دانلود و نمایش مقالات مرتبط با social information::صفحه 1
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نتیجه جستجو - social information

تعداد مقالات یافته شده: 14
ردیف عنوان نوع
1 Predictors of Traumatic Suicide Attempts in Youth Presenting to Hospitals with Level I Trauma Centers
پیش بینی اقدام به خودکشی آسیب زا در جوانان مراجعه کننده به بیمارستان های مراکز ترومای سطح یک-2020
Background: Limited research exists examining the predictors of suicide attempts by mechanism. Objective: The purpose of this study was to examine predictors of traumatic suicide attempts in youth. Methods: Data came from patients 5–18 years of age presenting because of a suicide attempt at 2 hospitals in Central Texas with level I trauma centers. Univariate logistic regression examined the association between traumatic suicide attempts and variables describing the patient’s demographic, mental health, and social information. We used the Mann–Whitney U test to examine the association between traumatic suicide attempts and the continuous variable of age. Results: Of 231 patients included in this study, most were female (75.8%), non-Hispanic white (48.1%), and had a median age of 15.0 years (interquartile range 14–16). Compared with patients presenting because of an intentional overdose, patients presenting because of traumatic suicide attempts were associated with a reported criminal history (odds ratio [OR] 14.50 [95% confidence interval {CI} 3.84–54.82]), reported Child Protective Services history (OR 3.26 [95% CI 0.99– 10.77]), being publicly insured or uninsured (OR 1.80 [95% CI 1.02–3.19]), male (OR 2.37 [95% CI 1.28–4.38]), and identifying as Hispanic (OR 2.01 [95% CI 1.10–3.68). Conclusions: Our findings inform targeted preventative resources and education efforts to populations of greatest need.
Keywords: emergency department | suicide attempt | trauma center | traumatic suicide attempt | youth
مقاله انگلیسی
2 Research on the application of block chain big data platform in the construction of new smart city for low carbon emission and green environment
تحقیق در مورد کاربرد بستر داده های بزرگ بلاک چین در ساخت شهر هوشمند جدید برای انتشار کربن کم و محیط سبز-2020
The sharing of government information resources is significant for improving the level of governance and social information. However, due to the existence of cross-domain security and trust islands, government departments are hindering the sharing of government information resources with other organizations and the public. To this end, the blockchain technology is used to construct a decentralized distributed peer-to-peer trust service system, which is integrated with the existing PKI/CA security system to establish a new trust model that supports multi-CA coexistence. Based on this, the structural composition and functional data flow of the blockchain smart city information resource sharing and exchange model designed in this paper. This paper launched a study on the role of the smart big data platform, and selected the development of smart cities in Hefei as an empirical analysis. From the connotation of smart city, block chain and big data technology combined, and the positive effects of relevant information technology summarized on the construction of smart city big data platform. Based on this, the smart city development level evaluation model of TOPSIS method constructed. The evaluation model constructed to make a vertical comparison from 2012 to 2017, the scale of smart cities is growing at an average annual rate of more than 30%, saving 20% of urban resource allocation and becoming a new pillar industry. Therefore, Hefei City should further increase environmental supervision and promote the use of low-carbon environmental protection new energy. The improvement of government management level has a positive effect on the construction of smart Hefei
Keywords: Block chain | PKI/CA | New smart city | Government information
مقاله انگلیسی
3 A social recommender system based on reliable implicit relationships
یک سیستم توصیه گر اجتماعی مبتنی بر روابط ضمنی قابل اعتماد-2019
Recommender systems attempt to suggest information that is of potential interest to users helping them to quickly find information relevant to them. In addition to historical user–item interaction data, such as users’ ratings on items, social recommendation methods use social relationships between users to improve the accuracy of recommendations. However, the available social relationships are often extremely sparse. Therefore, incorporating implicit relationships into the recommendation process can be effective to improve the performance of social recommender systems, especially for those users whose explicit relationships are insufficient to make accurate recommendations. The existing approaches have not considered reliability of the implicit relationships. In this paper, a social recommender system is proposed based on reliable implicit relationships. To this end, Dempster– Shafer theory is used as a powerful mathematical tool to calculate the implicit relationships. Moreover, a new measure is introduced to evaluate the reliability of predictions, where unreliable predictions are recalculated using a neighborhood improvement mechanism. This mechanism uses a confidence measure between the users to identify ineffective users in the neighborhood set of a target user. Finally, new reliable ratings are calculated by removing the identified ineffective neighbors. Extensive experiments are conducted on three well-known datasets, and the results demonstrate that our approach achieves superior performance to the state-of-the-art recommendation methods
Keywords: Recommender system | Social information | Reliability | Implicit relationship | Dempster–Shafer theo
مقاله انگلیسی
4 An intelligent recommender system using social trust path for recommendations in web-based social networks
یک سیستم پیشنهادی هوشمند با استفاده از مسیر اعتماد اجتماعی برای توصیه در شبکه های اجتماعی مبتنی بر وب-2019
In this paper, we combine a social regularization approach that incorporates social network information to benefit recommender systems with the trust information between users. Both trust and rating records (tags) are employed to predict the missing values (tags) in the user-item matrix. Especially, we use an algorithm for best recommended trust path selection, to identify multiple recommended trust paths and to determine an aggregate path for generating different final recommendations. Empirical analyses on real datasets show that the combination of social information and trust achieves superior performance to existing approaches.
