Facebook Parenting Groups as a Source for Parenting: An Investigation on Mothers

The main aim of the present study was to examine the reasons for parents’ following of Facebook parenting groups. Another aim was to investigate the demographic, Facebook-use related, individual and parenting-related factors related to the frequency of active and passive following of these groups. One hundred ninety-three Turkish mothers (Mage = 33.56, SDage = 5.03, Range = 21-48) completed the demographic information form, the use of social media form, the trait anxiety inventory, the perceived offline social support scale and the self-perception of parental role questionnaire. Results demonstrated that parents were following Facebook parenting groups more passively and its frequency was related positively to the parent’s education level and the frequency of using Facebook, and negatively to the children’s mean age. The frequency of active following was found to be predicted positively by the frequency of using Facebook and the frequency of sharing on Facebook, and negatively by the level of parental competence. These findings were discussed in terms of the idea that Facebook parenting groups might provide informational support to the parents and have become a source for parenting. Keywords: Parenting, Facebook, online social network, information

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Online Social Network Information Dissemination Integrating Overconfidence and Evolutionary Game Theory

IEEE Access ◽

10.1109/access.2021.3090783 ◽

2021 ◽

pp. 1-1

Author(s):

Xiaochao Wei ◽

Yanfei Zhang ◽

Yuyao Fan ◽

Guihua Nie

Keyword(s):

Game Theory ◽

Social Network ◽

Evolutionary Game Theory ◽

Information Dissemination ◽

Online Social Network ◽

Evolutionary Game ◽

Network Information

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Perceived Stigma and Associated Factors among Patient with Tuberculosis, Wolaita Sodo, Ethiopia: Cross-Sectional Study

Tuberculosis Research and Treatment ◽

10.1155/2019/5917537 ◽

2019 ◽

Vol 2019 ◽

pp. 1-5 ◽

Cited By ~ 5

Author(s):

Bereket Duko ◽

Asres Bedaso ◽

Getinet Ayano ◽

Zegeye Yohannis

Keyword(s):

Social Support ◽

Sampling Technique ◽

Cross Sectional Study ◽

Sectional Study ◽

Perceived Stigma ◽

Related Factors ◽

Cross Sectional ◽

Stigma Scale ◽

Social Support Scale ◽

Wolaita Sodo

Background. Tuberculosis is a historically stigmatized disease and the stigma associated with it affects the institution, community, and interpersonal factors. Therefore, understanding tuberculosis-related perceived stigma has importance in improving quality of the patients. Objective. The aim of this study was to assess prevalence and factors associated with perceived stigma among patients with tuberculosis attending Wolaita Sodo University Referral Hospital, Ethiopia. Methods. Institution based cross-sectional study was conducted among a total of 417 tuberculosis patients who had treatment follow-up at TB clinics and were recruited for the study. Systematic random sampling technique was used to recruit study participants. A 12-item perceived TB stigma scale was used to assess tuberculosis-related perceived stigma. In addition, Oslo social support scale was used to assess social support related factors. Results. Prevalence of tuberculosis-related perceived stigma by using perceived tuberculosis stigma scale was 42.4%. Patients who had pulmonary TB [AOR=2.49, (95% CI: 1.24, 4.87)], being intensive phase category [AOR=1.42, (95% CI: 1.19, 2.58)], TB/HIV coinfection [AOR= 3.54, (95% CI: 1.37, 9.12)], poor social support [AOR=2.45, (95% CI: 1.18, 5.09)], and using substance (alcohol, khat and cigarette) [AOR=1.78, (95% CI: 1.28, 3.17)] were more likely to have perceived TB stigma when compared to their counter parts. Conclusion. Health education programs should be conducted to reduce TB stigma and improve patients’ compliance.

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The Online Social Network and User Innovation

Journal of Organizational and End User Computing ◽

10.4018/joeuc.20211101oa07 ◽

2021 ◽

Vol 33 (6) ◽

pp. 0-0

Keyword(s):

Social Network ◽

Online Social Networks ◽

Structural Characteristics ◽

Online Social Network ◽

User Interaction ◽

User Innovation ◽

Media Technology ◽

The Social ◽

Use Of Social Media ◽

The Impact

The wide use of social media technology boosts many online innovation platforms, providing effective communication channels for innovation spreading among online users. From the social network perspective, this paper investigates the impact of online interactive relations on user innovation by holistically examining online relations from relational and structural embeddedness, qualified by both the ego-centered and the entire network, respectively. User interaction data from LEGO Ideas are used to empirically test the effects of relational and structural characteristics of online social networks on users’ idea contributions. The results for relational characteristics reveal that the number of online ties has an inverted U-shaped relationship with user innovation, the strength of online ties positively affects user innovation, and neighbor characteristics cannot affect user innovation. For structural characteristics, both centrality and bridge location positively affect user innovation. The findings provide reasonable suggestions for both online users and innovation platforms.

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Detecting Stress Based on Social Networking Interactions

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.k1734.0981119 ◽

2019 ◽

Vol 8 (11) ◽

pp. 693-696

Keyword(s):

Data Mining ◽

Social Media ◽

Detection Efficiency ◽

Online Social Network ◽

Social Characteristics ◽

Network Information ◽

Social Media Platforms ◽

Stress States ◽

Detection Of Stress ◽

Social Media Network

Stress is a kind of demand to respond to any in your body's manner. It can be based on experiences that are both good and bad. Psychological stress threatens the health of individuals. People are used to exchanging their schedule and daily operations with colleagues on social media platforms with the reputation of a social media network, creating it possible to hold online social network information for stress detection. For a variety of applications data mining methods are used. Data mining plays a significant role in the detection of stress in sector. We proposed a new model in this article to detect stress. Initially, in this model, discover a correlation between stress states of user and effective public interactions. This describes a set of textual, visual and social characteristics related to stress from different elements and proposes a new hybrid model coupled with Convolutional Neural Network (CNN) to efficiently hold tweet content and data on social interaction to detect stress. The suggested model can enhance the detection efficiency by 97.8 percent, which is quicker than the current scheme, from the experimental outcomes

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