How random are online social interactions?
Ontology highlight
ABSTRACT:
SUBMITTER: Wang C
PROVIDER: S-EPMC3433691 | biostudies-other | 2012
REPOSITORIES: biostudies-other
Similar Datasets
Project description:It is widely documented that social capital can benefit individual and social development. However, research on the roles of internet technologies in cultivating social capital has not arrived at a consensus. This article aims to understand the effects of online social interactions (OSIs) on generalized trust and prosocial civic engagement, two essential forms of social capital, with a longitudinal study and structural equation model. Fixed-effect model estimations consistently show that OSIs can effectively increase levels of generalized trust in China. Also, trust in parents is used as an alternative dependent variable to provide a comparative analysis. The mechanisms of these two sources of trust are different, and insignificant effects of OSIs on trust in parents are found to implicitly support the causal link between OSIs and trust in strangers. In this study, we implemented a series of robustness checks, for example, examinations using only the netizens as a sample and cross-sectional methods. Furthermore, we explored the relationship between OSIs and prosocial civic engagement (charitable donation), a behavior form of social capital. The SEM results suggested that charitable behaviors were positively affected by OSIs and generalized trust played a positive mediating role. Additionally, significant positive direct and indirect effects through the generalized trust in OSIs were found on prosocial behaviors.
| S-EPMC9614328 | biostudies-literature
Project description:Online health communities facilitate communication among people with health problems. Most prior studies focus on examining characteristics of these communities in sharing content, while limited work has explored social interactions between communities with different stances on a health problem. Here, we analyse a large communication network of individuals affected by eating disorders on Twitter and explore how communities of individuals with different stances on the disease interact online. Based on a large set of tweets posted by individuals who self-identify with eating disorders online, we establish the existence of two communities: a large community reinforcing disordered eating behaviours and a second, smaller community supporting efforts to recover from the disease. We find that individuals tend to mainly interact with others within the same community, with limited interactions across communities and inter-community interactions characterized by more negative emotions than intra-community interactions. Moreover, by studying the associations between individuals' behavioural characteristics and interpersonal connections in the communication network, we present the first large-scale investigation of social norms in online health communities, particularly on how a community approves of individuals' behaviours. Our findings shed new light on how people form online health communities and can have broad clinical implications on disease prevention and online intervention.
| S-EPMC6066201 | biostudies-literature
Project description:Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM), the world's first open-participation research platform for the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients' online social activities by measuring the numbers of "posts and views" and "helpful marks" each patient obtained. The patients' recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank) and the two online social activity measures were significantly correlated with patients' recovery. Furthermore, we re-collected the patients' recovery data two months after the first data collection. We found significant correlations between the patients' social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders.
| S-EPMC4548489 | biostudies-literature
Project description:The COVID-19 pandemic has dramatically changed the nature of our social interactions. In order to understand how protective equipment and distancing measures influence the ability to comprehend others' emotions and, thus, to effectively interact with others, we carried out an online study across the Italian population during the first pandemic peak. Participants were shown static facial expressions (Angry, Happy and Neutral) covered by a sanitary mask or by a scarf. They were asked to evaluate the expressed emotions as well as to assess the degree to which one would adopt physical and social distancing measures for each stimulus. Results demonstrate that, despite the covering of the lower-face, participants correctly recognized the facial expressions of emotions with a polarizing effect on emotional valence ratings found in females. Noticeably, while females' ratings for physical and social distancing were driven by the emotional content of the stimuli, males were influenced by the "covered" condition. The results also show the impact of the pandemic on anxiety and fear experienced by participants. Taken together, our results offer novel insights on the impact of the COVID-19 pandemic on social interactions, providing a deeper understanding of the way people react to different kinds of protective face covering.
| S-EPMC7844002 | biostudies-literature
Project description:Online social networks have increasing influence on our society, they may play decisive roles in politics and can be crucial for the fate of companies. Such services compete with each other and some may even break down rapidly. Using social network datasets we show the main factors leading to such a dramatic collapse. At early stage mostly the loosely bound users disappear, later collective effects play the main role leading to cascading failures. We present a theory based on a generalised threshold model to explain the findings and show how the collapse time can be estimated in advance using the dynamics of the churning users. Our results shed light to possible mechanisms of instabilities in other competing social processes.
