. We use the copula representation of the multiplex centrality distributions to generate model multiplex networks with given rank correlations. This allows us to separately manipulate the marginal centrality distribution of each layer and the interdependence between the layers, and to investigate the role of the two using both analytical and numerical methods.

OLMNE+FT: Multiplex network embedding based on overlapping links

Multiplex networks describe a large number of systems ranging from social networks to the brain. These multilayer structure encode information in their structure. This information can be extracted by measuring the correlations present in the multiplex networks structure, such as the overlap of the links in different layers. Many multiplex networks are also weighted, and the weights of the links can be strongly correlated with the structural properties of the multiplex network. For example, in multiplex network formed by the citation and collaboration networks between PRE scientists it was found that the statistical properties of citations to coauthors differ from the one of citations to noncoauthors, i.e., the weights depend on the overlap of the links. Here we present a theoretical framework for modeling multiplex weighted networks with different types of correlations between weights and overlap. To this end, we use the framework of canonical network ensembles, and the recently introduced concept of multilinks, showing that null models of a large variety of network structures can be constructed in this way. In order to provide a concrete example of how this framework apply to real data we consider a multiplex constructed from gene expression data of healthy and cancer tissues.

A tanulmány egy olyan északkelet-magyarországi faluval foglalkozik, ahol a külföldi (ukrajnai) bevándorlás jellemző folyamat. A kutatás célja azoknak a diszkurzív és szimbolikus kulturális gyakorlatoknak az elemzése, amelyeken keresztül a fogadó társadalom kijelöli a településre érkező ukrajnai migránsok társadalmi és munkaerő-piaci státuszát, szabályozza a bevándorlás folyamatát és kialakítja a faluban élő különféle etnikai közösségek (magyarok, romák, ukránok) közötti viszonyokat. A tanulmány a külföldi bevándorlás jelenségét az etnikumközi kapcsolatok különféle formáinak – együttműködés, elkülönülés, versengés stb. – kialakulása, továbbá a csoportok közötti gazdasági, társadalmi, hatalmi egyenlőtlenségek kontextusában értelmezi.

Multiplex networks are representations of multilayer interconnected complex networks where the nodes are the same at every layer. They turn out to be good abstractions of the intricate connectivity of multimodal transportation networks, among other types of complex systems. One of the most important critical phenomena arising in such networks is the emergence of congestion in transportation flows. Here, we prove analytically that the structure of multiplex networks can induce congestion for flows that otherwise would be decongested if the individual layers were not interconnected. We provide explicit equations for the onset of congestion and approximations that allow us to compute this onset from individual descriptors of the individual layers. The observed cooperative phenomenon is reminiscent of Braess' paradox in which adding extra capacity to a network when the moving entities selfishly choose their route can in some cases reduce overall performance. Similarly, in the multiplex structure, the efficiency in transportation can unbalance the transportation loads resulting in unexpected congestion.

Multiplex network community detection algorithm based on motif awareness

Modern society is increasingly massively connected, reflecting an omnipresent tendency to organize social, economic, and technological structures in complex networks. Recently, with the advent of the so-called multiplex networks, new concepts and tools were necessary to better understand the characteristics of this type of system, as well as to analyze and quantify its performance and efficiency. The concept of diversity in multiplex networks is a striking example of this intrinsically interdisciplinary effort to better understand the nature of complex networks. In this work, we introduce the Multiplex Efficiency Index, which allows quantifying the temporal evolution of connectivity diversity, particularly when the number of layers of the multiplex network varies over time. Using data related to air passenger transportation in Brazil we investigate, through the new index, how the Brazilian air transportation network has being changing over the years due to the privatization processes of airports and mergers of airlines in Brazil. Besides that, we show how the Multiplex Efficiency Index is able to quantify fluctuations in network efficiency in a non-biased way, limiting its values between 0 and 1, taking into account the number of layers in the multiplex structure. We believe that the proposed index is of great value for the evaluation of the performance of any multiplex network, and to analyze, in a quantitative way, its temporal evolution independently of the variation in the number of layers.

Synchronization phenomenon plays an important role in the dynamic process on complex networks. In this letter, we consider synchronization under multiplex structures and explore the effect of external parts on the multilayered Kuramoto model with positive correlation between frequencies and degree. We show that large and strong mixing parts of the external layer may put off synchronization while the coupling strength of external layers has an accelerating, but limited, influence on synchronization. In particular, an explosive synchronization can be obtained by weakening the co-evolution coupling strength. The transition tends to be smooth when the co-evolution coupling strength increases. Our findings indicate that externality from multiplex networks, especially the mixing parts, and the co-evolution coupling strength should be of importance for synchronization on one certain layer.

