scholarly journals Novel Influence Maximization Algorithm for Social Network Behavior Management

2021 ◽  
Vol 3 (1) ◽  
pp. 60-68
Author(s):  
Sivaganesan D
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Behavior ◽  
Social Action ◽  
Behavior Management ◽  
Network Size ◽  
Influence Maximization ◽  
Interactive Behavior ◽  
Social Network Size ◽  
The Social

The users largely contributing towards product adoption or information utilization in social networks are identified by the process of influence maximization. The exponential growth in social networks imposes several challenges in the analyses of these networks. Important has been given to modeling structural properties while the relationship between users and their social behavior has being ignored in the existing literature. With respect to the social behavior, the influence maximization task has been parallelized in this paper. In order to maximize the influence in social networks, an interest based algorithm with parallel social action has been proposed. This is algorithm enables identifying influential users in social network. The interactive behavior of the user is weighted dynamically as social actions along with the interests of the users. These two semantic metrics are used in the proposed algorithm. An optimal influential nodes set is computed by implementing the machines with CPU architecture with perfect parallelism through community structure. This helps in reducing the execution time and overcoming the real-word social network size challenges. When compared to the existing schemes, the proposed algorithm offers improved efficiency in the calculation speed on real world networks.

scholarly journals Associations Between Social Support, Social Networks, and Financial Exploitation in Older Adults

2016 ◽  
Vol 37 (8) ◽  
pp. 990-1011 ◽  
Author(s):  
Scott R. Beach ◽  
Richard Schulz ◽  
Rodlescia Sneed
Keyword(s):  
Social Support ◽  
Older Adults ◽  
Social Networks ◽  
Social Network ◽  
Perceived Social Support ◽  
Population Based ◽  
Network Size ◽  
Social Network Size ◽  
Financial Exploitation ◽  
The Social

Social support and social networks are important correlates of elder mistreatment. This study tests hypothesized associations between perceived social support, social network size, and financial exploitation (FE). A population-based survey of 903 older adults (60+) in Allegheny County (Pittsburgh, Pennsylvania) found that lower perceived social support and larger social networks were simultaneously associated with higher risk for FE since age 60, controlling for known risk factors. The same associations were found for FE in the last 6 months. Older adults with larger social networks combined with lower perceived social support were most likely to report FE. When it comes to the role of social relationships and risk for FE, “more may not always be better.” Encouragement to widen the social network by “making new friends” should be stressed less than making sure these new network members will truly be supportive of the older adult.

Social networks and service use among representative cases of psychosis in South London

1997 ◽  
Vol 171 (1) ◽  
pp. 15-19 ◽  
Author(s):  
Thomas Becker ◽  
Graham Thornicroft ◽  
Morven Leese ◽  
Paul McCrone ◽  
Sonia Johnson ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Service Use ◽  
Network Size ◽  
Controlled Study ◽  
Network Characteristics ◽  
Social Network Size ◽  
The Social ◽  
One Year ◽  
Prospective Controlled Study

BackgroundLarge social networks in patients with severe mental illness have been reported to be associated with a low rate of hospitalisation. We aim to determine whether social network size is related to the likelihood of hospitalisation and the amount of service use.MethodAs part of a prospective controlled study, baseline interview data for a random sample of one-year prevalent cases with non-organic psychosis were analysed with respect to social network characteristics and service use during a six-month period.ResultsThe likelihood of hospitalisation decreased with an increase in network size, while the number of services used by patients grew as the social network size increased.ConclusionsWhile larger social networks may be associated with a lower likelihood of hospitalisation, they may also be related to wider use of non-hospital services.

scholarly journals Social relationships, living arrangements and loneliness

2021 ◽  
Author(s):  
W. Schmitz ◽  
S. Mauritz ◽  
M. Wagner
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Living Arrangements ◽  
Oldest Old ◽  
Well Being ◽  
Intimate Partner ◽  
Network Size ◽  
Cross Sectional ◽  
Social Network Size ◽  
The Social

