Interactive English Reading Community Based on Social Network Sites

One of the major trends in the reform of English language teaching is the application of network technologies. This paper discusses the application of social network sites in building an interactive English reading community under the guidance of the constructivist learning theory and its influence on the learners＇ English reading. This SNS-aided reading community puts the students as the center and the teacher the guide, embodying students＇ subjectivity, equality, and interactivity. The study shows that the interactive English reading community can motivate students to read, improve their reading skills, and thus develop a new SNS-aided English reading model for English learners.

The Impacts of Social Network Sites on English Teaching and Learning in China

This article mainly studies the impacts of social network sites on English teaching and learning from several aspects,such as the background knowledge of social network sites(SNSs),definition and types,as well as the common use of SNSs in China.The article uses a special view to analyze the possibility of using social network sites on English education.

The Rise and Fall of Social Networking Sites： A Comparative Study of Cyworld and Facebook

This study examines why some social networking sites （SNSs） stagnate while other SNSs grow by comparing Cyworld with Facebook. Cyworld was one of the most successful SNSs in the world, but its international expansion efforts failed. Facebook＇s open technology has had considerable influence on various sectors of the economy and society and allowed it to become a dominant SNS at the global level, whereas Cyworld has remained a local SNS. Facebook＇s open platform and application programming interface （API） pose a serious challenge to Cyworld＇s walled-garden approach. Cyworld is based on strong ties fostering close relationships, whereas Facebook expands social networks through its open and weak ties and has more network power than Cyworld. Therefore, openness is the main reason behind the rise of Facebook and the fall of Cyworld.

The Impact of Social Media Networks Websites Usage on Students’ Academic Performance

Social Networks Sites (SNSs) are dominating all internet users’ generations, especially the students’ communities. Consequently, academic institutions are increasingly using SNSs which leads to emerge a crucial question regarding the impact of SNSs on students’ academic performance. This research investigates how and to what degree the use of SNSs affects the students’ academic performance. The current research’s data was conducted by using drop and collect surveys on a large population from the University of Jordan. 366 undergraduate students answered the survey from different faculties at the university. In order to study the impact of SNSs on student’s academic performance, the research hypotheses was tested by using descriptive analysis, T-test and ANOVA. Research results showed that there was a significant impact of SNS on the student’s academic performance. Also, there was a significant impact of SNS use per week on the student’s academic performance, whereas no differences found in the impact of use of SNSs on academic performance due to age, academic achievement, and use per day to most used sites. The findings of this research can be used to suggest future strategies in enhancing student’s awareness in efficient time management and better multitasking that can lead to improving study activities and academic achievements.

Factors influencing knowledge contribution:An empirical investigation of social networking website users

Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.

Privacy disclosure in Chinese social networking sites:An investigation of Renren users

Purpose:This study was conducted to investigate the current situation of privacy disclosure(in the Chinese social networking sites.Design/methodology/approach:Data analysis was based on profiles of 240 college students on Renren.com,a popular college-oriented social networking site in China.Users’ privacy disclosure behaviors were studied and gender difference was analyzed particularly.Correlation analysis was conducted to examine the relationships among evaluation indicators involving user name,image,page visibility,message board visibility,completeness of education information and provision of personal information.Findings:A large amount of personal information was disclosed via social networking sites in China.Greater percentage of male users than female users disclosed their personal information.Furthermore,significantly positive relationships were found among page visibility,message board visibility,completeness of education information and provision of personal information.Research limitations:Subjects were collected from only one social networking website.Meanwhile,our survey involves subjective judgments of user name reliability,category of profile images and completeness of information.Practical implications:This study will be of benefit for college administrators,teachers and librarians to design courses for college students on how to use social networking sites safely.Originality /value:This empirical study is one of the first studies to reveal the current situation of privacy disclosure in the Chinese social networking sites and will help the research community gain a deeper understanding of privacy disclosure in the Chinese social networking sites.

How Do Companies Achieve Their Marketing Goals With Social Networks？

This work examines the role of social network sites as a tool used by companies to achieve marketing goals. As known from the main business literature, the social network represents one of the most important instrument to improve the company fame by strengthening the affection of customers to the brand. For this reason, some companies use these tools to build relations and contacts with customers all over the world. The population of social networks users is made, for the most parts, of youngsters （people belonging to the 13-30 years old cluster）. In the last years, with the social web networking, social communication lost the exclusive social meaning and social network sites become strategic instruments for the construction of powerful relations that connect people with people and people with firms. This work is aimed at clarifying the genesis and the evolution of the relations between companies and potential customers, focusing on the tools used by the firm to achieve their marketing goals through social network sites （SNSs）. First of all, the work proposes the recognition of some studies about the origin of web social network and their links with marketing strategies. Secondly, it considers marketing goals achieved from any companies through social networking with a particular focus on advertising through web social networking.

