Prediction of influential nodes in social networks based on local communities and users' reaction information.

Identifying influential nodes is one of the basic issues in managing large social networks. Identifying influence nodes in social networks and other networks, including transportation, can be effective in applications such as identifying the sources of spreading rumors, making advertisements more effective, predicting traffic, predicting diseases, etc. Therefore, it will be important to identify these people and nodes in social networks from different aspects. In this article, a new method is presented to identify influential nodes in the social network. The proposed method utilizes the combination of users' social characteristics and their reaction information to identify influential users. Since the identification of these users in the large social network is a complex process and requires high processing power and time, clustering and identifying communities have been used in the proposed method to reduce the complexity of the problem. In the proposed method, the structure of the social network is divided into its constituent communities and thus the problem of identifying influential nodes (in the entire network) turns into several problems of identifying an influential node (in each community). The suggested method for predicting the nodes first predicts the links that may be created in the future and then identifies the influential nodes based on an iterative strategy. The proposed algorithm uses the criteria of centrality and influence domain to identify this category of users and performs the identification process both at the community and network levels. The efficiency of the method has been evaluated using real databases and the results have been compared with previous works. The results demonstrate that the proposed method provides a more suitable performance in detecting the influential nodes and is superior in terms of accuracy, recall and processing time.

The influence of service performance in China's sci-tech commissioner system: Using social network analysis and interpretable machine learning.

The Sci-Tech Commissioner System (SCS) is a result of exploratory efforts by the Chinese government to use science and technology to strengthen the agricultural sector. Social network analysis (SNA) and machine learning (ML) techniques make it feasible to assess the service performance in China's SCS by using indicators such as group types and structure features. In this study, SNA and a clustering algorithm were employed to categorize service group types of sci-tech commissioners. By comparing the accuracy of different classification algorithms in predicting the clustering results, LightGBM algorithm was finally select to determine the clustering features of sci-tech commissioners and establish an interpretable ML model. Then, the SHAP was used to algorithm to analyze influences affecting service performance. Results show that the service forms of sci-tech commissioners are group-oriented, and that group types include small groups of young commissioners with close cooperation, larger groups of young and middle-aged commissioners, small groups of middle-aged and old commissioners with close cooperation, and isolated points of highly-influential commissioners. Furthermore, while group size is not the determinant of a commissioner's average performance, group structure and coordination ability were found to be more critical. Moreover, while differences in distinct types of service performance are caused by various factors, but good group structures and extensive social contacts are essential for high service performance.

Using GPS-defined venue-based affiliation networks among Black sexually minoritized men and transgender women to identify locations for HIV prevention interventions.

PURPOSE: HIV biomedical intervention uptake is suboptimal among Black sexually minoritized men (SMM) and transgender women (TW). Venues where people meet and interact shape HIV-related risk and prevention behaviors. We aimed to construct GPS-defined venue-based affiliation networks and identify the unique set of venues that could maximize reach of HIV biomedical interventions among Black SMM and TW. METHODS: We used baseline survey and GPS data from 272 Black SMM and TW in the Neighborhoods and Networks (N2) Cohort Study in Chicago, Illinois (2018-2019). We mapped participants' GPS data to the nearest pre-identified SMM- and TW-friendly venue (n = 222) to construct affiliation networks. Network analyses were performed to identify influential venues that can yield high reach to intervention candidates. RESULTS: Participants were affiliated with 75.5 % of all pre-identified venues based on GPS data. Two influential venues were identified in the non-PrEP use network, which when combined, could reach 52.5 % of participants not taking PrEP. Participants that could be reached through these two influential venues reported more non-main sex partners than participants not affiliated with either venue (p = 0.049). CONCLUSION: We demonstrate a potential for GPS-defined venue-based affiliation networks to identify unique combinations of venues that could maximize the impact of HIV prevention interventions.

Issues Related to the Use of Visual Social Networks and Perceived Usefulness of Social Media Literacy During the Recovery Phase: Qualitative Research Among Girls With Eating Disorders.