| S-EPMC5711899 | biostudies-other
Project description:An increasing fraction of today's social interactions occur using online social media as communication channels. Recent worldwide events, such as social movements in Spain or revolts in the Middle East, highlight their capacity to boost people's coordination. Online networks display in general a rich internal structure where users can choose among different types and intensity of interactions. Despite this, there are still open questions regarding the social value of online interactions. For example, the existence of users with millions of online friends sheds doubts on the relevance of these relations. In this work, we focus on Twitter, one of the most popular online social networks, and find that the network formed by the basic type of connections is organized in groups. The activity of the users conforms to the landscape determined by such groups. Furthermore, Twitter's distinction between different types of interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links to the groups (the weakness of strong ties); events transmitting new information go preferentially through links connecting different groups (the strength of weak ties) or even more through links connecting to users belonging to several groups that act as brokers (the strength of intermediary ties).
| S-EPMC3256152 | biostudies-literature
Project description:BACKGROUND:Methamphetamine is an illicit and addictive psychostimulant that remains to be a significant cause of economic burden in Australia. Social media is increasingly being used by nongovernment organizations and health services to encourage the growth of social support networks among people with health-related issues. Several studies have investigated the utility of social media in providing social support to groups of people with health-related issues. However, limited research exists that explores how people who have been directly or indirectly affected by methamphetamine use social media for social support. OBJECTIVE:This study aimed to determine the types of social support being sought and provided by people affected by methamphetamine when interacting with others on a Facebook page. METHODS:A total of 14,777 posts were collected from a Facebook page and transferred into an Excel document for content analysis. The posts were manually coded into categories of social support using an adapted version of Cutrona and Suhr's Social Support Behavior Code. Posts could be coded into more than one category. Saturation was reached at 2000 posts, which were used to draw inferences. RESULTS:Emotional support was the most offered support type, with 42.05% (841/2000) of posts providing this form of support. This is followed by esteem support, which was provided in 40.40% (808/2000) of posts. Overall, 24.20% (484/2000) of posts offered informational support. Network support and tangible support were the least offered support types, with 2.25% (45/2000) and 1.70% (34/2000) of posts offering these types of support, respectively. CONCLUSIONS:This study suggests that online social support groups can be effective in challenging stigma by encouraging people affected by methamphetamine to connect with each other and talk about their struggles. This in turn represents an important step toward successful rehabilitation.
| S-EPMC6774572 | biostudies-literature
Project description:Who thrives while socially distancing? In this exploratory study, we polled over 500 participants from the United States on April 8, 2020-during the early stages of the COVID-19 pandemic when the practice of social distancing was at its peak. Above and beyond other social and nonsocial activities, living arrangements, employment circumstances, personality traits, and demographics, people who spent more time interacting with close others-in person or online-felt more socially connected. In contrast, people who spent more time interacting with weak ties, specifically online, experienced greater negative affect, more stress, and lower social connectedness. In sum, much like in-person interactions, online social interactions with strong ties are associated with higher well-being, but online interactions with weak ties are related to lower well-being.
| S-EPMC8525190 | biostudies-literature
Project description:Recurrent neural networks (RNNs) enable the production and processing of time-dependent signals such as those involved in movement or working memory. Classic gradient-based algorithms for training RNNs have been available for decades, but are inconsistent with biological features of the brain, such as causality and locality. We derive an approximation to gradient-based learning that comports with these constraints by requiring synaptic weight updates to depend only on local information about pre- and postsynaptic activities, in addition to a random feedback projection of the RNN output error. In addition to providing mathematical arguments for the effectiveness of the new learning rule, we show through simulations that it can be used to train an RNN to perform a variety of tasks. Finally, to overcome the difficulty of training over very large numbers of timesteps, we propose an augmented circuit architecture that allows the RNN to concatenate short-duration patterns into longer sequences.
| S-EPMC6561704 | biostudies-literature
Project description:Social interactions in insects are strongly driven by conspecific chemical signals that are detected via chemoreceptors of olfactory and gustatory neurons. Odorant binding proteins (Obps) transport volatile odorants to chemosensory receptors, but their pleiotropic effects on behaviors and other traits are not well characterized. Here, we knocked down expression of 14 Drosophila melanogaster Obp genes using RNAi and found that seven had reduced male aggressive behavior, particularly Obp56h. RNAi knockdown of Obp56h gene expression also reduced courtship latency; significantly impacted cuticular hydrocarbon production, with a major reduction in 5-Tricosene (5-T); and affected expression of many other genes, including Or19b, Gr97a and several genes associated with lipase activity. We propose that Obp56h plays a dual role in pheromone production and perception and that 5-T, an inhibitory sex pheromone produced by males that increases latency for early stages of courtship, is implicated as a possible ligand for Obp56h.
2017-01-01 | GSE75590 | GEO