Abstract Background Oldest-old people are expected to be particularly likely to experience loneliness due to the loss of their intimate partner or of same-aged social network members. It is assumed that individuals in different living arrangements maintain different kinds of social networks because they adjust their networks to their specific needs. However, not much is known about the variation in the social networks of the oldest-old depending on their living arrangements and how this variation is related to loneliness. This is the first study that seeks to fill this research gap by examining how the composition and the size of a social network varies among the oldest-old depending on their living arrangements with a partner (coresidential partnership, living apart together (LAT) partnership, no partnership), and how this variation contributes to explain loneliness among the oldest-old. Methods We used cross-sectional data from the representative survey NRW80+ (Quality of Life and Well-Being of the Very Old in North-Rhine Westphalia). The sample of analysis used in this study consists of 1860 respondents from the German state of North-Rhine Westphalia aged 80 years and older. Associations between social network characteristics and living arrangements were tested using χ2-tests and one-way ANOVA. Ordered logit models were used to explain loneliness. Results Respondents in a coresidential partnership maintained larger social networks than those in an LAT partnership and those with no intimate partner. Furthermore, the respondents with no partner maintained more diverse social networks. Compared to those in the other living arrangements, the respondents in an LAT partnership maintained the smallest and least diverse social networks. Being in a coresidential partnership and the social network size were found to be negatively associated with loneliness. Conclusion First, the results indicate that respondents who do not have a partner adjusted their social networks to meet their needs in the absence of this relationship. Second, we conclude that being in a coresidential partnership and having a large social network protects the oldest-old against loneliness.

Why Do High-Status People Have Larger Social Networks? Belief in Status-Quality Coupling as a Driver of Network-Broadening Behavior and Social Network Size

2020 ◽  
Author(s):  
Jiyin Cao ◽  
Edward Bishop Smith
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Status ◽  
Positive Association ◽  
Network Size ◽  
High Status ◽  
Discussion Section ◽  
Social Network Size ◽  
Tightly Coupled ◽  
The Relationship

Previous research has demonstrated that the size and reach of people’s social networks tend to be positively related to their social status. Although several explanations help to account for this relationship—for example, higher-status people may be part of multiple social circles and therefore have more social contacts with whom to affiliate—we present a novel argument involving people’s beliefs about the relationship between status and quality, what we call status-quality coupling. Across seven separate studies, we demonstrate that the positive association between social status and network-broadening behavior (as well as social network size) is contingent on the extent to which people believe that status is a reliable indicator of quality. Across each of our studies, high- and low-status people who viewed status and quality as tightly coupled differed in their network-broadening behaviors, as well as in the size of their reported social networks. The effect was largely driven by the perceived self-value and perceived receptivity of the networking target. Such differences were significantly weaker or nonexistent among equivalently high- and low-status people who viewed status as an unreliable indicator of quality. Because the majority of participants—both high- and low-status—exhibited beliefs in status-quality coupling, we conclude that such a belief marks an important and previously unaccounted-for driver of the relationship between status, network-broadening behaviors, and social networks. Implications for research on social capital, advice seeking, and inequality are highlighted in the discussion section.

scholarly journals Differences in anxieties and social networks in a group-matched sample of autistic and typically developing students transitioning to university

Autism ◽  
2019 ◽  
Vol 24 (5) ◽  
pp. 1138-1151
Author(s):  
Jiedi Lei ◽  
Chris Ashwin ◽  
Mark Brosnan ◽  
Ailsa Russell
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Anxiety ◽  
Autistic Traits ◽  
Network Size ◽  
Typically Developing ◽  
Social Network Size ◽  
Social Network Structure ◽  
Matched Design ◽  
The Relationship

Transitioning to university can be anxiety-provoking for all students. The relationship between social anxiety, autistic traits and students’ social network structure, and perceived support is poorly understood. This study used a group-matched design where autistic students ( n = 28) and typically developing students ( n = 28) were matched on sex, age (17–19 years), ethnicity, pre-university academic performance and degree subject at university. Autistic students reported greater transition to university worries, and a smaller social network size compared to typically developing students, though perceived similar levels of support from their social networks. Autistic and typically developing students showed differential patterns of association with both autistic traits and social anxiety. Broader clinical and practical implications of findings are discussed.