BACKGROUND: The patient-centered approach is essential for quality health care and patient safety. Understanding the service user's perspective on the factors maintaining the health problem is crucial for successful treatment, especially for patients who do not recognize their condition as clinically relevant or concerning. Despite the association between intensive use of visual social media and body dissatisfaction and eating disorders, little is known about the meanings users assign to posting or searching for edited photos and the strategies they use to protect themselves from digital risks. OBJECTIVE: This study aims to examine how young women recovering from eating disorders in Northern Italy perceive the health risks and potential benefits associated with visual social networks (ie, Instagram and Snapchat). The literature has found these platforms to be detrimental to online body comparisons. It also explores the perceived usefulness, willingness, and personal interest in coconstructing social media literacy programs with girls recovering from eating disorders. METHODS: A total of 30 semistructured interviews were conducted with adolescent girls aged 14-17 years at the end of their treatment for eating disorders. The following areas of research were addressed: (1) the meanings associated with the use of Instagram and Snapchat; (2) the investment in the photographic dimension and feedback; (3) the impact of visual social networks on body experiences; (4) the potential and risks perceived in their use; (5) the importance of supporting girls undergoing treatment for eating disorders in using social networks; and (6) the usefulness and willingness to co-design social network literacy programs. Content analysis was applied. RESULTS: A total of 7 main contents emerged: active or passive role in using social networks, the impact of online interactions on body image, investment in the photographic dimension, effects on self-representation, perceived risks, self-protective strategies, and potential benefits. The findings highlight a strong awareness of the processes that trigger body comparisons in the virtual context, creating insecurity and worsening the relationship with oneself. The self-protective behaviors identified are the development of critical thinking, the avoidance of sensitive content, increased control over social networking site use, and a certain skepticism toward developing antagonistic ideologies. All these topics were considered fundamental. CONCLUSIONS: The findings provide important insights for health professionals working with youth in preparing media literacy programs. These programs aim to reduce potential risks and amplify the positive effects of online resources. They underscore the importance of addressing this issue during hospitalization to develop skills and critical thinking aimed at changing small habits that perpetuate the problem in everyday life. The inherent limitations in current service practices, which may not adequately address individual needs or impact posttreatment life, must also be considered.

Applying Social Network Theory to Vaping in High School: Implications for Person-Centered Intervention.

BACKGROUND: Peer influence on risky behavior is particularly potent in adolescence and varies by gender. Smoking prevention programs focused on peer-group leaders have shown great promise, and a social influence model has proven effective in understanding adult smoking networks but has not been applied to adolescent vaping until 2023. This work aims to apply a social influence model to analyze vaping by gender in a high school network. METHODS: A high school's student body was emailed an online survey asking for gender, age, grade level, vape status, and the names of three friends. Custom Java and MATLAB scripts were written to create a directed graph, compute centrality measures, and perform Fisher's exact tests to compare centrality measures by demographic variables and vape status. RESULTS: Of 192 students in the school, 102 students responded. Students who vape were in closer-knit friend groups than students who do not vape (p < .05). Compared to males who vape, females who vape had more social ties to other students who vape, exhibiting greater homophily (p < .01). Compared to females who do not vape, females who vape were in closer-knit friend groups (p < .05) and had more ties to other students who vape (p < .01). CONCLUSION: Differences in vaping by social connectedness and gender necessitate school and state policies incorporating the social aspect of vaping in public health initiatives. Large-scale research should determine if trends can be generalized across student bodies, and more granular studies should investigate differences in motivations and social influence by demographic variables to individualize cessation strategies.

Determining multidimensional influences of network heterogeneity on university students' psychological and academic well-being: The mediating role of social network exhaustion.

