In recent years, more and more mass mediums mentioned blog, the new individual public mediums in network, and more and more blogger began blogging. They documented their life, expressed deeply felt emotions and provide commentary and opinions in blog. Blog is stage that blogger present self for audience, blogger can transmit image to their audience. But these bloggers express what self-presentation in blog? This research use the concept of self-presentation and analysis of social network, and study the social network is formed with online dairies blog and the self image. we discovered that connection relations centralize in the popular blogs, and the more popular blogs have more indegree. The support of audience is motivation of continue writing for blog. In the dimension of self-presentation, the most self in blog is decorated from real life of blogger. But even blogger can choice to present which image, they still reproduced structure and characteristic of real world in blogoshpere. The research also discovered blogger wish to segregate audience, presented different self before different reader.

Information privacy is a paradoxical issue. Especially after Facebook, information privacy has become more important than before. College student Facebook users share a great deal of information on Facebook, and Facebook collects users’personal information. Users’ personal information on Facebook is linked to their identity; therefore negative consequences (privacy problems) have become possible on Facebook. This study focused on college students’ privacy concerns and awareness of privacy issues and settings. Moreover, heavy and light users’ privacy concerns were compared in this study. According to the survey results, privacy is still important to Facebook users and different privacy concerns exist among heavy and light users. Results also show that privacy on Facebook is not a simple thing. It is related to identity construction, users’ experience, and awareness of privacy implications. / text

No description available.

Thesis (M.A.)--University of West Florida, 2008. / Title from title page of source document. Document formatted into pages; contains 71 pages. Includes bibliographical references.

For the majority of social species, group composition is dynamic, and individuals are interconnected in a heterogeneous social network. In this study I investigate the mechanisms underpinning social structure in the endangered southern resident killer whale (Orcinus Orca) population using a long term dataset, and explore the consequences of these. My results demonstrate that resource availability may be an important determinant of social network structure. A significant relationship between the connectivity of the social network and salmon abundance occurred, with a more interconnected network in years of high salmon abundance. As networks are non-random, highly connected individuals may play a key role in population processes such as information and disease transmission. While associations occurred both within and between matrilines, females had a significantly higher number of associates than males, as did older individuals of both sexes. Older males played a more important role in interconnecting the network. The attributes of group leadership were then investigated in matrilines and in individuals. Leadership was not a factor of size or mean age of matriline. However, there was a significant relationship between leadership score and the matriline sex ratio. Individually, females had higher leadership scores than males, and there was a positive correlation between leadership score and age in both sexes. I suggest that the oldest females have the highest 4 leadership scores due to increased ecological knowledge that comes with a prolonged lifespan. Using multi-generational records for two populations of killer whales, I show that both reproductive and post-reproductive mothers increase the survival of offspring, particularly in older male offspring. This is consistent with theoretical predictions, and may explain why female killer-whales have evolved the longest post-reproductive lifespan of all non-human animals. Given the role that individuals of high network centrality can play in population processes, understanding the driving forces behind social network structure is vital when designing effective conservation and management plans.

Frequent pattern mining is an important research areas in data mining. Since its introduction, it has drawn attention of many researchers. Consequently, many algorithms have been proposed. Popular algorithms include level-wise Apriori based algorithms, tree based algorithms, and hyperlinked array structure based algorithms. While these algorithms are popular and beneficial due to some nice properties, they also suffer from some drawbacks such as multiple database scans, recursive tree constructions, or multiple hyperlink adjustments. In the current era of big data, high volumes of a wide variety of valuable data of different veracities can be easily collected or generated at high velocity in various real-life applications. Among these 5V's of big data, I focus on handling high volumes of big data in my Ph.D. thesis. Specifically, I design and implement a new efficient frequent pattern mining algorithmic technique called B-mine, which overcomes some of the aforementioned drawbacks and achieves better performance when compared with existing algorithms. I also extend my B-mine algorithm into a family of algorithms that can perform big data mining efficiently. Moreover, I design four different frameworks that apply this family of algorithms to the real-life application of social network mining. Evaluation results show the efficiency and practicality of all these algorithms. / February 2017

