Gay men, social media and self-presentation : managing identities in Gaydar, Facebook and beyond

This study analyses young gay men's identity management in social networking sites Gaydar and Facebook. It examines the expanded opportunities for identity management made available through the convergence of these spaces, as well as new privacy and safety concerns. Findings from this study are discussed in terms of their significance for gay men's digital culture, the approach to gay men's mental health taken by GLBT organisations and support groups, and within broader concerns around social networking sites and digital inequality.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

Community college faculty's teaching social networks and their implications for librarians

Collaboration between faculty and librarians is an important topic of discussion and research among academic librarians. These partnerships between faculty and librarians are vital for enabling students to become lifelong learners through their information literacy education. This research developed an understanding of academic collaborators by analyzing a community college faculty's teaching social networks. A teaching social network, an original term generated in this study, is comprised of communications that influence faculty when they design and deliver their courses. The communication may be formal (e.g., through scholarly journals and professional development activities) and informal (e.g., through personal communication) through their network elements. Examples of the elements of a teaching social network may be department faculty, administration, librarians, professional development, and students. This research asked 'What is the nature of faculty's teaching social networks and what are the implications for librarians?' This study moves forward the existing research on collaboration, information literacy, and social network analysis. It provides both faculty and librarians with added insight into their existing and potential relationships. This research was undertaken using mixed methods. Social network analysis was the quantitative data collection methodology and the interview method was the qualitative technique. For the social network analysis data, a survey was sent to full-time faculty at Las Positas College, a community college, in California. The survey gathered the data and described the teaching social networks for faculty with respect to their teaching methods and content taught. Semi-structured interviews were conducted following the survey with a sub-set of survey respondents to understand why specific elements were included in their teaching social networks and to learn of ways for librarians to become an integral part of the teaching social networks. The majority of the faculty respondents were moderately influenced by the elements of their network except the majority of the potentials were weakly influenced by the elements in their network in their content taught. The elements with the most influence on both teaching methods and content taught were students, department faculty, professional development, and former graduate professors and coursework. The elements with the least influence on both aspects were public or academic librarians, and social media. The most popular roles for the elements were conversations about teaching, sharing ideas, tips for teaching, insights into teaching, suggestions for ways of teaching, and how to engage students. Librarians' weakly influenced faculty in their teaching methods and their content taught. The motivating factors for collaboration with librarians were that students learned how to research, students' research projects improved, faculty saved time by having librarians provide the instruction to students, and faculty built strong working relationships with librarians. The challenges of collaborating with librarians were inadequate teaching techniques used when librarians taught research orientations and lack of time. Ways librarians can be more integral in faculty's teaching social networks included: more workshops for faculty, more proactive interaction with faculty, and more one-on-one training sessions for faculty. Some of the recommendations for the librarians from this study were develop a strong rapport with faculty, librarians should build their services in information literacy from the point of view of the faculty instead of from the librarian perspective, use staff development funding to attend conferences and workshops to improve their teaching, develop more training sessions for faculty, increase marketing efforts of the librarian's instructional services, and seek grant opportunities to increase funding for the library. In addition, librarians and faculty should review the definitions of information literacy and move from a skills based interpretation to a learning process.

Augmenting analytical CRM strategies with social BI

Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

A social matching system : using implicit and explicit information for personalized recommendation in online dating service

Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.