Mobile social media has become indispensable to university students' communication with various socio-demographic populations, exposing them to diverse social networks and augmenting their network heterogeneity. Although the psychological ramifications of network heterogeneity have been extensively examined, its correlated academic outcomes remain inconclusive. The current study formulated an integrated theoretical research model based on the stressor-stress-outcome framework to investigate the influence of factors associated with network heterogeneity (specifically, privacy invasion, social comparison, self-presentation, and excessive WeChat use) on social media exhaustion, psychological well-being, and academic well-being among university students. Furthermore, the research examined the mediating effect of social network exhaustion among network heterogeneity, psychological well-being, and academic well-being. A cross-sectional survey of 1128 WeChat users revealed that social comparison and excessive WeChat use had positive associations with social network exhaustion, while privacy invasion and self-presentation were negatively correlated with social network exhaustion. Additionally, social network exhaustion was negatively correlated with psychological well-being and academic well-being. Furthermore, social network exhaustion mediated the influences of network heterogeneity on psychological well-being and academic well-being. These obtained results could contribute to a more nuanced understanding of the underlying causes of social network exhaustion and the multifaceted effects of network heterogeneity. These insights may prove valuable for practitioners to enhance university students' psychological states and academic performance in the contemporary mobile media-saturated environment.

Social integration and long-term physical and psychosocial quality of life among prostate cancer survivors in the Health Professionals Follow-up Study.

PURPOSE: Prostate cancer survivors may benefit from a supportive social environment. We investigated associations of social integration and long-term physical and psychosocial quality of life among prostate cancer survivors who were participants in the Health Professionals Follow-up Study. METHODS: We included 1,428 individuals diagnosed with non-metastatic prostate cancer between 2008 and 2016. Social integration was measured by the Berkman-Syme Social Network Index (SNI) and marital status. We fit generalized linear mixed effect models for associations of SNI and marital status with patient reported outcome measures on physical and psychosocial quality of life captured between 2008 and 2020, adjusting for age, race, employment status, body mass index, comorbidities, smoking history, and clinical factors. RESULTS: Among those with baseline SNI (N = 1,362), 46.4% were socially integrated, 20.3% were moderately integrated, 27.4% were moderately isolated, and 5.9% were socially isolated. Among those reporting baseline marital status (N = 1,428), 89.5% were married. Socially integrated survivors (vs. socially isolated) reported fewer depressive signs and better psychosocial wellbeing. Physical quality of life did not differ by social integration. Married survivors (vs. not married) reported fewer urinary symptoms, but there were no differences in bowel, sexual, or vitality/hormonal symptoms. CONCLUSIONS: Among prostate cancer survivors, being socially integrated was associated with fewer depressive signs and better psychosocial wellbeing, and married prostate cancer survivors had fewer urinary symptoms. IMPLICATIONS FOR CANCER SURVIVORS: This study highlighted aspects of long-term physical and psychosocial quality of life that are more favorable among prostate cancer survivors with a supportive social environment.

Evidence-based practice in traditional persian medicine (TPM): a stakeholder and social network analysis.

BACKGROUND: The utilization of complementary and alternative medicine (CAM) is experiencing a global surge, accompanied by the adoption of national CAM policies in numerous countries. Traditional Persian medicine (TPM) is highly used as CAM in Iran, and the ongoing scientific evaluation of its interventions and the implementation of evidence-based medicine (EBM) encounters various barriers. Therefore, comprehending the characteristics and interactions of stakeholders is pivotal in advancing EBM within TPM policies. In this study, we utilized both classical stakeholder analysis and social network analysis to identify key stakeholders and potential communication patterns, thereby promoting EBM in TPM policy-making. METHODS: A cross-sectional nationwide stakeholder analysis was conducted in 2023 using snowball sampling. The interviews were carried out using a customized version of the six building blocks of health. Data were collected through semi-structured interviews. Stakeholders were assessed based on five factors (power, interest, influence, position, and competency). The connections and structure of the network were analyzed using degree, betweenness, closeness centrality, and modularity index to detect clusters of smaller networks. RESULTS: Among twenty-three identified stakeholders, the Ministry of Health and Medical Education (MOHME) and the Public were the most powerful and influential. The Iranian Academy of Medical Sciences was the most competent stakeholder. Social network analysis revealed a low density of connections among stakeholders. Pharmaceutical companies were identified as key connectors in the network, while the Public, supreme governmental bodies, and guilds acted as gatekeepers or brokers. The MOHME and Maraji were found to be high-ranking stakeholders based on four different centrality measures. CONCLUSION: This study identifies powerful stakeholders in the network and emphasizes the need to engage uninterested yet significant stakeholders. Recommendations include improving competence through education, strengthening international relations, and fostering stronger relationships. Engaging key connectors and gatekeepers is essential for bridging gaps in the network.