Keywords: Collaborative filtering | Big data | recommender system| Social network | Trust
مقاله انگلیسی
5 Social skills training (SST) effects on social information processing skills in justice-involved adolescents: Affective empathy as predictor or moderator
تاثیرات آموزش مهارتهای اجتماعی روی مهارتهای پردازش اطلاعات اجتماعی در نوجوانان درگیر با دادگستری: همدلی موثر به عنوان پیش بینی کننده یا واسطه-2018
Objectives To examine the influence of affective empathy on post-treatment effects on social information processing of an outpatient individual social skills training for justice-involved adolescents. Methods The sample consisted of juveniles who received Tools4U, a social skills training with a parental component, as a penal sanction (N = 115). Propensity score matching was used to select a control group of juveniles receiving treatment as usual (TAU) of n = 108 juveniles (of a total N = 354). Affective empathy was examined as a moderator and predictor of treatment effects on social information processing skills: hostile intent attribution and cognitive distortions. Results Empathy only influenced treatment effects on hostile intent attribution, and not on any of the other social information processing skills (i.e., cognitive distortions). Tools4U was only effective in improving hostile intent attribution for juveniles with moderate or high affective empathy and not for juveniles with low empathy. No moderating or predictive effects were found for cognitive distortions. Conclusions Affective empathy only influenced (Tools4U) treatment effects on hostile intent attribution: a minimum level of empathy may be required to decrease hostile intent attribution in treatment. The intervention proved to be effective in decreasing cognitive distortions (i.e., self-centering, assuming the worst), regardless of affective empathy level. Future studies should investigate and refine the complex interaction of affective empathy with other factors and treatment changes, particularly for long-term effects on delinquency.
keywords: Empathy |Predictor |Moderator |Social cognitive skills |Social information processing |Social skills training |Juvenile delinquents |Justice-involved adolescents
مقاله انگلیسی
6 A social recommendation method based on an adaptive neighbor selection mechanism
یک روش توصیه اجتماعی برمبنای یک مکانیزم انتخاب همسایه سازگار-2018
Recommender systems are techniques to make personalized recommendations of items to users. In e-commerce sites and online sharing communities, providing high quality recommendations is an important issue which can help the users to make effective decisions to select a set of items. Collaborative filtering is an important type of the recommender systems that produces user specific recommendations of the items based on the patterns of ratings or usage (e.g. purchases). However, the quality of predicted ratings and neighbor selection for the users are important problems in the recommender systems. Selecting suitable neighbors set for the users leads to improve the accuracy of ratings prediction in recommendation process. In this paper, a novel social recommendation method is proposed which is based on an adaptive neighbor selection mechanism. In the proposed method first of all, initial neighbors set of the users is calculated using clustering algorithm. In this step, the combination of historical ratings and social information between the users are used to form initial neighbors set for the users. Then, these neighbor sets are used to predict initial ratings of the unseen items. Moreover, the quality of the initial predicted ratings is evaluated using a reliability measure which is based on the historical ratings and social information between the users. Then, a confidence model is proposed to remove useless users from the initial neighbors of the users and form a new adapted neighbors set for the users. Finally, new ratings of the unseen items are predicted using the new adapted neighbors set of the users and the interested items are recommended to the active user. Experimental results on three real-world datasets show that the proposed method significantly outperforms several state-of-the-art recommendation methods.
keywords: Recommender systems| Adaptive neighbor selection| Confidence| Reliability| Trust
مقاله انگلیسی
7 Questioner or question: Predicting the response rate in social question and answering on Sina Weibo
سوال کننده و سوال: پیش بینی نرخ پاسخ در سوال و جواب اجتماعی روی وب سینا-2018
With the noted popularity of social networking sites, people increasingly rely on these social networks to address their information needs. Although social question and answering is potentially an important venue seeking information online, it, unfortunately, suffers from a problem of low response rate, with the majority of questions receiving no response. To understand why the response rate of social question and answering is low and hopefully to increase it in the future, this research analyzes extrinsic factors that may influence the response probability of questions posted on Sina Weibo. We propose 17 influential factors from 2 different perspectives: the content of the question, and the characteristics of the questioner. We also train a prediction model to forecast a questions likelihood of being responded based on the proposed features We test our predictive model on more than 60,000 real-world questions posted on Weibo, which generate more than 600,000 responses. Findings show that a Weibos question answerability is primarily contingent on the questioner versus the question. Our findings indicate that using appreciation emojis can increase a questions response probability, whereas the use of hashtags negatively influences the chances of receiving answers. Our contribution is in providing insights for the design and development of future social question and answering tools, as well as for enhancing social network users’ collaboration in supporting social information seeking activities.