Social networks in arid Australia : a review of concepts and evidence

Arid systems are markedly different from non-arid systems. This distinctiveness extends to arid-social networks, by which we mean social networks which are influenced by the suite of factors driving arid and semi-arid regions. Neither the process of how aridity interacts with social structure, nor what happens as a result of this interaction, is adequately understood. This paper postulates three relative characteristics which make arid-social networks distinct: that they are tightly bound, are hierarchical in structure and, hence, prone to power abuses, and contain a relatively higher proportion of weak links, making them reactive to crisis. These ideas were modified from workshop discussions during 2006. Although they are neither tested nor presented as strong beliefs, they are based on the anecdotal observations of arid-system scientists with many years of experience. This paper does not test the ideas, but rather examines them in the context of five arid-social network case studies with the aim of hypotheses building. Our cases are networks related to pastoralism, Aboriginal outstations, the ‘Far West Coast Aboriginal Enterprise Network’ and natural resources in both the Lake-Eyre basin and the Murray–Darling catchment. Our cases highlight that (1) social networks do not have clear boundaries, and that how participants perceive their network boundaries may differ from what network data imply, (2) although network structures are important determinants of system behaviour, the role of participants as individuals is still pivotal, (3) and while in certain arid cases weak links are engaged in crisis, the exact structure of all weak links in terms of how they place participants in relation to other communities is what matters.

Social media and tacit knowledge sharing : physicians' perspectives and experiences

Tacit knowledge sharing amongst physicians is known to have a significant impact on the quality of medical decisions. This thesis posits that social media can provide new opportunities for tacit knowledge sharing amongst physicians, and demonstrates this by presenting findings from a review of relevant literature and a qualitative survey conducted with physicians. Using thematic analysis, the study revealed five major themes and over twenty sub-themes as potential contributions of social media to tacit knowledge flow amongst physicians.

Producing while consuming: Social interaction around photos shared within private group

User-generated content plays a pivotal role in the current social media. The main focus, however, has been on the explicitly generated user content such as photos, videos and status updates on different social networking sites. In this paper, we explore the potential of implicitly generated user content, based on users’ online consumption behaviors. It is technically feasible to record users’ consumption behaviors on mobile devices and share that with relevant people. Mobile devices with such capabilities could enrich social interactions around the consumed content, but it may also threaten users’ privacy. To understand the potentials of this design direction we created and evaluated a low-fidelity prototype intended for photo sharing within private groups. Our prototype incorporates two design concepts, namely, FingerPrint and MoodPhotos that leverage users’ consumption history and emotional responses. In this paper, we report user values and user acceptance of this prototype from three participatory design workshops.

Identifying the Events That Connect Social Media Users : Charting Follower Accession on Twitter

Twitter is the focus of much research attention, both in traditional academic circles and in commercial market and media research, as analytics give increasing insight into the performance of the platform in areas as diverse as political communication, crisis management, television audiencing and other industries. While methods for tracking Twitter keywords and hashtags have developed apace and are well documented, the make-up of the Twitter user base and its evolution over time have been less understood to date. Recent research efforts have taken advantage of functionality provided by Twitter's Application Programming Interface to develop methodologies to extract information that allows us to understand the growth of Twitter, its geographic spread and the processes by which particular Twitter users have attracted followers. From politicians to sporting teams, and from YouTube personalities to reality television stars, this technique enables us to gain an understanding of what prompts users to follow others on Twitter. This article outlines how we came upon this approach, describes the method we adopted to produce accession graphs and discusses their use in Twitter research. It also addresses the wider ethical implications of social network analytics, particularly in the context of a detailed study of the Twitter user base.

The role of the ethnic enclave in facilitating immigrant business performance and social integration