Do Adolescents Adopt the Prosocial Behaviors of the Classmates They Like? A Social Network Analysis on Prosocial Contagion.

While the influence of high-status peers on maladaptive behaviors is well-documented, socialization processes of prosocial behavior through high-status peers remain understudied. This study examined whether adolescents' prosocial behavior was influenced by the prosocial behavior of the peers they liked and whether this effect was stronger when the peers they liked were also well-liked by their classmates. Three waves of data, six months apart, were collected among Chilean early adolescents who completed peer nominations and ratings at Time 1 (n = 294, Mage = 13.29, SD = 0.62; 55.1% male), Time 2 (n = 282), and Time 3 (n = 275). Longitudinal social network analyses showed that adolescents adopted the prosocial behavior of the classmates they liked - especially if these classmates were well-liked by peers in general. In addition, adolescents low in likeability were more susceptible to this influence than adolescents high in likeability. The influence resulted both in increases and - especially - decreases in prosocial behavior, depending on the level of prosociality of the liked peer. Findings suggest that likeability represents an important aspect of peer status that may be crucial for understanding the significance of peer influence with respect to prosocial behaviors during adolescence. Pre-Registration: https://osf.io/u4pxm .

Exploring stroke discourse on Twitter through content and network analysis among Indian users.

The study aimed to understand stroke-related Twitter conversations in India, focusing on topics, message sources, reach, and influential users to provide insights to stakeholders regarding community needs for knowledge, support, and interventions. Geo-tagged Twitter posts focusing on stroke originating from India and, spanning from November 7, 2022, to February 28, 2023, were systematically obtained via the Twitter application programming interface, using keywords and hashtags sourced through Symplur Signals. Preprocessing involved the removal of hashtags, stop words, and URLs. The Latent Dirichlet Allocation (LDA) topic model was used to identify recurring stroke-related topics, while influential users were identified through social network analysis. About half of the tweets about stroke in India were about seeking support and post-stroke bereavement sharing and had the highest reachability. Four out of 10 tweets were from the individual twitter users. Tweets on the topic risk factors, awareness and prevention (14.6%) constituted the least proportion, whereas the topic management, research, and promotion had the least retweet ratio. Twitter demonstrates significant potential as a platform for both disseminating and acquiring stroke-related information within the Indian context. The identified topics and understanding of the content of discussion offer valuable resources to public health professionals and organizations to develop targeted educational and engagement strategies for the relevant audience.

Feeling phony online - The impostor phenomenon's link to online self-presentation, self-esteem, and social network site use.

This study examined the relationship between the impostor phenomenon, self-esteem, online self-presentation, and social network site usage across Instagram, Facebook, TikTok, LinkedIn, and Tinder. The sample consisted of n = 541 individuals (46 % men; Mage = 27, SDage = 8.5). In addition to demographics, quantitative social network site use metrics, and self-esteem, the impostor expression emerged as an incremental predictor for the online self-presentation facets adaptable self (ß = 0.26, p < .001), authentic self (ß = -0.29, p < .001) and freedom of self online (ß = 0.25, p < .001). Self-esteem partially mediated the impostor expression's effect on the authentic self. Findings suggest that a high impostor expression links to lower online authenticity, higher online self-adaption, and a preference for online communication and self-presentation.

Body Size Perceptions Associated with Body Mass Index and Weight Loss Intentions Among Two Immigrant Populations.

