scholarly journals Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users

2018 ◽  
Vol 44 (11) ◽  
pp. 1567-1581 ◽  
Author(s):  
Pan Liu ◽  
David Chan ◽  
Lin Qiu ◽  
William Tov ◽  
Victor Joo Chuan Tong
Keyword(s):  
Social Network ◽  
Impression Management ◽  
Emotional Expression ◽  
Large Scale ◽  
Positive Emotions ◽  
Negative Emotions ◽  
Network Density ◽  
Social Network Structure ◽  
Societal Level ◽  
Using Data

Using data from 13,789 Facebook users across U.S. states, this study examined the main effects of societal-level cultural tightness–looseness and its interaction effects with individuals’ social network density on impression management (IM) in terms of online emotional expression. Results showed that individuals from culturally tight (vs. loose) states were more likely to express positive emotions and less likely to express negative emotions. Meanwhile, for positive emotional expression, there was a tightness–looseness by social network density interaction effect. In culturally tight states, individuals with dense (vs. sparse) networks were more likely to express positive emotions, while in culturally loose states this pattern was reversed. For negative emotional expression, however, no such interaction was observed. Our findings highlight the influence of cultural norms and social network structure on emotional expressions as IM strategies.

scholarly journals Considerations of Control Groups: Comparing Active-Control with No Treatment for Examining the Effects of Brief Intervention

Sports ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 156
Author(s):  
Andrew M. Lane ◽  
Chris J. Beedie ◽  
Tracey J. Devonport ◽  
Andrew P. Friesen
Keyword(s):  
Treatment Group ◽  
Active Control ◽  
Repeated Measures ◽  
Large Scale ◽  
Positive Emotions ◽  
Self Report ◽  
Psychological Skills ◽  
Negative Effects ◽  
Self Report Data ◽  
Using Data

Background: A large-scale online study completed by this research team found that brief psychological interventions were associated with high-intensity pleasant emotions and predicted performance. The present study extends this work using data from participants (n = 3376) who completed all self-report data and engaged in a performance task but who did not engage with an intervention or control condition and therefore present as an opportunistic no-treatment group. Methods: 41,720 participants were selected from the process and outcome focus goals intervention groups, which were the successful interventions (n = 30,096), active-control (n = 3039), and no-treatment (n = 8585). Participants completed a competitive task four times: first as practice, second to establish a baseline, third following an opportunity to complete a brief psychological skills intervention, and lastly following an opportunity to repeat the intervention. Repeated measures MANOVA indicated that over four performance rounds, the intensity of positive emotions increased, performance improved, and the amount of effort participants exerted increased; however, these increases were significantly smaller in the no-treatment group. Conclusions: Findings suggest that not engaging in active training conditions had negative effects. We suggest that these findings have implications for the development and deployment of online interventions.

scholarly journals Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke

2021 ◽  
Vol 12 ◽  
Author(s):  
Archana Podury ◽  
Sophia M. Raefsky ◽  
Lucy Dodakian ◽  
Liam McCafferty ◽  
Vu Le ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Depressive Symptoms ◽  
Network Structure ◽  
Network Size ◽  
Network Density ◽  
Stroke Patients ◽  
Historical Cohort ◽  
Home Based ◽  
Social Network Structure

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms.Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences.Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks.Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.

scholarly journals Mediating Effects of Place Attachment and Satisfaction on the Relationship between Tourists’ Emotions and Intention to Recommend

2016 ◽  
Vol 56 (8) ◽  
pp. 1079-1093 ◽  
Author(s):  
Sameer Hosany ◽  
Girish Prayag ◽  
Robert Van Der Veen ◽  
Songshan (Sam) Huang ◽  
Siripan Deesilatham
Keyword(s):  
Place Attachment ◽  
Positive Emotions ◽  
Positive Relationship ◽  
Negative Emotions ◽  
Developmental Theory ◽  
Mediating Effects ◽  
Tourist Destination ◽  
Model Based ◽  
Using Data ◽  
The Relationship

