19 resultados para Attributed Social Networks, Community Detection
Resumo:
This book explores a compelling range of community-based activities from different cultures and nations which help nurture intercultural understanding and practices of sustainable development. The specially commissioned chapters from practitioners and academics offer a set of interconnected case studies, personal stories, philosophical discussions and critical reflections on direct experiences focussing on co-operative action, creative media innovation and community empowerment connecting individuals, groups, organisations from across our converging world. At the bookís core is a central belief that ecological sustainability can only be attained through social learning, community empowerment, participation and a commitment to global justice. It is the first in a series of books addressing issues emerging from the Schumacher Instituteís Converging World Initiative.
Resumo:
The world's population is ageing. Older people are healthier and more active than previous generations. Living in a hypermobile world, people want to stay connected to dispersed communities as they age. Staying connected to communities and social networks enables older people to contribute and connect with society and is associated with positive mental and physical health, facilitating independence and physical activity while reducing social isolation. Changes in physiology and cognition associated with later life mean longer journeys may have to be curtailed. A shift in focus is needed to fully explore older people, transport and health; a need to be multidisciplinary in approach and to embrace social sciences and arts and humanities. A need to embrace different types of mobilities is needed for a full understanding of ageing, transport and health, moving from literal or corporeal through virtual and potential to imaginative mobility, taking into account aspirations and emotions. Mobility in later life is more than a means of getting to destinations and includes more affective or emotive associations. Cycling and walking are facilitated not just by improving safety but through social and cultural norms. Car driving can be continued safely in later life if people make appropriate and informed decisions about when and how to stop driving; stringent testing of driver ability and skill has as yet had little effect on safety. Bus use facilitates physical activity and keeps people connected but there are concerns for the future viability of buses. The future of transport may be more community led and involve more sharing of transport modes.
Resumo:
Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.
Resumo:
In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.