Objective: The study aims to build a comprehensive network structure of psychopathology based on patient narratives by combining the merits of both qualitative and quantitative research methodologies. Research methods: The study web-scraped data from 10,933 people who disclosed a prior DSM/ICD11 diagnosed mental illness when discussing their lived experiences of mental ill health. The study then used Python 3 and its associated libraries to run network analyses and generate a network graph. Key findings: The results of the study revealed 672 unique experiences or symptoms that generated 30023 links or connections. The study also identified that of all 672 reported experiences/symptoms, five were deemed the most influential; “anxiety,” “fear,” “auditory hallucinations,” “sadness,” and “depressed mood and loss of interest.” Additionally, the study uncovered some unusual connections between the reported experiences/symptoms. Discussion and recommendations: The study demonstrates that applying a quantitative analytical framework to qualitative data at scale is a useful approach for understanding the nuances of psychopathological experiences that may be missed in studies relying solely on either a qualitative or a quantitative survey-based approach. The study discusses the clinical implications of its results and makes recommendations for potential future directions.

This study aims to explore the dependencies on the cryptocurrency market using social network tools. We focus on the correlations observed in the cryptocurrency returns. Based on the sample of cryptocurrencies listed between January 2015 and December 2022 we examine which cryptos are central to the overall market and how often major players change. Static network analysis based on the whole sample shows that the network consists of several communities strongly connected and central, as well as a few that are disconnected and peripheral. Such a structure of the network implies high systemic risk. The day-by-day snapshots show that the network evolves rapidly. We construct the ranking of major cryptos based on centrality measures utilizing the TOPSIS method. We find that when single measures are considered, Bitcoin seems to have lost its first-mover advantage in late 2016. However, in the overall ranking, it still appears among the top positions. The collapse of any of the cryptocurrencies from the top of the rankings poses a serious threat to the entire market.

Previous studies show aggression-related structural alterations in frontal and limbic brain regions. Most studies have focused on overall aggression, instead of its subtypes, and on specific regions instead of networks. This study aims to identify both brain networks and regions that are associated with reactive and proactive subtypes of aggression. Structural MRI data were collected from 340 adolescents (125 F/215 M) with a mean age of 16.29 (SD = 1.20). Aggression symptomology was indexed via the Reactive Proactive Aggression Questionnaire (RPQ). Freesurfer was used to estimate Cortical Volume (CV) from seven networks and regions within specific networks associated with aggression. Two multivariate analyses of covariance (MANCOVAs) were conducted on groups for low versus higher reactive and proactive RPQ scores. Our reactive aggression MANCOVA showed a main effect in CV [F(14,321) = 1.935, p = 0.022,ηp2 = 0.078] across all the 7-Networks. Unpacking this main effect revealed significant volumetric differences in the right Limbic Network (LN) (p = 0.029) and the Temporal Pole (p = 0.011), where adolescents in the higher reactive aggression group showed higher cortical volumes. Such findings are consistent with region/voxel-specific analyses that have associated atypical structure within the LN and reactive aggression. Moreover, the temporal pole is highly interconnected with regions important in the regulation and initiation of reactive aggression.

Japan is the world’s largest producer of love simulation games, revealing a curious feature: these games, in theory, assign female players to the unique task of seducing a male character, but, in reality, they promote the establishment of a network of friendship between women. Love cannot be achieved if this network is not carefully woven both in play and in real life. Based on the analysis of this double dynamics, outwardly contradictory, I would like to advance the following hypothesis: that such games enable their users to ‘outsmart’ gender expectations. These games, called otome games, became popular in the context of a national panic related to the declining birthrate: they target the market of women who – living alone or with their parents – are held responsible for the future shortfall of the system. These new generations of women don’t start a family. They have no children. How do they manage to ward off exclusion and stigma? The study will focus on the strategies collectively devised to turn otome games into an identity-building tool, promoting friendship between players as a means of resistance against social norms.

