Horizon CDT Year 1

地平线 CDT 第 1 年

• 批准号: 2887266
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2887266
• 关键词: Horizon; CDT; Year

Digital communication plays a crucial role in social interactions, social network maintenance and people's mental wellbeing (Masur, 2021; Meier et al., 2016). With language data providing insights into social network dynamics (Liu et al., 2022), gossip is an important component of social interactions (Yucel et al., 2021) and lack thereof.Loneliness, inevitably associated with social interactions, has increased in recent years due to the COVID-19 pandemic and the associated social changes (Kovacs et al., 2021). The perspectives of marginalised groups such as LGBTQ+, disabled and neurodivergent people are often misunderstood and dismissed with regard to loneliness and social dynamics (Mellifont, 2021; Armitage & Nellums, 2020; Garcia et al., 2019). In addition, past research has identified issues with studies investigating loneliness as a phenomenon, such as the under-representation of adults aged 25-65, with most data coming from young (18-21) and older adults (65+); as well as the need to consider behavioural data in future research (Reedman-Flint et al., 2022).Considering the above problems, this PhD project aims to cross-sectionally understand people's sense of embeddedness in their digital and offline social networks. Drawing on the experiences of adults aged 18-65 years old (allowing for the inclusion of 18-24 year-olds due to the numerous social transitions typically happening around that age); the LGBTQ+ community as well as disabled and neurodivergent people outside of clinical settings, the analysis will allow us to gain insight into the dynamics of social networks, language patterns as well as the role of gossip in interactions within social groups.The inclusion of marginalised voices in this research project will allow to design tailored interventions for improved wellbeing, including both digital self-help resources as well as guidance for counsellors.The proposed methodology will be of mixed nature. Participants will be invited to take part in interviews and complete surveys on their social network dynamics and loneliness experiences. Minority group membership will be considered amongst the demographic information collected as well as lived experiences, where appropriate. Additionally, the participants will be asked to share their digital footprint data for language and social network insights. The data will be analysed using a mixed-methods approach: combining quantitative and qualitative language analysis methods, in addition to social network analysis and predictive models.This PhD project will contribute to the understanding of the social network dynamics and loneliness experiences of disabled, neurodivergent and LGTBQ+ people; in addition to expanding on the existing knowledge of the above for the general adult population. This approach will allow to design and implement digital wellbeing interventions tailored to the user's needs.The project is running in partnership with B:friend - a befriending charity offering support to lonely older adults. The work is supported by the Engineering and Physical Research Council [Grant number EP/S023305/1].

数字通信在社交互动、社交网络维护和人们的心理健康中起着至关重要的作用（Masur，2021; Meier等人，2016年）。语言数据提供了对社交网络动态的洞察（Liu et al.，2022），八卦是社会互动的重要组成部分（Yucel等人，由于COVID-19大流行和相关的社会变化，不可避免地与社会互动相关的孤独近年来有所增加（Kovacs et al.，2021年）。边缘化群体，如LGBTQ+，残疾人和神经分歧者的观点经常被误解和忽视，涉及孤独和社会动态（Mellifont，2021; Armitage & Nellums，2020; Garcia等人，2019年）。此外，过去的研究已经确定了将孤独感作为一种现象进行研究的问题，例如25-65岁的成年人代表性不足，大多数数据来自年轻人（18-21岁）和老年人（65岁以上）;以及需要在未来的研究中考虑行为数据（Reedman-Flint等人，2022).考虑到上述问题，本博士项目旨在跨部门地了解人们在数字和离线社交网络中的嵌入感。借鉴18-65岁成年人的经验（考虑到18-24岁年龄段的人通常会经历许多社会转型，因此可以纳入这一年龄段）; LGBTQ+社区以及临床环境之外的残疾人和神经分歧者，分析将使我们能够深入了解社交网络的动态，语言模式以及八卦在社会群体互动中的作用。在这个研究项目中纳入边缘化的声音将允许设计量身定制的干预措施，以改善福祉，包括数字自助资源和辅导员指导。拟议的方法将是混合性的。参与者将被邀请参加访谈，并完成关于他们的社交网络动态和孤独体验的调查。在收集的人口统计信息以及生活经历中，将酌情考虑少数群体成员身份。此外，参与者将被要求分享他们的数字足迹数据，以获得语言和社交网络见解。数据将使用混合方法进行分析：将定量和定性语言分析方法相结合，以及社交网络分析和预测模型。这个博士项目将有助于理解残疾人，神经分歧者和LGTBQ+人群的社交网络动态和孤独体验;此外，还将扩展上述普通成年人群的现有知识。该项目与B：friend（一家为孤独的老年人提供支持的慈善机构）合作开展。这项工作得到了工程和物理研究理事会的支持[批准号EP/S 023305/1]。