This study develops a model based on the developmental theory of place attachment. The model considers the influence of tourists’ emotions on place attachment and the mediating effects of satisfaction and place attachment on the relationship between tourists’ emotions and intention to recommend. The model was tested using data collected from 464 international tourists at the end of their trip to Thailand. Results show that positive emotions, negative emotions and satisfaction are significant determinants of place attachment. In particular, negative emotions display a positive relationship with place attachment. In addition, only satisfaction mediates the relationship between tourists’ emotions and intention to recommend. Findings highlight the need for researchers to incorporate emotions in modeling place attachment and offer implications for marketers promoting Thailand as a tourist destination.

scholarly journals China Public Psychology Analysis About COVID-19 Under Considering Sina Weibo Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei Pan ◽  
Ren-jie Wang ◽  
Wan-qiang Dai ◽  
Ge Huang ◽  
Cheng Hu ◽  
...  
Keyword(s):  
Large Scale ◽  
Positive Emotions ◽  
Negative Emotions ◽  
Classification Model ◽  
Test Results ◽  
Data Set ◽  
Decay Period ◽  
Auc Value ◽  
The Government ◽  
And Control

COVID-19 not only poses a huge threat to public health, but also affects people’s mental health. Take scientific and effective psychological crisis intervention to prevent large-scale negative emotional contagion is an important task for epidemic prevention and control. This paper established a sentiment classification model to make sentiment annotation (positive and negative) about the 105,536 epidemic comments in 86 days on the official Weibo of People’s Daily, the test results showed that the accuracy of the model reached 88%, and the AUC value was greater than 0.9. Based on the marked data set, we explored the potential law between the changes in Internet public opinion and epidemic situation in China. First of all, we found that most of the Weibo users showed positive emotions, and the negative emotions were mainly caused by the fear and concern about the epidemic itself and the doubts about the work of the government. Secondly, there is a strong correlation between the changes of epidemic situation and people’s emotion. Also, we divided the epidemic into three period. The proportion of people’s negative emotions showed a similar trend with the number of newly confirmed cases in the growth and decay period, and the extinction period. In addition, we also found that women have more positive emotional performance than men, and the high-impact groups is also more positive than the low-impact groups. We hope that these conclusions can help China and other countries experiencing severe epidemics to guide publics respond.

scholarly journals Rank-dependent social inheritance determines social network structure in a wild mammal population

2020 ◽  
Author(s):  
Amiyaal Ilany ◽  
Kay E. Holekamp ◽  
Erol Akçay
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interactions ◽  
Social Rank ◽  
Wild Mammal ◽  
Social Network Structure ◽  
Spotted Hyenas ◽  
Using Data ◽  
Degree Of Similarity ◽  
Animal Social Networks

AbstractThe structure of animal social networks influences survival and reproductive success, as well as pathogen and information transmission. However, the general mechanisms determining social structure remain unclear. Using data on 73,767 social interactions among wild spotted hyenas over 27 years, we show that a process of social inheritance determines how offspring relationships are formed and maintained. The relationships of offspring with other hyenas are similar to those of their mothers over up to six years, and the degree of similarity increases with maternal social rank. The strength of mother-offspring relationship affects social inheritance and is positively correlated with offspring longevity. These results confirm the hypothesis that social inheritance of relationships can structure animal social networks and be subject to adaptive tradeoffs.

scholarly journals Identifying emotional Facial Expressions in Practice: A Study on Medical Students

2020 ◽  
pp. 025371762093678
Author(s):  
Alapan Bandyopadhyay ◽  
Sarbari Sarkar ◽  
Abhijit Mukherjee ◽  
Sharmistha Bhattacherjee ◽  
Soumya Basu
Keyword(s):  
Social Sciences ◽  
Medical Students ◽  
Facial Expressions ◽  
Emotional Expression ◽  
Positive Emotions ◽  
Medical Training ◽  
Negative Emotions ◽  
Mental Illnesses ◽  
Emotional Facial Expressions ◽  
The Social

