Exploring the Impact of Social Networking on Communication in Organizations

ABSTRACT

Social networking technology has the potential to transform how organizations communicate, cooperate, and connect with key stakeholders. Our research explores how social networking technologies are deployed within organizations and how the use of these technologies is related to effectiveness in organizational communication and promotion. We also identify the facilitating factors and constraints around the use of social networking tools for communication. To examine these questions, we conducted interviews with 131 senior level executives across a broad range of organizations and employed both quantitative and qualitative methods of analysis. The executives were asked to rate numerically and then discuss in narrative form a series of questions about IT strategy and issues affecting social networking in their organization. We find important differences both in the types of tools used as well as how they are used and discuss the implications of our findings for companies seeking to more effectively harness social networking technologies.     

An Empirical Study Evaluating Social Networking Continuance and Success

Social networking site (SNS) use decisions have led to major economic and social transformations worldwide. While many organizations seek to use SNSs from a strategic perspective to reach their customer, it is important to understand what makes SNSs successful in order to use them for competitive purposes. The current research evaluates the influence of the social capital theory on SNS success measures. A model was developed and empirically tested using two data samples to ensure valid and reliable results for success of SNSs. The results display the importance of social capital in SNS success followed by practitioner and academic implications.     

Delineating the dimensions of social support on social networking sites and their effects: A comparative model

Social networking sites (SNSs) allow users to connect with each other by overcoming geographical and temporal boundaries and thus empower people to search for social support from online. Social support has been considered a key social value that online users can obtain from SNSs. However, few studies have systematically investigated social support in such a context. Motivated to address this gap, we have developed an advanced and theoretical framework to delineate social support on SNSs by clearly revealing the dimensions of online social support on SNSs and examining their effects on users' commitment and SNS continuance. Further, we introduce gender as a key moderator and explain in theory how differently men and women perceive the importance of the dimensions in evaluating online social support over SNSs. Our research results indicate that the identified three dimensions (informational support, emotional support, and network management) are important components of the online social support on SNSs, which is positively associated with commitment and continuance. In addition, the weight of each dimension in the evaluation of online social support varies by gender. This study is among the very first to explore online social support in the context of SNS and its effects, and has rich theoretical and practical implications.     

Correlation between Facebook use for educational purposes and academic performance of students

In this paper a research on the application of Facebook in education is presented. A total of 139 students of the Faculty of Education in Sombor (Serbia) participated in the research. The results establish a positive correlation between the academic performance of students and the frequency of use of Facebook for educational purposes. The factor of perceived usefulness greatly affected the decision of students to use Facebook as a learning aid. No significant difference in the frequency of use of Facebook for general purposes has been reported between the groups of students divided by the academic performance.     

Understanding how big data leads to social networking vulnerability

Although the term “Big Data” is often used to refer to large datasets generated by science and engineering or business analytics efforts, increasingly it is used to refer to social networking websites and the enormous quantities of personal information, posts, and networking activities contained therein. The quantity and sensitive nature of this information constitutes both a fascinating means of inferring sociological parameters and a grave risk for security of privacy. The present study aimed to find evidence in the literature that malware has already adapted, to a significant degree, to this specific form of Big Data. Evidence of the potential for abuse of personal information was found: predictive models for personal traits of Facebook users are alarmingly effective with only a minimal depth of information, “Likes”, It is likely that more complex forms of information (e.g. posts, photos, connections, statuses) could lead to an unprecedented level of intrusiveness and familiarity with sensitive personal information. Support for the view that this potential for abuse of private information is being exploited was found in research describing the rapid adaptation of malware to social networking sites, for the purposes of social engineering and involuntary surrendering of personal information.     

物联传感网噪声过滤的自适应线性权值算法

针对物联传感网络由于数据类型不一致造成散粒噪声.提出一种物联传感网络散粒噪声过滤的自适应线性权值算法.提取物联传感网络散粒噪声特征参数,对上述参数进行线性变换,获取噪声关联特征参数自适应线性权值,完成物联传感网络散粒噪声过滤.实验表明,该算法能够有效过滤物联传感网络中的散粒噪声,取得了令人满意的结果.     

CDM:Content Diffusion Model for Information-Centric Networks

This paper proposes the Content Diffusion Model(CDM) for modeling the content diffusion process in information-centric networking(ICN).CDM is inspired by the epidemic model and it provides a method of theoretical quantitative analysis for the content diffusion process in ICN.Specifically,CDM introduces the key functions to formalize the key factors that influence the content diffusion process,and thus it can construct the model via a simple but efficient way.Further,we derive CDM by using different combinations of those key factors and put them into several typical ICN scenarios,to analyze the characteristics during the diffusion process such as diffusion speed,diffusion scope,average fetching hops,changing and final state,which can greatly help to analyze the network performance and application design.A series of experiments are conducted to evaluate the efficacy and accuracy of CDM.The results show that CDM can accurately illustrate and model the content diffusion process in ICN.     

Positive Dedalus programs tolerate non-causality

Declarative networking is a recent approach to programming distributed applications with languages inspired by Datalog. A recent conjecture posits that the delivery of messages should respect causality if and only if they are used in non-monotone derivations. We present our results about this conjecture in the context of Dedalus, a Datalog-variant for distributed programming. We show that both directions of the conjecture fail under a strong semantical interpretation. But on a more syntactical level, we show that positive Dedalus programs can tolerate non-causal messages, in the sense that they compute the correct answer even when messages can be sent into the past.     

Another brick in the Facebook wall – How personality traits relate to the content of status updates

Status updates represent a new form of one-to-many communication which is widely used among members of social networking sites (SNS). The present study investigated the question of who in particular uses the self-presentational opportunities of this feature and which users engage in riskier self-disclosures than others. Combining questionnaire and content analysis, we related self-reports on users’ personality traits (extraversion, narcissism, self-efficacy, need to belong, need for popularity) to the actual use of Facebook status updates. Results showed that higher degrees of narcissism led to deeper self-disclosures and more self-promotional content within these messages. Users with higher need to belong disclosed more intimate information in status updates, while perceived efficacy of self-presentation was negatively related to the mass suitability of postings. Findings extend prior research on personality and SNS usage with regard to dynamic features and content differences in online self-presentation.     

The effect of gratifications derived from use of the social networking site Qzone on Chinese adolescents’ positive mood

Drawing from Uses and Gratifications Theory, this study explores the influence of the gratifications derived from use of the social networking site Qzone on Chinese adolescents’ positive mood. Qzone is the social networking site that is most preferred and used by Chinese adolescents. Hypothesized relationships are analyzed by structural equation analysis in a sample of 220 Chinese adolescents aged 14–19 with an online Qzone profile. Gratifications that Chinese adolescents receive from use of the online social network Qzone, such as socializing, information-seeking, and entertainment are found to have a significantly positive influence on their positive mood. Findings of this study extend the existing theoretical framework on the application of the Uses and Gratifications Theory to social networking sites. In addition, findings are in line with those of a number of authors who suggest that social networking site use may have positive consequences for teenagers. Theoretical and practical implications are discussed.