Event Abstract Back to Event The multiplex interplay between phonological and semantic networks impacts word production across different types of aphasia Nichol Castro1* and Massimo Stella2 1 Georgia Institute of Technology, United States 2 University of Southampton, United Kingdom The structure of mental lexicon networks, where similar words are connected, influences several language processes in healthy (e.g., De Deyne, Navarro, & Storms, 2013; Vitevitch, Goldstein, Siew, & Castro, 2015) and clinical (e.g., Castro, Pelczarski, & Vitevitch, 2017) populations, above and beyond traditional psycholinguistic measures. Specific to aphasia, phonological networks were found to influence picture naming performance by people with Broca’s and Wernicke’s aphasia (Vitevitch & Castro, 2015). However, these previous endeavors only examined one type of word-word similarity (e.g., phonological similarity; Vitevitch, 2008). The more recent approach of multiplex lexical networks (Stella, Beckage, & Brede, 2017; Stella, Beckage, Brede, & De Domenico, 2018) allows consideration of semantic and phonological relationships among words simultaneously. We extend the previous analysis of picture naming by people with aphasia to include the multiplex lexical network defined in Stella et al. (2018), where words are connected on four layers representing free associations, synonyms, generalizations, and phonological similarities. We focused on three network measures, namely degree, PageRank, and closeness centrality, for each word on each layer and over the entire multiplex. Degree is a local network measure equal to the number of immediate links of a node. PageRank highlights meso-scale network patterns by identifying the most important nodes in the network. Closeness centrality is a global network measure quantifying how fast information can flow from one node to all others. As multiplex generalizations of these measures we used multidegree (the sum of word degrees across layers), PageRank versatility (De Domenico, Solé-Ribalta, Omodei, Gómez, & Arenas, 2015), and multiplex closeness centrality, respectively. To assess picture naming performance, we conducted logistic regression models predicting the probability of correct picture naming from traditional psycholinguistic predictors (word length, frequency, and age of acquisition), type of aphasia (Anomic, Conduction, Wernicke, Broca, and healthy controls), and each of the network measures (layer-specific and multiplex variants) using archival data. We found that for local and meso-structural measures (i.e. degree and PageRank), the layer-specific variants were more predictive of picture naming performance than the multiplex variants. Conversely, for the global measure of closeness centrality, we found the multiplex variant being twice more predictive of picture naming performance than layer-specific variants. Furthermore, the difference in production likelihood between words with high and low multiplex closeness centrality is considerably greater for people with different types of aphasia than healthy controls, suggesting that this measure is particularly sensitive to picture naming performance in this clinical population (Fig. 1). These findings indicate that picture naming by people with aphasia crucially depends on the global interplay between phonology and semantics, which is captured by the whole multiplex structure. These findings may have particular relevance for the treatment of aphasia. Potentially, selecting words with high multiplex closeness centrality for treatment will lead to greater generalization of treatment to untrained words than when selecting words with low closeness centrality, given that words with high multiplex closeness centrality are 1) already better accessed by people with aphasia and 2) well-connected within the entire multiplex lexical network through semantic and phonological connections. Figure 1 Acknowledgements Portions of this work were made possible with a Ruth L. Kirschstein National Research Service Award (NRSA) Institutional Research Training Grant from the National Institutes of Health (National Institute on Aging) 5T32AG000175 to NC. MS acknowledges support from a Doctoral Training Centre grant (EP/G03690X/1). References Castro, N., Pelczarski, K. M., & Vitevitch, M. S. (2017). Using Network Science Measures to Predict the Lexical Decision Performance of Adults Who Stutter. Journal of Speech, Language, and Hearing Research, 60(7), 1911-1918. De Deyne, S., Navarro, D. J., & Storms, G. (2013). Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations.Behavior research methods, 45(2), 480-498. De Domenico, M., Solé-Ribalta, A., Omodei, E., Gómez, S., & Arenas, A. (2015). Ranking in interconnected multilayer networks reveals versatile nodes. Nature communications, 6, 6868. Stella, M., Beckage, N. M., & Brede, M. (2017). Multiplex lexical networks reveal patterns in early word acquisition in children.Scientific Reports, 7, 46730. Stella, M., Beckage, N. M., Brede, M., & De Domenico, M. (2018). Multiplex model of mental lexicon reveals explosive learning in humans. Scientific reports, 8(1), 2259. Vitevitch, M. S. (2008). What can graph theory tell us about word learning and lexical retrieval?. Journal of Speech, Language, and Hearing Research, 51(2), 408-422. Vitevitch, M. S., & Castro, N. (2015). Using network science in the language sciences and clinic. International journal of speech-language pathology, 17(1), 13-25. Vitevitch, M. S., Goldstein, R., Siew, C. S., & Castro, N. (2014). Using complex networks to understand the mental lexicon. In Yearbook of the Poznan Linguistic Meeting, 1(1), 119-138. Keywords: Aphasia, multiplex lexical networks, Psycholinguistics, complex networks, picture naming, clinical applications Conference: Academy of Aphasia 56th Annual Meeting, Montreal, Canada, 21 Oct - 23 Oct, 2018. Presentation Type: poster presentation Topic: not eligible for a student prize Citation: Castro N and Stella M (2019). The multiplex interplay between phonological and semantic networks impacts word production across different types of aphasia. Conference Abstract: Academy of Aphasia 56th Annual Meeting. doi: 10.3389/conf.fnhum.2018.228.00035 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 16 Apr 2018; Published Online: 22 Jan 2019. * Correspondence: Dr. Nichol Castro, Georgia Institute of Technology, Atlanta, United States, nichol.castro@psych.gatech.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Nichol Castro Massimo Stella Google Nichol Castro Massimo Stella Google Scholar Nichol Castro Massimo Stella PubMed Nichol Castro Massimo Stella Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