Background: Successful identification of emotional expression in patients is of considerable importance in the diagnosis of diseases and while developing rapport between physicians and patients. Despite the importance of such skills, this aspect remains grossly overlooked in conventional medical training in India. This study aims to explore the extent to which medical students can identify emotions by observing photographs of male and female subjects expressing different facial expressions. Methods: A total of 106 medical students aged 18–25, without any diagnosed mental illnesses, were shown images of the six universal facial expressions (anger, sadness, fear, happiness, disgust, and surprise) at 100% intensity with an exposure time of 2 seconds for each image. The participants marked their responses after each image was shown. Collected data were analyzed using Statistical Package for the Social Sciences. Results: Participants could identify 76.54% of the emotions on average, with higher accuracy for positive emotions (95.6% for happiness) and lower for negative emotions (46% for fear). There were no significant variations in identification with respect to sex of the observers. However, it was seen that participants could identify emotions better from male faces than those from female faces, a finding that was statistically significant. Negative emotions were identified more accurately from male faces, while positive emotions were identified better from female ones. Conclusions: Male participants identified emotions better from male faces, while females identified positive emotions better from female faces and negative ones from male faces.

scholarly journals Collective Emotions during the COVID-19 Outbreak

2021 ◽  
Author(s):  
Hannah Metzler ◽  
Bernard Rimé ◽  
Max Pellert ◽  
Thomas Niederkrotenthaler ◽  
Anna Di Natale ◽  
...  
Keyword(s):  
Emotional Expression ◽  
Large Scale ◽  
Positive Emotions ◽  
Emotional Reactions ◽  
Emotional Expressions ◽  
Life Changes ◽  
Social Media Data ◽  
Collective Emotions ◽  
Mental Health Support ◽  
Media Data

The COVID-19 pandemic has exposed the world's population to sudden challenges that elicited strong emotional reactions. Although investigations of responses to tragic one-off events exist, studies on the evolution of collective emotions during a pandemic are missing. We analyzed the digital traces of emotional expressions in tweets during five weeks after the start of outbreaks in 18 countries and six different languages. We observed an early strong upsurge of anxiety-related terms in all countries, which was stronger in countries with stronger increases in cases. Sadness terms rose and anger terms decreased around two weeks later, as social distancing measures were implemented. Positive emotions remained relatively stable. All emotions changed together with an increase in the stringency of measures during certain weeks of the outbreak. Our results show some of the most enduring changes in emotional expression observed in long periods of social media data. Words that frequently occurred in tweets suggest a shift in topics of conversation across all emotions, from political ones in 2019, to pandemic related issues during the outbreak, including everyday life changes, other people, and health. This kind of time-sensitive analyses of large-scale samples of emotional expression have the potential to inform mental health support and risk communication.

scholarly journals Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction

2020 ◽  
Vol 34 (01) ◽  
pp. 254-261
Author(s):  
Haozhe Wu ◽  
Zhiyuan Hu ◽  
Jia Jia ◽  
Yaohua Bu ◽  
Xiangnan He ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Large Scale ◽  
Social Role ◽  
Network Evolution ◽  
Complex Interaction ◽  
Social Network Structure ◽  
Spatial Attributes ◽  
Temporal Interaction