BACKGROUND: The rates of obesity among immigrant populations within the USA rise with increasing duration of residency. The aims of this study were to examine weight self-perception and body image discrepancy within a large community sample of Hispanic and Somali predominantly immigrant adults. METHODS: Utilizing a community-based participatory research (CBPR) approach to collect survey data from a sample of adults who self-identified as Hispanic, Latino, or Somali in Southeast Minnesota. Correlations among actual body mass index (BMI), perceived weight category, and perceived body size were assessed with Spearman rank correlation coefficients. Associations of weight loss intentions with actual BMI, perceived weight category, perceived body size, and body image discrepancy were assessed using Kruskal-Wallis nonparametric tests. RESULTS: A total of 1256 adults completed the survey and biometric measurements (610 Hispanic, 646 Somali); 81% (457) and 50% (328) had a BMI in the overweight or obese category in the Hispanic and Somali cohorts, respectively. Among participants with a BMI of > 25, more participants reported a perceived body size that was overweight or obese than a perceived weight category that was in the overweight or obese category (79% vs. 48%, p = < 0.0001). Body image discrepancy, but not actual BMI, was associated with weight loss intentions for both groups. Perceived body size and perceived weight category were associated with weight loss intentions for Hispanic participants only. CONCLUSIONS: Perceived body size is a more accurate self-report proxy of BMI-defined weight status compared with the perceived weight category among Hispanic and Somali immigrant groups. Body image discrepancy may be more predictive of weight loss intentions than actual BMI.

Seeing the teacher through my peers' eyes? A social network study on adolescents' teaching quality perceptions.

BACKGROUND: Prior research has documented the pervasive influence that peers can exert on adolescents' lives. However, knowledge on whether adolescents' perceptions of the quality of the teacher's instruction are also prone to peer influences is lacking. METHOD: This study (N = 248 German adolescents) used longitudinal social network analysis to investigate whether (a) friends become more similar in their teaching quality perceptions (influence effects) and/or whether (b) students with initially more similar perceptions of teaching quality were more likely to become friends (selection effects). We also explored whether (c) students with more positive teaching quality perceptions were better integrated socially. RESULTS: We did not find support for influence or selection effects. However, students who rated their teacher's instruction more positively were better integrated socially. CONCLUSIONS: Our work adds to research on the role of peers in adolescence and enhances our understanding of peer influences on students' perceptions of instruction.

Diversity in invasive species management networks.

Effective management of invasive species requires collaboration across a range of stakeholders. These stakeholders exhibit diverse attributes such as organisation types, operational scale, objectives, and roles within projects. Identifying the diverse attributes of stakeholders is beneficial for increasing collaboration success while minimising potential conflicts among multiple stakeholders when managing invasive species across landscapes. Despite the increasing number of studies on connections among stakeholders, there is little understanding of the diverse attributes of stakeholders involved in invasive species management. This is a notable gap because the diversity of stakeholders is one of the significant factors that can influence collaboration success. To bridge this knowledge gap, we used a social network approach to identify the attributes of stakeholders that influence their participation in collaborations using a case study of invasive wild pig (Sus scrofa) management in Queensland, Australia. Our findings suggest that even though the overall stakeholder network was diverse, the stakeholder network at the project level exhibited a lack of diversity on average, particularly regarding the scale of operation and type of organisation. In other words, stakeholders are highly likely to form ties in projects involving other stakeholders from similar types of organisations or operational scales. We suggest that targeting a greater diversity of stakeholders across types of organisations and scales of operations might enhance the success of collaborative invasive species management.

The association of social networks and depression in community-dwelling older adults: a systematic review.

BACKGROUND AND OBJECTIVE: Depression is a globally prevalent mental condition, particularly among older adults. Previous research has identified that social networks have a buffering effect on depression. Existing systematic reviews have either limited their research to specific geographic areas or provided evidence from over a decade ago. The vast body of recent literature particularly from the last decade emphasizes the need for a comprehensive review. This systematic review aims to analyze the association of structural aspects of social networks and depression in older adults. METHODS: The electronic databases APA PsycINFO, ProQuest, PSYINDEX, PubMed, Scopus, SocINDEX, and Web of Science were searched from date of data base inception until 11 July 2023. Studies were eligible for inclusion if they reported on community-dwelling older adults (defined as a mean age of at least 60 years old), had an acceptable definition for depression, referred to the term social network in the abstract, and were published in English. Quality was appraised using the Newcastle Ottawa Scale for cross-sectional and longitudinal studies. Outcome data were extracted independently from each study and analyzed by direction of the relationship, social network domain and cross-sectional or longitudinal study design. RESULTS: In total, 127 studies were included. The study categorizes structural network aspects into seven domains and finds that larger and more diverse networks, along with closer social ties, help mitigate depression. The literature on the relationships between depression and network density, homogeneity, and geographical proximity is scarce and inconclusive. DISCUSSION AND IMPLICATIONS: Despite inconsistent findings, this review highlights the importance of quantifying complex social relations of older adults. Limitations of this review include publication and language bias as well as the exclusion of qualitative research. Further research should use longitudinal approaches to further investigate the reciprocal relationship between social networks and depression. Following this review, interventions should promote the integration of older adults in larger and more diverse social settings. Other: This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant [454899704]. This systematic review was pre-registered. The review-protocol can be accessed at https://doi.org/10.17605/OSF.IO/6QDPK .