keywords: Social Q&A |Social network |Information seeking |Weibo
مقاله انگلیسی
8 رویکرد خوشه‌بندی زمانی برای سیستم‌های توصیه‌گر اجتماعی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 19
هدف سیستم های توصیه گر این است که از بین تعداد زیادی از موارد موجود ، موارد مرتبط را به کاربران پیشنهاد دهند. این سیستم ها با موفقیت در صنایع مختلف مانند تجارت الکترونیک ، آموزش و بهداشت دیجیتال استفاده شده اند. از طرف دیگر ، رویکردهای خوشه بندی می تواند به سیستم های توصیه گر کمک کند تا کاربران را در خوشه های مناسب ، که به عنوان محله های فرایند پیش بینی در نظر گرفته شده اند ، گروه بندی کند. اگرچه این یک واقعیت است که ترجیحات کاربران در طول زمان متفاوت است ، اما رویکردهای خوشه بندی سنتی با نظر گرفتن این عوامل مهم موفق نیستند. برای رفع این مشکل ، یک سیستم توصیه اجتماعی در این مقاله ارائه شده است که مبتنی بر یک رویکرد خوشه بندی زمانی است. به طور خاص ، اطلاعات زمانی رتبه بندی ارائه شده توسط کاربران بر روی موارد و همچنین اطلاعات اجتماعی در بین کاربران در روش پیشنهادی در نظر گرفته شده است. نتایج تجربی در یک مجموعه داده معیار نشان می دهد که کیفیت توصیه ها بر اساس روش پیشنهادی از نظر دقت و اندازه گیری پوشش به طور قابل توجهی بالاتر از روش های پیشرفته است.
کلمات کلیدی: سیستم توصیه گر | خوشه بندی | زمانی | اطلاعات اجتماعی | گراف
مقاله ترجمه شده
9 Expressing emotions in blogs: The role of textual paralinguistic cues in online venting and social sharing posts
ابراز احساسات در وبلاگ ها: نقش نشانه های زبانشناختی متنی در خروجی آنلاین و پست های اشتراک اجتماعی-2017
Textual paralanguage cues (TPC) have been signaled as effective emotion transmitters online. Though several studies have investigated their properties and occurrence, there remains a gap concerning their communicative impact within specific psychological processes, such as the social sharing of emotion (SSE, Rime, 2009). This study content-analyzed Live Journal blogposts for the occurrence of TPC in three  phases of online SSE: initiation, feedback and repost. We compared these to TPC on a second type of emotional expression, emotional venting. Based on Social Information processing theory (SIP, Walther, 1992), and on the Emotional Mimicry in Context (EMC, Hess & Fischer, 2013) framework, we study predictive relationships in TPC usage in our phased model of online SSE. Results showed that TPC pre vailed in SSE blogposts and strongly dominated in emotional venting posts. TPC was more common in affective feedback than cognitive. Moreover, the presence of tactile affective cues (i.e., hugs, kisses) in the initiation post predicted their presence in affective feedback. Results lend support to the idea that TPC are used in socio-contextual ways in online SSE and particularly extrapolate certain FtF nonverbal behaviors, such as the provision of socio-affective touch.
Keywords: Nonverbal communication | Paralinguistic cues | Social sharing of emotion | Emotional mimicry | Venting | Social networking sites
مقاله انگلیسی
10 Why men and women continue to use social networking sites: The role of gender differences
چرا مردان و زنان همچنان از سایت های شبکه های اجتماعی استفاده می کنند: نقش تفاوت های جنسیتی-2017
Organizations increasingly use social media and especially social networking sites (SNS) to support their marketing agenda, enhance collaboration, and develop new capabilities. However, the success of SNS initiatives is largely dependent on sustainable user participa tion. In this study, we argue that the continuance intentions of users may be gender sensitive. To theorize and investigate gender differences in the determinants of continu ance intentions, this study draws on the expectation-confirmation model, the uses and gratification theory, as well as the self-construal theory and its extensions. Our survey of 488 users shows that while both men and women are motivated by the ability to self enhance, there are some gender differences. Specifically, while women are mainly driven by relational uses, such as maintaining close ties and getting access to social information on close and distant networks, men base their continuance intentions on their ability to gain information of a general nature. Our research makes several contributions to the dis course in strategic information systems literature concerning the use of social media by individuals and organizations. Theoretically, it expands the understanding of the phe nomenon of continuance intentions and specifically the role of the gender differences in its determinants. On a practical level, it delivers insights for SNS providers and marketers into how satisfaction and continuance intentions of male and female SNS users can be dif ferentially promoted. Furthermore, as organizations increasingly rely on corporate social networks to foster collaboration and innovation, our insights deliver initial recommenda tions on how organizational social media initiatives can be supported with regard to gender-based differences.
Keywords: Gender | Social networking sites | Facebook | Continuance intention | Satisfaction | Uses and gratifications | Gendered self-construal Relational interdependence | Collective interdependence
مقاله انگلیسی
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