Online Social Networks (OSNs) evolve through two pervasive behaviors: follow and unfollow, which respectively signify relationship creation and relationship dissolution. Researches on social network evolution mainly focus on the follow behavior, while the unfollow behavior has largely been ignored. Mining unfollow behavior is challenging because user's decision on unfollow is not only affected by the simple combination of user's attributes like informativeness and reciprocity, but also affected by the complex interaction among them. Meanwhile, prior datasets seldom contain sufficient records for inferring such complex interaction. To address these issues, we first construct a large-scale real-world Weibo1 dataset, which records detailed post content and relationship dynamics of 1.8 million Chinese users. Next, we define user's attributes as two categories: spatial attributes (e.g., social role of user) and temporal attributes (e.g., post content of user). Leveraging the constructed dataset, we systematically study how the interaction effects between user's spatial and temporal attributes contribute to the unfollow behavior. Afterwards, we propose a novel unified model with heterogeneous information (UMHI) for unfollow prediction. Specifically, our UMHI model: 1) captures user's spatial attributes through social network structure; 2) infers user's temporal attributes through user-posted content and unfollow history; and 3) models the interaction between spatial and temporal attributes by the nonlinear MLP layers. Comprehensive evaluations on the constructed dataset demonstrate that the proposed UMHI model outperforms baseline methods by 16.44 on average in terms of precision. In addition, factor analyses verify that both spatial attributes and temporal attributes are essential for mining unfollow behavior.

Buyer–seller relationship, sales effectiveness and sales revenue: a social network perspective

2018 ◽  
Vol 9 (4) ◽  
pp. 414-436
Author(s):  
Yu Che ◽  
Yongqiang Li ◽  
Kim-Shyan Fam ◽  
Xuan Bai
Keyword(s):  
Social Network ◽  
Underlying Mechanism ◽  
Sales Performance ◽  
Insurance Companies ◽  
Network Density ◽  
Content Type ◽  
Sales Revenue ◽  
Strength Of Ties ◽  
Sales Effectiveness ◽  
Using Data

Purpose This study aims to examine the underlying mechanism of buyer–seller ties and salespeople’s performance. Also examined was the moderating effects of the density of the customer network in which the salesperson is embedded. Design/methodology/approach The study developed a framework incorporating five key variables: strength of ties, network benefits, network density, sales effectiveness and sales revenue. The framework was tested using data from insurance companies in China. Findings Process regression and stepwise regression results indicated that information, influence and solidarity benefit will mediate the effects of strength of ties on sales effectiveness both when taken as a set and separately. Information, influence and solidarity benefit will mediate the effects of strength of ties on sales revenue when taken as a set, but only influence will mediate the effect separately. In addition, the positive relationship between strength of ties and solidarity benefit is weaker when network density is high. Practical implications Sales managers should initiate trainings and workshops about how to obtain high-quality information from customers, improving influencing power and establishing solidarity with customers. Moreover, salespeople should avoid conducting business with a group of customers if they are densely connected to one another. Originality/value On the one hand, this study contributes to the underlying mechanism research on buyer–seller ties and sales performance. On the other hand, it contributes to the contingency research on sales performance and the development of social network theory.

scholarly journals Emotional Contagion in the Online Depression Community

Healthcare ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1609
Author(s):  
Jingyun Tang ◽  
Guang Yu ◽  
Xiaoxu Yao
Keyword(s):  
Support Groups ◽  
Positive Emotions ◽  
Negative Emotions ◽  
User Interaction ◽  
Emotional Contagion ◽  
Estimating Equation ◽  
Generalized Estimating Equation ◽  
Diurnal Patterns ◽  
Using Data ◽  
Interaction Behaviors

Negative emotions are prevalent in the online depression community (ODC), which potentially puts members at risk, according to the theory of emotional contagion. However, emotional contagion in the ODC has not been confirmed. The generalized estimating equation (GEE) was used to verify the extent of emotional contagion using data from 1548 sample users in China’s popular ODC. During interaction, the emotional themes were analyzed according to language use. The diurnal patterns of the interaction behaviors were also analyzed. We identified the susceptible groups and analyzed their characteristics. The results confirmed the occurrence of emotional contagion in ODC, that is, the extent to which the user’s emotion was affected by the received emotion. Our study also found that when positive emotional contagion occurred, the replies contained more hopefulness, and when negative emotional contagion occurred, the replies contained more hopelessness and fear. Second, positive emotions were easier to spread, and people with higher activity in ODC were more susceptible. In addition, nighttime was an active period for user interaction. The results can help community managers and support groups take measures to promote the spread of positive emotions and reduce the spread of negative emotions.

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