scholarly journals Influence Maximization in Social Network Considering Memory Effect and Social Reinforcement Effect

2019 ◽  
Vol 11 (4) ◽  
pp. 95
Author(s):  
Wang ◽  
Zhu ◽  
Liu ◽  
Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Memory Effect ◽  
Influence Maximization ◽  
Viral Marketing ◽  
Maximization Problem ◽  
Social Reinforcement ◽  
Reinforcement Effect ◽  
The Social ◽  
Influence Maximization Problem

Social networks have attracted a lot of attention as novel information or advertisement diffusion media for viral marketing. Influence maximization describes the problem of finding a small subset of seed nodes in a social network that could maximize the spread of influence. A lot of algorithms have been proposed to solve this problem. Recently, in order to achieve more realistic viral marketing scenarios, some constrained versions of influence maximization, which consider time constraints, budget constraints and so on, have been proposed. However, none of them considers the memory effect and the social reinforcement effect, which are ubiquitous properties of social networks. In this paper, we define a new constrained version of the influence maximization problem that captures the social reinforcement and memory effects. We first propose a novel propagation model to capture the dynamics of the memory and social reinforcement effects. Then, we modify two baseline algorithms and design a new algorithm to solve the problem under the model. Experiments show that our algorithm achieves the best performance with relatively low time complexity. We also demonstrate that the new version captures some important properties of viral marketing in social networks, such as such as social reinforcements, and could explain some phenomena that cannot be explained by existing influence maximization problem definitions.

scholarly journals Extraversion is associated with advice network size, but not network density or emotional closeness to network members

2020 ◽  
Author(s):  
Connor Malcolm ◽  
Tamsin Saxton ◽  
Kris McCarty ◽  
Sam G. B. Roberts ◽  
Thomas Victor Pollet
Keyword(s):  
Social Network ◽  
Network Size ◽  
Network Density ◽  
Friendship Networks ◽  
Social Self ◽  
Emotional Closeness ◽  
Personality Variables ◽  
Social Network Size ◽  
The Social ◽  
Personal Wellbeing

Friendship networks are instrumental to a whole range of outcomes including career success and personal wellbeing, and as such it is important to ask how social networks are shaped by personality variables. However, previous research examining how extraversion is associated with social network size and closeness to social network members has produced inconsistent findings. Here, we assessed how extraversion (HEXACO model) was associated with three key features of advice networks (size, density, and emotional closeness to network members) in a sample of 199 participants (17 - 75 years, M = 25, SD = 11; 146 women). We found that higher levels of extraversion (and its four facets: social self-esteem, social boldness, sociability, and liveliness) corresponded to a significantly larger advice network, but not greater network density, or greater emotional closeness to network members. The social manifestation of extraversion here seems to be operationalised in terms of a greater number of interactive advice partners, but no increased probability of ensuring that contacts are connected to each other, or of developing emotionally deep relationships with contacts.

Postdiagnosis social networks and lifestyle and treatment mechanisms in the Ater Breast Cancer Pooling Project (ABCPP).

2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 115-115
Author(s):  
Candyce H. Kroenke ◽  
Yvonne Michael ◽  
Xiao-Ou Shu ◽  
Elizabeth Poole ◽  
Marilyn L. Kwan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Social Networks ◽  
Social Network ◽  
Alcohol Consumption ◽  
Cancer Survival ◽  
Network Size ◽  
Cancer Prognosis ◽  
Social Network Size ◽  
Network Diversity ◽  
Socially Isolated