Face recognition's practical relevance: Social bonds, not social butterflies.

Research on individual differences in face recognition has provided important foundational insights: their broad range, cognitive specificity, strong heritability, and resilience to change. Elusive, however, has been the key issue of practical relevance: do these individual differences correlate with aspects of life that go beyond the recognition of faces, per se? Though often assumed, especially in social realms, such correlates remain largely theoretical, without empirical support. Here, we investigate an array of potential social correlates of face recognition. We establish social relationship quality as a reproducible correlate. This link generalises across face recognition tasks and across independent samples. In contrast, we detect no robust association with the sheer quantity of social connections, whether measured directly via number of social contacts or indirectly via extraversion-related personality indices. These findings document the existence of a key social correlate of face recognition and provide some of the first evidence to support its practical relevance. At the same time, they challenge the naive assumption that face recognition relates equally to all social outcomes. In contrast, they suggest a focused link of face recognition to the quality, not quantity, of one's social connections.

Detecting and Understanding Social Influence During Drinking Situations: Protocol for a Bluetooth-Based Sensor Feasibility and Acceptability Study.

BACKGROUND: High-risk alcohol consumption among young adults frequently occurs in the presence of peers who are also drinking. A high-risk drinking situation may consist of particular social network members who have a primary association with drinking. Fine-grained approaches such as ecological momentary assessment (EMA) are growing in popularity for studying real-time social influence, but studies using these approaches exclusively rely on participant self-report. Passive indicators of peer presence using Bluetooth-based technology to detect real-time interactions have the potential to assist in the development of just-in-time interventions. OBJECTIVE: This study seeks to examine the feasibility and acceptability of using a Bluetooth-based sensor and smartphone app to measure social contact in real-world drinking situations. METHODS: Young adults (N=20) who drink heavily and report social drinking will be recruited from the community to participate in a 3-week EMA study. Using a social network interview, index participants will identify and recruit 3 of their friends to carry a Bluetooth beacon. Participants will complete a series of EMA reports on their own personal Android devices including random reports; morning reports; first-drink reports; and signal-contingent reports, which are triggered following the detection of a beacon carried by a peer participant. EMA will assess alcohol use and characteristics of the social environment, including who is nearby and who is drinking. For items about peer proximity and peer drinking, a customized peer list will be presented to participants. Feedback about the study protocol will be ascertained through weekly contact with both index and peer participants, followed by a qualitative interview at the end of the study. We will examine the feasibility and acceptability of recruitment, enrollment of participants and peers, and retention. Feasibility will be determined using indexes of eligibility, enrollment, and recruitment. Acceptability will be determined through participant enrollment and retention, protocol compliance, and participant-reported measures of acceptability. Feasibility and acceptability for peer participants will be informed by enrollment rates, latency to enrollment, compliance with carrying the beacon, and self-reported reasons for compliance or noncompliance with beacon procedures. Finally, EMA data about peer proximity and peer drinking will support the validity of the peer selection process. RESULTS: Participant recruitment began in February 2023, and enrollment was completed in December 2023. Results will be reported in 2025. CONCLUSIONS: The protocol allows us to examine the feasibility and acceptability of a Bluetooth-based sensor for the detection of social contact between index participants and their friends, including social interactions during real-world drinking situations. Data from this study will inform just-in-time adaptive interventions seeking to address drinking in the natural environment by providing personalized feedback about a high-risk social context and alerting an individual that they are in a potentially unsafe situation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50650.