Improved Key Node Recognition Method of Social Network Based on PageRank Algorithm

The types and functions of social networking sites are becoming more abundant with the prevalence of self-media culture,and the number of daily active users of social networking sites represented by Weibo and Zhihu continues to expand.There are key node users in social networks.Compared with ordinary users,their influence is greater,their radiation range is wider,and their information transmission capabilities are better.The key node users playimportant roles in public opinion monitoring and hot event prediction when evaluating the criticality of nodes in social networking sites.In order to solve the problems of incomplete evaluation factors,poor recognition rate and low accuracy of key nodes of social networking sites,this paper establishes a social networking site key node recognition algorithm(SNSKNIS)based on PageRank(PR)algorithm,and evaluates the importance of social networking site nodes in combination with the influence of nodes and the structure of nodes in social networks.This article takes the Sina Weibo platform as an example,uses the key node identification algorithm system of social networking sites to discover the key nodes in the social network,analyzes its importance in the social network,and displays it visually.

Anomaly Detection in Social Media Texts Using Optimal Convolutional Neural Network

Social Networking Sites(SNSs)are nowadays utilized by the whole world to share ideas,images,and valuable contents by means of a post to reach a group of users.The use of SNS often inflicts the physical and the mental health of the people.Nowadays,researchers often focus on identifying the illegal beha-viors in the SNS to reduce its negative influence.The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide anno-tated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy.To overcome these issues,the proposed methodology utilizes a Modified Convolutional Neural Network(MCNN)using stochastic pooling and a Leaky Rectified Linear Unit(LReLU).Here,each word in the social media text is analyzed based on its meaning.The stochastic pooling accurately detects the anomalous social media posts and reduces the chance of overfitting.The LReLU overcomes the high computational cost and gradient vanishing problem associated with other activation functions.It also doesn’t stop the learning process when the values are negative.The MCNN computes a specified score value using a novel integrated anomaly detection tech-nique.Based on the score value,the anomalies are identified.A Teaching Learn-ing based Optimization(TLBO)algorithm has been used to optimize the feature extraction phase of the modified CNN and fast convergence is offered.In this way,the performance of the model is enhanced in terms of classification accuracy.The efficiency of the proposed technique is compared with the state-of-art techni-ques in terms of accuracy,sensitivity,specificity,recall,and precision.The proposed MCNN-TLBO technique has provided an overall architecture of 97.85%,95.45%,and 97.55%for the three social media datasets namely Facebook,Twitter,and Reddit respectively.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Kaixin001 Network with Random Hierarchical Model

A new random hierarchical model to describe the neighborhood properties of Kaixin001 network is developed in this paper. The degree distribution of this network model follows P（k） k-γ with y = 1. It means the network model has a power-law distribution. Through calculating the clustering coefficients and average path length （APL）, the result reflects that the model has the properties of high clustering coefficients and low APL.

Detecting Information on the Spread of Dengue on Twitter Using Articial Neural Networks

Social media platforms have lately emerged as a promising tool for predicting the outbreak of epidemics by analyzing information on them with the help of machine learning techniques.Many analytical and statistical models are available to infer a variety of user sentiments in posts on social media.The amount of data generated by social media platforms,such as Twitter,that can be used to track diseases is increasing rapidly.This paper proposes a method for the classication of tweets related to the outbreak of dengue using machine learning algorithms.An articial neural network(ANN)-based method is developed using Global Vector(GloVe)embedding to use the data in tweets for the automatic and efcient identication and classication of dengue.The proposed method classies tweets related to the outbreak of dengue into positives and negatives.Experiments were conducted to assess the proposed ANN model based on performance evaluation matrices(confusion matrices).The results show that the GloVe vectors can efciently capture a sufcient amount of information for the classier to accurately identify and classify tweets as relevant or irrelevant to dengue outbreaks.The proposed method can help healthcare professionals and researchers track and analyze epidemic outbreaks through social media in real time.