115 Background: Larger social networks have been associated with better breast cancer survival. To investigate potential mediators, we evaluated associations of social network size and diversity with lifestyle and treatment factors associated with prognosis. Methods: We included 9,331 women from the After Breast Cancer Pooling Project who provided data on social networks within two years following diagnosis. A social network index was derived from information about the presence of a spouse or intimate partner, religious ties, community participation, friendship ties, and numbers of relatives. Diversity was assessed as variety of ties, independent of size. We used logistic regression to evaluate associations with outcomes and evaluated whether effect estimates differed using meta-analytic techniques. Results: Associations of social networks and outcomes generally did not differ by cohort. Because of the low prevalence of smoking and alcohol consumption in the Shanghai cohort, however, analyses of smoking and alcohol included US cohorts only. Women who were socially isolated (small networks) were more likely to be obese (body mass index>30 kg/m2, OR=1.21, 95% CI:1.03-1.42) and have low physical activity (<10 MET-h/wk, OR=1.53, 95% CI:1.34-1.75) compared to socially integrated women. Women with low network diversity were more likely to be current smokers (OR=3.68, 95% CI:2.19-6.19) and have high alcohol consumption (>15 g/d alcohol, OR=2.43, 95% CI:1.60-3.69). Among node positive cases, socially isolated women were more likely not to receive chemotherapy (OR=1.52, 95% CI:1.03-2.25). By contrast, low network diversity, but not social network size, was associated with greater odds of not receiving adjuvant hormonal therapy (OR=1.52, 95% CI:1.03-2.23). Associations with surgery were nonsignificant. Conclusions: In a large pooled cohort, small, less diverse social networks measured post-diagnosis were associated with more adverse lifestyle factors and less intensive cancer treatment, which may help to explain poorer breast cancer prognosis in socially isolated women.

scholarly journals Social brain volume is associated with in-degree social network size among older adults

2018 ◽  
Vol 285 (1871) ◽  
pp. 20172708 ◽  
Author(s):  
Seyul Kwak ◽  
Won-tak Joo ◽  
Yoosik Youm ◽  
Jeanyung Chey
Keyword(s):  
Social Network ◽  
Social Connectedness ◽  
Brain Volume ◽  
Brain Regions ◽  
Network Size ◽  
Global Network ◽  
Social Brain ◽  
Social Network Size ◽  
The Social ◽  
Brain Correlates

The social brain hypothesis proposes that large neocortex size evolved to support cognitively demanding social interactions. Accordingly, previous studies have observed that larger orbitofrontal and amygdala structures predict the size of an individual's social network. However, it remains uncertain how an individual's social connectedness reported by other people is associated with the social brain volume. In this study, we found that a greater in-degree network size, a measure of social ties identified by a subject's social connections rather than by the subject, significantly correlated with a larger regional volume of the orbitofrontal cortex, dorsomedial prefrontal cortex and lingual gyrus. By contrast, out-degree size, which is based on an individual's self-perceived connectedness, showed no associations. Meta-analytic reverse inference further revealed that regional volume pattern of in-degree size was specifically involved in social inference ability. These findings were possible because our dataset contained the social networks of an entire village, i.e. a global network. The results suggest that the in-degree aspect of social network size not only confirms the previously reported brain correlates of the social network but also shows an association in brain regions involved in the ability to infer other people's minds. This study provides insight into understanding how the social brain is uniquely associated with sociocentric measures derived from a global network.

scholarly journals Orbital prefrontal cortex volume predicts social network size: an imaging study of individual differences in humans

2012 ◽  
Vol 279 (1736) ◽  
pp. 2157-2162 ◽  
Author(s):  
Joanne Powell ◽  
Penelope A. Lewis ◽  
Neil Roberts ◽  
Marta García-Fiñana ◽  
R. I. M. Dunbar
Keyword(s):  
Prefrontal Cortex ◽  
Social Network ◽  
Cognitive Skills ◽  
Social Cognitive ◽  
Imaging Study ◽  
Network Size ◽  
Magnetic Resonance Images ◽  
Social Brain ◽  
Social Network Size ◽  
The Social

The social brain hypothesis, an explanation for the unusually large brains of primates, posits that the size of social group typical of a species is directly related to the volume of its neocortex. To test whether this hypothesis also applies at the within-species level, we applied the Cavalieri method of stereology in conjunction with point counting on magnetic resonance images to determine the volume of prefrontal cortex (PFC) subfields, including dorsal and orbital regions. Path analysis in a sample of 40 healthy adult humans revealed a significant linear relationship between orbital (but not dorsal) PFC volume and the size of subjects' social networks that was mediated by individual intentionality (mentalizing) competences. The results support the social brain hypothesis by indicating a relationship between PFC volume and social network size that applies within species, and, more importantly, indicates that the relationship is mediated by social cognitive skills.

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