The COVID-19 pandemic has significantly changed the work and employment experience for employees, resulting in novel or exacerbated stressors and challenges. At the same time, worker isolation resulting from layoffs, work-from home arrangements, and social distancing policies have prompted workers to turn to online social platforms to cope with these stressors. The goal of our research is to elucidate the online social coping process. We integrated the Transactional Model of Stress and social support theories and applied computational grounded theorizing and various machine learning techniques to a large corpus of work-related conversations on Reddit to propose a microanalytic theory of online social coping process. This model sheds light on the interactive and dynamic nature of the online social coping process and shows how sharers and responders interact and react to one another depending on the content of shared stressors, the social coping strategies the sharers adopt, and whether the sharer and responder belong to the same occupational category. We contribute to the social coping literature by demonstrating the importance of considering the listener’s response to the social coping attempt and by extending the theory on social coping to the online domain.

The article points out the shortcomings in the activities of the police for the prevention of group offenses of minors. Among them are the following: prevention does not take into account the changing subject of activity of groups of juvenile offenders depending on social processes in society, as well as the changing system of communication links in these communities, the transition from real contacts between group members to virtual communication using digital technologies; prevention is focused mainly on small and unstable groups of juvenile delinquents, the specifics of communication links and the subject of criminal activity of stable criminal groups are not taken into account; police bodies do not interact enough with other subjects of general and special prevention of juvenile delinquency, primarily in terms of information exchange; police activities are focused mainly on supervising the activities of members of groups consisting of on preventive accounting; low activity of police officers to identify adults who involve underage members of groups in committing crimes and antisocial actions. These shortcomings in the activities of the police predetermined the relevant proposals to improve the prevention of group crimes of minors, which include the following. 1. Police officers should take into account the subject of activity of groups of juvenile offenders changing under the influence of social processes in society in order to determine the priorities of preventive impact. 2. The police should be focused not only on working with ordinary groups of juvenile offenders (unstable and small in number), but also with stable criminal groups that are focused mainly on committing mercenary crimes and that are resistant to preventive effects. 3. Police bodies should interact more intensively with other subjects of general and special prevention of juvenile delinquency, primarily in terms of information exchange. This allows the police to more fully present the properties of groups of juvenile offenders who are an independent and specific object of prevention, to implement preventive measures agreed with these subjects. 4. The activities of the police should not be limited to registering groups of juvenile offenders, supervising their participants who are on preventive registration, and conducting preventive conversations with them. It is necessary to use all forms of preventive influence provided for by Article 17 of Federal Law No. 182-FZ of June 23, 2016 "On the basics of the system of crime prevention in the Russian Federation" within the limits of their powers. 5. Police officers need to step up their activities to identify and bring to criminal responsibility adults who involve underage members of groups in committing crimes and anti-social actions.