The social organization of the Chinese diaspora in Malaysia has emerged as a very diversified phenomenon so that it is hard to speak of a coherent social and cultural community. Starting from the case of George Town (Penang), a port city once part of the British Empire and subsequently incorporated in present-day Malaysia, the article will illustrate the various forms of social organization developed by the Chinese in the longue durée. The analysis of the Chinese diaspora in George Town (Penang) based on long-term fieldwork helps to draw attention especially to its internal tensions, rivalries and even open and at times enduring conflicts. Through the notions of network and corporate group, distinctive of the Manchester school, by means of a dynamic analysis, thus mindful of specific historical processes, this article will examine the underlying modalities of organizational changes that occurred in this diasporic society within the colonial and national societies. Thus, the article avoids an essentialist vision based on a uniformity and cultural unity of these immigrant communities.

This essay explores the organisational character of Facebook's Libra currency by undertaking a critical reading of documents published by the Libra Association. Drawing on the conceptual work of Marilyn Strathern and Michel Serres, it illustrates how ownership cuts the network and encourages parasitism as a means of driving future profit. Central to this is the claim that Libra is not an exercise in democratising money, but rather, the opposite: Libra is run as a club, for the benefit of club members. The conceptual theme of ‘cutting’ is used to organise the argument. Rather than a cutting-edge technology, Libra's true innovation is organisational and consists in overturning the decentralised character of blockchain, such that distributed ledger technology is re-centralised by big tech firms. Outsiders are thus cut-off from Libra; only those inside the club have the right to participate in Libra and its governance. This position also affords members an exclusive capacity to take a cut of the profits generated through Libra. As a private organisation, members have sole rights to future profits generated from the Libra ecosystem and are in this way incentivised to create new product opportunities over time.

This paper examines the added-value that multisystem approaches bring to research and intervention in contexts of war and forced displacement. I highlight what is useful and truly innovative about systems-level work, aware that providing data-related evidence is only part of the story when connecting research to policy and practice. I discuss four types of added-value: these are conceptual, instrumental, capacity-building, and connectivity impacts that, respectively, aim to change current knowledge, improve implementation, build research skills, and strengthen network connectivity. Specifically, systems-based research can help transform the key frames of humanitarian work, fostering the more integrated and distributive models of professional assistance known as resilience and network humanitarianism. I argue that systems-level approaches on resilience and flourishing in war-affected and refugee populations help to articulate new mindsets, methodologies, partnerships, and ways of working relevant for humanitarian research, policy and practice. I focus attention on interdisciplinary, interventionist, prospective, transgenerational, and network-building initiatives. My specific examples cover the family context of mental health and trauma memory in Afghanistan, as well as program evaluation with Syrian refugees in Jordan, connecting stress biology to human experience, and social networks to psychological empowerment. The paper suggests future directions to support more effective and impactful systems-level work in protracted humanitarian crises.

SARS-CoV-2 rapidly spreads among humans via social networks, with social mixing and network characteristics potentially facilitating transmission. However, limited data on topological structural features has hindered in-depth studies. Existing research is based on snapshot analyses, preventing temporal investigations of network changes. Comparing network characteristics over time offers additional insights into transmission dynamics. We examined confirmed COVID-19 patients from an eastern Chinese province, analyzing social mixing and network characteristics using transmission network topology before and after widespread interventions. Between the two time periods, the percentage of singleton networks increased from 38.9$ \% $ to 62.8$ \% $$ (p<0.001) $; the average shortest path length decreased from 1.53 to 1.14 $ (p<0.001) $; the average betweenness reduced from 0.65 to 0.11$ (p<0.001) $; the average cluster size dropped from 4.05 to 2.72 $ (p=0.004) $; and the out-degree had a slight but nonsignificant decline from 0.75 to 0.63 $ (p=0.099). $ Results show that nonpharmaceutical interventions effectively disrupted transmission networks, preventing further disease spread. Additionally, we found that the networks’ dynamic structure provided more information than solely examining infection curves after applying descriptive and agent-based modeling approaches. In summary, we investigated social mixing and network characteristics of COVID-19 patients during different pandemic stages, revealing transmission network heterogeneities.