Promoting social support and social networks among Irish pensioners in South London, UK

This paper explores the activities of an Irish-led voluntary sector project that sought to minimise social isolation and build social networks among Irish elderly people living in a socio-economically deprived borough in South London, UK. The study from which this paper is drawn aimed to explore the nature and extent of unmet mental health needs among Irish pensioners. Using a naturalistic and exploratory design, data were collected through 19 semi-structured interviews, observation of project activities and analysis of members' case files. The paper presents findings in relation to the significant themes that emerged from the data analysis, which used a grounded theory approach. It discusses the social support systems within the project and examines the ways in which they maintained the mental wellbeing of the projects' members and interconnected with other areas of the project's activities. The study's findings demonstrated that the project provided space for social interaction among otherwise isolated Irish pensioners, many of whom experienced multiple morbidity. The project worked successfully to overcome the sense of stigma that prevented many of its members accessing statutory services; it also identified needs among carers. There was an Irish cultural ambience at the project centre, which generated a sense of belonging among members, and assisted in the development of social networks. The project initiated other forms of social support through the use of volunteers and developed befriending and telephone support services. The project developed partnership working with other agencies, particularly community mental health services, in order to provide support to elderly people who might otherwise have been institutionalised. The project engaged with the cultural norms of this marginalised white minority ethnic community to promote both social interaction and social networks. It offered a model of good practice for agencies working with isolated elderly members of minority ethnic communities.

Social reader : following social networks in the wilds of the blogosphere

The social interactions manifest in blogs by the network of comments left by owners and readers are an under-used resource, both for blog pundits and industry. We present a web-based feed reader that renders these relationships with a graph representation, and enables exploration by displaying people and blogs who are proximate to a user's network. Social Reader is an example of Casual Information Visualization, and aims to help the user understand and explore blog-based social networks in a daily, real-life setting. A six week study of the software involving 20 users confirmed the usefulness of the novel visual display, via a quantitative analysis of use logs, and an exit survey.

Augmenting trust establishment in dynamic systems with social networks

Social networking has recently flourished in popularity through the use of social websites. Pervasive computing resources have allowed people stay well-connected to each other through access to social networking resources. We take the position that utilizing information produced by relationships within social networks can assist in the establishment of trust for other pervasive computing applications. Furthermore, we describe how such a system can augment a sensor infrastructure used for event observation with information from mobile sensors (ie, mobile phones with cameras) controlled by potentially untrusted third parties.

Emotional reactions to real-world events in social networks

A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.

The rise of the 'silver surfer' : online social networking and social inclusion for older adults

As the proportion of older adults continues to grow in many Western countries, there are increasing concerns about how to meet their needs. Ensuring social connectedness and inclusion is one way to support older adults’ wellbeing. Online social networking has become common place amongst younger age groups, suggesting its possible usefulness for older adults, in order to combat isolation and loneliness. Some quantitative studies have already explored the amount and degree of online social networking amongst older adults. To add further understanding of how older adults experience social inclusion via the internet, the current qualitative study aimed to explore older adults’ subjective experience of online social networking. Findings demonstrated a number of supports and barriers to social inclusion which reflect barriers to social inclusion of older adults in the non-virtual world. Recommendations to support social inclusion of isolated older adults via online social networking are suggested.

The role of health literacy and social networks in arthritis patients' health information-seeking behavior : a qualitative study

Background. Patients engage in health information-seeking behaviour to maintain their wellbeing and to manage chronic diseases such as arthritis. Health literacy allows patients to understand available treatments and to critically appraise information they obtain from a wide range of sources.

Aims. To explore how arthritis patients' health literacy affects engagement in arthritis-focused health information-seeking behaviour and the selection of sources of health information available through their informal social network.

Methods. An exploratory, qualitative study consisting of one-on-one semi-structured interviews. Twenty participants with arthritis were recruited from community organizations. The interviews were designed to elicit participants' understanding about their arthritis and arthritis medication and to determine how the participants' health literacy informed selection of where they found information about their arthritis and pain medication.

Results. Participants with low health literacy were less likely to be engaged with health information-seeking behaviour. Participants with intermediate health literacy were more likely to source arthritis-focused health information from newspapers, television, and within their informal social network. Those with high health literacy sourced information from the internet and specialist health sources and were providers of information within their informal social network.

Conclusion. Health professionals need to be aware that levels of engagement in health information-seeking behaviour and sources of arthritis-focused health information may be related to their patients' health literacy.

Udderly fantastic online communities : how organisations are using online social networking for community relations and issues management

From empowering consumers and citizens, through to sharing party photographs and organising social events, social networking has transformed the way most people communicate. The Australian dairy industry, wracked by ten years of drought and increasing numbers of activists questioning its environmental and social costs, has established a closed-wall social networking site, called Udderly Fantastic, exclusively for internal stakeholders such as farmers and dairy manufacturers. This case study demonstrates that organisations wanting to engage their stakeholders in an open and transparent way can use social networking as a way of providing information and, importantly, a platform for dialogue in which issues can be raised and discussed.

Online social capital : mood, topical and psycholinguistic analysis

Social media provides rich sources of personal information and community interaction which can be linked to aspect of mental health. In this paper we investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and authors' mood, of a large corpus of blog posts, to analyze the aspect of social capital in social media communities. Using data collected from Live Journal, we find that bloggers with lower social capital have fewer positive moods and more negative moods than those with higher social capital. It is also found that people with low social capital have more random mood swings over time than the people with high social capital. Significant differences are found between low and high social capital groups when characterized by a set of latent topics and psycholinguistic features derived from blogposts, suggesting discriminative features, proved to be useful for classification tasks. Good prediction is achieved when classifying among social capital groups using topic and linguistic features, with linguistic features are found to have greater predictive power than latent topics. The significance of our work lies in the importance of online social capital to potential construction of automatic healthcare monitoring systems. We further establish the link between mood and social capital in online communities, suggesting the foundation of new systems to monitor online mental well-being.

Recognising user identity in twitter social networks via text mining

Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, training of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.