Resilience refers to the capacity to quickly return to normal levels of functioning in the face of adversity. This capacity has previously been linked to social support. The purpose of this study was to investigate the role of social networks in the association between resilience and social anxiety in a clinical group with social anxiety disorder (n = 41) and a control group of university students (n = 40). The results showed that controls were significantly more resilient than the clinical group. Controls had significantly larger, more diverse and active social networks than the clinical group. Resilience was negatively associated with social anxiety in both groups. In the clinical group, there was a significant partial mediation effect of resilience on social anxiety through the size of the social network, a x b = –0.33, 95% CI [–0.718, –0.111]. Potential clinical applications of these results were discussed.

The present work starts with study of past and current methods from the field of analysis and visualization of social networks. Selected methods are then described in detail. Following part is devoted to research of current software. Selected applications are tested and evaluated according to their capability of showing a development in dynamic social networks -- networks with temporal data. Based on these researches an application is designed and implemented. This application can be used for analysis and visualization of a development of dynamic networks in time. Finally, the application is tested on co-authorship social network by means of the bibliographic database of scientific papers DBLP. The work also presents the results of the experiments with implemented algorithms.

Thesis advisor: Patrick McQuillan / The challenges facing our communities are complex, interconnected, and urgent (Kania & Kramer, 2011). Recognizing these challenges, policy makers, funders, and practitioners are turning to social partnerships as a promising strategy for community and educational change (Bess, 2015; Henig et al., 2015). Social partnerships involve the joining together of organizations from across sectors of society to tackle social problems (Crane & Seitanidi, 2014). The underlying premise of the Promise Neighborhoods program, one such social partnership, is that providing access to resources, services, and supports in a comprehensive manner will have the greatest effect on educational and community outcomes (U.S. Department of Education, 2018). This study seeks to shed light on the process of initiating and implementing a social partnership. In this study the author employed a two-phased, mixed methods design using social network analysis and interviews with organizational representatives to examine the network structures of communication and collaboration within one Promise Neighborhoods initiative: the Boston Promise Initiative. The sample for the social network analysis consisted of 33 individuals from 27 partner organizations. Further, follow-up interviews with 11 individuals were held to understand how network structures and processes might impact educational and community change. Findings from the social network analysis and qualitative interviews reveal networks of communication and collaboration rooted in a deep history of place-based change efforts, facilitating access to network resources and social capital among partner organizations. The findings highlight the importance of recognizing both challenges and opportunities of partnering with schools. Further, the findings highlight the importance of a lead organization’s ability to attend to both technical processes, such as facilitating communication among partners, and cultural processes, such as negotiating organizational identity. Taken together, the findings from this study point to the complex nature of cross-sector collaboration and identify structural factors and network processes that may impact the success of the efforts. By better understanding the structure and processes inherent in social partnerships, organizations can be better supported as they develop and implement cross-sector initiatives aimed at making meaningful change in their communities. / Thesis (PhD) — Boston College, 2018. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.

Thesis advisor: Sara Moorman / With the increasing digitalization of society, the line between private and public has blurred. Social network sites (SNSs) like Facebook and Instagram facilitate such a process, with users utilizing the sites for public displays of private emotions or events. What was once intimate conversation between two individuals or personal experience shared only with those in one’s physical company have become public conversations and shared experiences for networks of Friends and Followers to comment on, like, share, and survey. Consequently, social media has allowed for heightened expressions of grief, a formerly private experience, online through the use of images, words, and reactions. The current study uses survey and interview data to understand who uses social media to grieve the loss of a family member (a particularly private loss), why an individual might do this, and how such posting influences the grieving process for the social media user. / Thesis (BA) — Boston College, 2018. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Sociology.