Quantifying relational change in community organisations participating in a Veteran suicide prevention learning collaborative: a social network analysis.

BACKGROUND: Veteran suicide remains a significant issue, as 17.5 Veterans die by suicide each day. The US Department of Veteran Affairs (VA) has implemented a robust suicide prevention program within its integrated behavioural health system. Further, the VA has increasingly contributed to suicide prevention in community settings, where a large proportion of Veterans receive health care and social services. One component integral to preventing suicide among Veterans receiving community services is ensuring that organisations are equipped with the latest evidence-based Veteran-specific suicide prevention strategies. METHODS: The Patient Safety Center of Inquiry-Suicide Prevention Collaborative piloted a Veteran suicide prevention learning collaborative in the Denver/Colorado Springs, CO region, spanning 16 months as a multimodal initiative to integrate community organisations and assist them in implementing Veteran suicide prevention strategies used within VA. Agencies completed social network analysis surveys at baseline (T1), year 1 (T2) and 16 months (T3) to examine social networks, partnerships and collaborations among community organisations and the VA over time. RESULTS: The quantity of learning collaborative relationships increased from 30 at T1 to 41 at T3 while the quality of relationships deepened over time from awareness and cooperative to more coordinated and integrated. CONCLUSION: Improvement in relationship quantity and quality facilitates community organisation engagement in collaborating to strengthen their Veteran suicide prevention programming. Learning collaboratives work with the individual organisation for intraorganisational facilitation of implementing suicide prevention strategies and engage and enhance interorganisational partnerships. This multimodal intervention can engage community organisations and provide a stronger safety net for Veterans at risk for suicide.

Unveiling Influence in Networks: A Novel Centrality Metric and Comparative Analysis through Graph-Based Models.

Identifying influential actors within social networks is pivotal for optimizing information flow and mitigating the spread of both rumors and viruses. Several methods have emerged to pinpoint these influential entities in networks, represented as graphs. In these graphs, nodes correspond to individuals and edges indicate their connections. This study focuses on centrality measures, prized for their straightforwardness and effectiveness. We divide structural centrality into two categories: local, considering a node's immediate vicinity, and global, accounting for overarching path structures. Some techniques blend both centralities to highlight nodes influential at both micro and macro levels. Our paper presents a novel centrality measure, accentuating node degree and incorporating the network's broader features, especially paths of different lengths. Through Spearman and Pearson correlations tested on seven standard datasets, our method proves its merit against traditional centrality measures. Additionally, we employ the susceptible-infected-recovered (SIR) model, portraying virus spread, to further validate our approach. The ultimate influential node is gauged by its capacity to infect the most nodes during the SIR model's progression. Our results indicate a notable correlative efficacy across various real-world networks relative to other centrality metrics.

Using a Combination of Novel Research Tools to Understand Social Interaction in the Drosophila melanogaster Model for Fragile X Syndrome.

Fragile X syndrome (FXS), the most common monogenic cause of inherited intellectual disability and autism spectrum disorder, is caused by a full mutation (>200 CGG repeats) in the Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene. Individuals with FXS experience various challenges related to social interaction (SI). Animal models, such as the Drosophila melanogaster model for FXS where the only ortholog of human FMR1 (dFMR1) is mutated, have played a crucial role in the understanding of FXS. The aim of this study was to investigate SI in the dFMR1B55 mutants (the groups of flies of both sexes simultaneously) using the novel Drosophila Shallow Chamber and a Python data processing pipeline based on social network analysis (SNA). In comparison with wild-type flies (w1118), SNA analysis in dFMR1B55 mutants revealed hypoactivity, fewer connections in their networks, longer interaction duration, a lower ability to transmit information efficiently, fewer alternative pathways for information transmission, a higher variability in the number of interactions they achieved, and flies tended to stay near the boundaries of the testing chamber. These observed alterations indicate the presence of characteristic strain-dependent social networks in dFMR1B55 flies, commonly referred to as the group phenotype. Finally, combining novel research tools is a valuable method for SI research in fruit flies.