Chinese immigrant entrepreneurs, known the world over for their successful business practices (Kee, 1994), tend to start businesses within their ethnic enclave. But in a move away from multiculturalism, host countries increasingly fear that immigration and asylum pose a threat to social integration resulting in a lack of social cohesion and a plethora of government programs (Cheong, Edwards, Goulbourne & Solomos, 2007). For many immigrant entrepreneurs, the EE is an integral part of their social and cultural context and the location where ethnic resources reside (Logan, Alba & Stults, 2003). Immigrant entrepreneurs can harness the networks for labor and customers through various ties in their EE (Portes and Zhou, 1996). Yang, Ho and Chang (2010) illustrate in their paper that the Chinese immigrant entrepreneurs (IE) were able to utilize ethnic network resources as their social capital in order to reduce transaction costs and thus enhance business performance. Tilly (1990) explains that immigrants’ reliance on such networks for business or other information minimizes the socioeconomic hardships they would experience in host countries (Raijman & Tienda, 2000). Acquiring jobs in ethnic businesses and establishing businesses within an EE may facilitate migrants’ social integration into the host country (Tian & Shan, 1999). Although an EE has distinct economic advantages for immigrant entrepreneurs, Sequeira and Rasheed (2006: 367) argue that ‘Exclusive reliance on strong ties within the immigrant enclave has a negative effect on growth outside the enclave community.’ Similarly, Drori, Honig and Ginsberg (2010: 20) also propose that ‘The greater the reliance of transnational entrepreneurs on ethnic (versus societal) embedded resources and network structure, the narrower their possibilities of expanding the scope of their business.’ This research asks, ‘What is the role of the ethnic enclave in facilitating immigrant business growth and social integration? This project has the following important aims: A1 To better understand the role of IE, in particular Chinese IE in the Australian economy A2 To investigate the role of the EE in facilitating or inhibiting immigrant business performance A3 To understand how locating their firm inside or outside of the EE will affect the IE’s embeddedness in co-ethnic and nonco-ethnic networks and social integration A4 To understand how an IE’s social network affects business performance and social integration

Professional development and social networks in digital content industry micro businesses

This study explores the professional development strategies of digital content professionals in Australian micro businesses. This thesis presents the argument that as these professionals are working in cutting edge creative fields where digital technology drives ongoing change, formal education experiences may be less important than for other professionals, and that specific types of online and face-to-face socially mediated informal learning strategies may be critical to currency. This thesis documents the findings of a broad survey of industry professionals' learning needs and development strategies, in conjunction with rich data from in-depth interviews and social network analyses.

The association between social support and levels of psychological distress in pregnant women in Australia

The purpose of this study was to explore associations between forms of social support and levels of psychological distress during pregnancy. Methods: A cross-sectional analysis of 2,743 pregnant women from south-east Queensland, Australia, was conducted utilising data collected between 2007-2011 as part of the Environments for Healthy Living (EFHL) project, Griffith University. Psychological distress was measured using the Kessler 6; social support was measured using the following four factors: living with a partner, living with parents or in-laws, self-perceived social network, and area satisfaction. Data were analysed using an ordered logistic regression model controlling for a range of socio-demographic factors. Results: There was an inverse association between self-perceived strength of social networks and levels of psychological distress (OR = 0.77; 95%CI: 0.70, 0.85) and between area satisfaction and levels of psychological distress (OR = 0.77; 95%CI: 0.69, 0.87). There was a direct association between living with parents or in-laws and levels of psychological distress (OR = 1.50; 95%CI: 1.16, 1.96). There was no statistically significant association between living with a partner and the level of psychological distress of the pregnant woman after accounting for household income. Conclusion: Living with parents or in-laws is a strong marker for psychological distress. Strategies aiming to build social support networks for women during pregnancy have the potential to provide a significant benefit. Policies promoting stable family relationships and networks through community development could also be effective in promoting the welfare of pregnant women.

‘He has a way gayer Facebook than I do’ : investigating sexual identity disclosure and context collapse on a social networking site

This study extends previous research into social networking sites (SNSs) as environments that often reduce spatial, temporal, and social boundaries, which can result in collapsed contexts for social situations. Context collapse was investigated through interviews and Facebook walkthroughs with 27 LGBTQ young people in the United Kingdom. Since diverse sexualities are often stigmatized, participants’ sexual identity disclosure decisions were shaped by both the social conditions of their online networks and the technological architecture of SNSs. Context collapse was experienced as an event through which individuals intentionally redefined their sexual identity across audiences or managed unintentional disclosure. To prevent unintentional context collapse, participants frequently reinstated contexts through tailored performances and audience separation. These findings provide insight into stigmatized identity performances in networked publics while situating context collapse within a broader understanding of impression management, which paves the way for future research exploring the identity implications of everyday SNS use.

Twitter-archive und die Herausforderungen von "Big Social Data" für die Medien- und Kommunikationswissenschaft

Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.