ESRC Capital Funding: Social Data Science Lab - Continuation of Methods and Infrastructure Development for Open Data Analytics in Social Research

ESRC 资本资助：社会数据科学实验室 - 社会研究中开放数据分析方法和基础设施开发的延续

• 批准号: ES/P008755/1
• 负责人: Pete Burnap
• 金额: $ 169.45万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FP008755%2F1
• 关键词: ESRC; Capital; Funding; Social; Data

The Social Data Science Lab has been established with the mission of democratising access to big social data among the academic, public and third sectors, and to support real-time social data analytics for research, policy & practice. The proposed capability project is designed to address existing technical and methodological shortcomings in our ability to marshal big social data for social research purposes. In particular, the project will provide enhanced and sustainable social media data collection and analysis technologies to academic, public and third sector researchers. This capability project will achieve this by:1. Providing the required technical resource and expertise to: i) optimise existing Lab social media analytics technologies for more efficient social media data collection, transformation and analysis across operating platforms (Windows, Linux, Mac OS); ii) integrate existing social media analytics tools (such as demographic and text classification tools); iii) make existing Lab tools extendable by the researcher community; iv) adapt Lab tools to user requirements and changes in social media provider technologies (i.e API changes); and v) support researchers in their social media data and analysis needs via dedicated Lab training and working-papers;2. Providing the required social science resource and expertise to: i) liaise with the researcher community to gather social media tool requirements; ii) liaise with ESRC administrative, local government and consumer big data centres; iii) write training materials and coordinate capability building activities; and iv) support researchers in their data and analysis queries;3. Ensuring the required investigator time to: i) manage the optimisation and enhancement of Lab tools and to implement a 'sustainability' business model; ii) manage existing partnerships with public, private and third sector users and the various ESRC big data network centres in the UK and elsewhere; iii) develop new partnerships with data providers; and iv) inform and oversee the development of world-leading training and capability building in Big Social Data Analytics;4. Exploring options for the sustainable processing of social media analytics within UK HE research infrastructure and providing an options paper for use by existing ESRC big data investments, and ultimately Phase 3 of the network.

成立社会数据科学实验室的使命是使学术、公共和第三部门对大数据的访问民主化，并支持用于研究、政策和实践的实时社会数据分析。拟议的能力项目旨在解决我们为社会研究目的收集大数据的能力方面现有的技术和方法上的缺陷。特别是，该项目将向学术、公共和第三部门研究人员提供增强和可持续的社交媒体数据收集和分析技术。这一能力项目将通过以下方式实现这一点：1.提供所需的技术资源和专业知识，以：i)优化现有的实验室社交媒体分析技术，以便更有效地跨操作平台(Windows、Linux、Mac OS)收集、转换和分析社交媒体数据；ii)集成现有的社交媒体分析工具(如人口统计和文本分类工具)；iii)使现有的实验室工具可由研究人员社区扩展；iv)使实验室工具适应用户需求和社交媒体提供商技术的变化(即API变化)；以及v)通过专门的实验室培训和工作论文，支持研究人员的社交媒体数据和分析需求；2.提供所需的社会科学资源和专业知识，以：i)与研究人员社区联系，收集社交媒体工具需求；ii)与ESRC行政、地方政府和消费者大数据中心联系；iii)编写培训材料并协调能力建设活动；以及iv)支持研究人员的数据和分析查询；3.确保研究人员有必要的时间：i)管理实验室工具的优化和增强，并实施‘可持续性’商业模式；ii)管理与公共、私营和第三部门用户以及英国和其他地方的ESRC大数据网络中心的现有伙伴关系；iii)与数据提供商发展新的伙伴关系；以及iv)为大数据分析领域世界领先的培训和能力建设的发展提供信息和监督；4.探索在英国高等教育研究基础设施内可持续处理社交媒体分析的选项，并提供供现有ESRC大数据投资使用的选项文件，最终实现网络的第三阶段。

项目成果

Fuzzy Multi-task Learning for Hate Speech Type Identification

• DOI: 10.1145/3308558.3313546
• 发表时间: 2019-05
• 期刊: The World Wide Web Conference
• 作者: Han Liu;P. Burnap;Wafa Alorainy;M. Williams

The Effect of the Brexit Vote on the Variation in Race and Religious Hate Crimes in England, Wales, Scotland and Northern Ireland

英国脱欧公投对英格兰、威尔士、苏格兰和北爱尔兰种族和宗教仇恨犯罪变化的影响

• DOI: 10.1093/bjc/azac071
• 发表时间: 2023
• 期刊: The British Journal of Criminology
• 作者: Williams M

Antisemitism on Twitter: Collective Efficacy and the Role of Community Organisations in Challenging Online Hate Speech

• DOI: 10.1177/2056305120916850
• 发表时间: 2020-04-01
• 期刊: SOCIAL MEDIA + SOCIETY
• 影响因子: 5.2
• 作者: Ozalp, Sefa;Williams, Matthew L.;Mostafa, Mohamed
• 通讯作者: Mostafa, