The objectives of this dissertation are to examine how expatriates¡¦ social network affect the ability of access information/resource and knowing- whom capital on their career advancement, as well as the effects of perceived organizational support correlate to host and home social network. Specially, this research investigates dual sources (host and home office) of expatriates¡¦ network in order to understand the impact on the network abilities and extent. Through confirmed factor analysis of pretest data, measurements were refined and the questionnaire used for the study was developed. For the study, 267 surveys were used for the data analyses. Structural equation modeling in LISREL 8.8 was employed to analyze the relationships among the latent constructs. The findings from the study revealed significant relationships between 1) expatriates¡¦ social network of host office and access information & resource, 2) social network of host office and knowing whom capital, 3) expatriates¡¦ social network of home office and access information & resource, 4) access information & resource and career advancement, and knowing whom capital and career advancement. This study contribute theoretically to the expatriates dual social network literature by clarifying the relationships among host social network, home social network, social network abilities and career advancement, while the previous studies focus on expatriates host country context. This research findings pointed out the expatriates not re-establish a personal network in the host environment but still keep contact with his/her home social network. The expatriates¡¦ host social network has direct and strong effect on access to information/resources and knowing-whom capital. And the expatriates¡¦ home social network also has positive impact on access to information/resources. This empirical model also provides future research with a new angle of view over expatriates social network and career advancement.

We live in a post-PC era with mobile devices on the rise. We can witness a growing number of applications that utilize the mobility of such devices to create applications that make our lives more efficient and connected. In the United States alone, millions of Americans play sports each year starting from middle school through college. With social media on the rise, there is a need for an application that takes advantage of the technologies incorporated in mobile devices with the ability to connect athletes in an area to one another. There is currently a lack of a social network application in the sports category of the Apple App Store. Therefore, this report describes how an iOS mobile application for a sports social network is designed, developed, and deployed. Specifically, we will explore in depth the iOS framework, user stories and requirements, the design and development of the client and backend application, and the tests and results. / text

This thesis aims to analyze the situation on the field of public business and social networks in the world and Czech Republic. It represents the types of software designed for implementation in a business environment and subsequent processing of the relevant data obtained from these networks. The second part focuses on the area of the Public Relations in the local business environment, identifying opportunities for evaluating the contribution for the company and discusses how PR links with emerging trends of everyday use of virtual social networks in companies and in corporate environments.

This research paper aims to investigate the role of enterprise social network to address these concerns such as knowledge sharing and collaboration. The authors have considered a case study based research approach as it is the best method to answer the research question. The leading multinational Bus and truck manufacture Scania was considered for our case study. The study has been done by researching the impact of enterprise social network tools such as Yammer and Lync and their attempt to answer these challenges in the organization. The paper concludes with the analysis based on the empirical findings and theoretical frame of reference. Suggestions and recommendations for further research in this area have also been mentioned in the concluding part of the thesis.

Abstract It likes a knowledge ¡§Yellow Pages ¡¨, knowledge map, indicates where is knowledge and how to get it, but doesn¡¦t contain knowledge. The principal purpose of a knowledge map is showing domain expert when someone need expertise. The resources of teachers¡¦ knowledge map, teachers¡¦ professional information, are fragmented by geographic condition. The map is piece not complete one. As rapid development of Internet, the rich webs contents provide a new way to build global teachers¡¦ knowledge map. The goal of this research is constructing¡yTeachers¡¦ Knowledge Map¡zfor sufficient knowledge sharing environment by collecting teachers¡¦ relative information from the web pages automatically and integrating plentiful Internet resource. There are four main purposes of this research, include (1) getting teachers¡¦ vita from web gages. (2) using teachers¡¦ personal vita and others webs¡¦ resources to construct teacher¡¦s professional specialty, and indicate research issues of teachers. (3) reflecting teachers¡¦ social network by web pages to show social information of individual teacher or group. Teachers¡¦ social network can provide information of how to get the expertise. (4) integrating prior purposes to create useful teachers¡¦ knowledge map for sufficient knowledge sharing environment.

Voluntary turnover is an important organizational issue with costs beyond monetary losses (Morrow & McElroy, 2007). Subsequently, the detrimental effects have engendered extensive research that has led to multiple turnover models attempting to unite antecedents to maximize the variance in predicting turnover and turnover intent (Griffeth et al., 2000). However, current models have omitted important aspects of an employee’s working experience. This dissertation addresses that gap; namely, the need to incorporate relational forces at work that keep individuals at their current organizations. The study integrates social relations and the traditional turnover model (Mobley, 1977) to examine the unique and joint effects of social relations in predicting turnover intent. An empirical study of two independent samples of full-time working individuals (N = 318; N = 235) endorsed a mixed methods approach to expand the measurement of social relations by examining social network content, strength, structure, and influence. Select work personality traits, work characteristics, and turnover outcomes were assessed via an online questionnaire. The results demonstrate that expressive link defection (i.e., friends leaving the organization), instrumental normative pressure to stay (i.e., advisors wanting employees to stay), and instrumental strength (i.e., frequency of contact with advisors) predict significant variance in turnover intent beyond traditional predictors. In addition, expressive link defection and instrumental normative pressure to stay had stronger relationships with turnover intent for longer tenured employees than shorter tenured employees.

This paper structurally estimates a dynamic model of usage behavior and network effects in a social network site using data from MySpace.com. We view a social network as a stock of capital that yields a flow of utilities over time by creating social interactions between the owner and her friends. When one decides to use a social network site, it may have two distinct network effects: (1) one can manage an existing base of friends through social networking and thus prevent depreciation of capital stock (maintenance effect), and (2) one may acquire new friends through social networking, which results in creation of new capital stock (investment effect). Thus, we model social networking as a dynamic process, in which one's current action to use a social network site can influence the evolution of her social network. We found that realtime chat and messaging, features of MySpace.com, positively affect one's usage decision and hence achieve the intended goal of generating site traffic. However, different demographic groups may have idiosyncratic preferences for these features. Based on parameter estimates, we performed counterfactual simulations with the goal of providing managers with ways to enhance firm performance. / text

Graph pattern matching is fundamental to social network analysis. Its effectiveness for identifying social communities and social positions, making recommendations and so on has been repeatedly demonstrated. However, the social network analysis raises new challenges to graph pattern matching. As real-life social graphs are typically large, it is often prohibitively expensive to conduct graph pattern matching over such large graphs, e.g., NP-complete for subgraph isomorphism, cubic time for bounded simulation, and quadratic time for simulation. These hinder the applicability of graph pattern matching on social network analysis. In response to these challenges, the thesis presents a series of effective techniques for querying large, dynamic, and distributively stored social networks. First of all, we propose a notion of query preserving graph compression, to compress large social graphs relative to a class Q of queries. We then develop both batch and incremental compression strategies for two commonly used pattern queries. Via both theoretical analysis and experimental studies, we show that (1) using compressed graphs Gr benefits graph pattern matching dramatically; and (2) the computation of Gr as well as its maintenance can be processed efficiently. Secondly, we investigate the distributed graph pattern matching problem, and explore parallel computation for graph pattern matching. We show that our techniques possess following performance guarantees: (1) each site is visited only once; (2) the total network traffic is independent of the size of G; and (3) the response time is decided by the size of largest fragment of G rather than the size of entire G. Furthermore, we show how these distributed algorithms can be implemented in the MapReduce framework. Thirdly, we study the problem of answering graph pattern matching using views since view based techniques have proven an effective technique for speeding up query evaluation. We propose a notion of pattern containment to characterise graph pattern matching using views, and introduce efficient algorithms to answer graph pattern matching using views. Moreover, we identify three problems related to graph pattern containment, and provide efficient algorithms for containment checking (approximation when the problem is intractable). Fourthly, we revise graph pattern matching by supporting a designated output node, which we treat as “query focus”. We then introduce algorithms for computing the top-k relevant matches w.r.t. the output node for both acyclic and cyclic pattern graphs, respectively, with early termination property. Furthermore, we investigate the diversified top-k matching problem, and develop an approximation algorithm with performance guarantee and a heuristic algorithm with early termination property. Finally, we introduce an expert search system, called ExpFinder, for large and dynamic social networks. ExpFinder identifies top-k experts in social networks by graph pattern matching, and copes with the sheer size of real-life social networks by integrating incremental graph pattern matching, query preserving compression and top-k matching computation. In particular, we also introduce bounded (resp. unbounded) incremental algorithms to maintain the weighted landmark vectors which are used for incremental maintenance for cached results.

Individual variation in asocial and social behavioural traits can affect patterns of social association. Resultant individual-level variation in sociality can be quantified using social network analysis. Social network analysis has recently been applied to the study of the evolution and development of social behaviour. Though captive systems have provided useful contributions to this endeavour, investigating the factors shaping social structure in wild populations affords superior ecological relevance. The characterisation of the social structure of wild animals has been greatly aided by improvements in automated data collection methods, particularly the miniaturisation of Radio-Frequency Identification (RFID) technology for the purposes of studying the social foraging behaviour of wild birds. In this thesis, I use RFID methods to examine the factors influencing between-individual variation in foraging routines (Chapter Two) and social network position (Chapter Three) in wild populations of a colonial corvid species, the jackdaw (Corvus monedula). I then relate social network position to reproductive success (Chapter Three) and investigate the developmental plasticity of jackdaw social behaviour by determining the effect of early life conditions on social network position (Chapter Four). Finally, I describe the fine-scale temporal dynamics of social foraging, the nature of accompaniment during paired foraging and the foraging benefits of social support (Chapter Five).

Much structured data of scientific interest can be represented as networks, where sets of nodes or vertices are joined together in pairs by links or edges. Although these networks may belong to different research areas, there is one property that many of them do have in common: the network community structure, which means that there exists densely connected groups of vertices, with only sparser connections between groups. The main goal of community mining is to discover these communities in social networks or other similar information network environments. We face many deficiencies in current community structure discovery methods. First, one similarity metric is typically applied in all networks, without considering the differences in network and application characteristics. Second, many existing methods assume the network information is fully available, and one node only belongs to one cluster. However, in reality, a social network can be huge thus it is hard to access the complete network. It is also common for social entities to belong to multiple communities. Finally, relations between entities are hard to understand in heterogeneous social networks, where multiple types of relations and entities exist. Therefore, the thesis of this research is to tackle these community mining problems, in order to discover and evaluate community structures in social networks from various aspects.