Is Facebook Linked to Selfishness? Investigating the Relationships among Social Media Use, Empathy, and Narcissism

The rise of social networking sites have led to changes in the nature of our social relationships, as well as how we present and perceive ourselves. The aim of the present study was to investigate the relationship among the following in adults: use of a highly popular social networking site—Facebook, empathy, and narcissism. The findings indicated that some Facebook activities, such as chatting, were linked to aspects of empathic concern, such as higher levels of Perspective Taking in males. The Photo feature in Facebook was also linked to better ability to place themselves in fictional situations. For only the females, viewing videos was associated with the extent to which they could identify with someone’s distress. The data also indicated that certain aspects of Facebook use, such as the photo feature, were linked to narcissism. However, the overall pattern of findings suggests that social media is primarily a tool for staying connected, than for self-promotion.

中学生被动性社交网站使用与抑郁的关系——身体不满和限制性饮食的链式中介作用及其性别差异

采用社交网站监视使用量表、负面身体自我量表、荷兰饮食行为问卷和流调中心抑郁量表对1161名中学生进行调查。结果发现:(1)被动性社交网站使用分别与身体不满、限制性饮食和抑郁呈显著正相关;(2)身体不满、限制性饮食在被动性社交网站使用与抑郁的关系间起中介作用;(3)身体不满、限制性饮食在被动性社交网站使用与抑郁的关系中起链式中介作用且具有性别差异。中学生被动性网络使用是诱发抑郁的网络风险因素,亦可通过身体不满和限制性饮食影响抑郁的发生,且具有性别差异,这为中学生抑郁的预防与干预工作提供理论指导。

“00后”医学生手机使用情况调查

目的:调查了解“00后”医学生手机使用情况,并对其中的问题提出针对性建议。方法:采用问卷调查方法,对427名“00后”医学生手机使用情况进行了网上问卷调查,并通过秩和检验方法对调查数据进行分析。结果:“00后”医学生手机使用以长时长和高频次为特点,其中,日均使用时长超过4小时的学生占75.6%,每30分钟使用1次的学生占70.2%,每天停止使用手机的时间在23点以后的学生占73.3%,仅有9.1%的学生认为自己能有效控制手机使用。结论:建议出台相关政策措施,对“00后”医学生手机使用进行有效管理和合理引导,既不过度依赖也不盲目排斥,以保障学生的身心健康和全面发展。

数字原住民特征对大学生问题性社交媒体使用的影响:链式中介模型

目的:基于人-情感-认知-执行交互作用(I-PACE)模型考察大学生数字原住民特征与问题性社交媒体使用的关系以及错失恐惧与自我控制的链式中介作用。方法:采用数字原住民量表、特质—状态错失恐惧量表、青少年问题性移动社交网络使用量表和自我控制量表对1071名大学生进行问卷调查。结果:①数字原住民特征正向预测问题性社交媒体使用(β=0.319,P<0.001);②错失恐惧与自我控制分别在其中起中介作用,效应值为0.114、0.067;③错失恐惧与自我控制在其中起链式中介作用,效应值为0.039。结论:数字原住民特征不仅直接影响问题性社交媒体使用,还通过错失恐惧和自我控制单独中介作用以及链式中介作用间接影响问题性社交媒体使用。

社交网站使用对青少年身体不满意的影响及其内在机制

身体不满意在青少年群体中广泛存在,社交网站使用被视为一种关键的影响因素。系统梳理社交网站使用影响青少年身体不满意的表现形式、作用路径及其中的调节因素,对于预防和干预青少年身体不满意具有重要意义。社交网站使用的程度、形式、行为以及动机均可能对青少年的身体不满意产生影响。这种影响主要通过“外貌比较与理想身材内化”“自我客体化与身体监控”“外貌自我图式与外貌自我差异”三条路径发挥作用。此外,这种影响会受到包括大五人格、自恋和完美主义的人格因素,自我同情、自我概念清晰性在内的自我认知因素,以及社交媒体素养、社交媒体外貌意识在内的媒体认知因素的调节。未来应当深化对社交网站使用与身体不满意之间关联的本土化研究,从对象、方法、内容等多个方面拓宽研究领域,并进一步验证和简化理论框架,以期挖掘出更多有益于改善青少年身体不满意的网络干预方案。

学术社交网站信息服务研究——基于国外13家学术社交网站的调查

学术社交网站实现了线上知识共享,满足了用户随时随地进行学术交流的需求。文章通过网站调研、文献检索、邮件咨询等方法,对国外不同类型的13家学术社交网站的学术信息服务进行调查分析,从学术信息服务群体、服务方式、服务内容三个方面总结提炼其服务特色,并为我国学术社交网站学术信息服务发展提出建议:提升个性化服务意识,满足用户差异性需求;汲取优质资源,推动创新发展;拓宽合作范畴,打破交流壁垒。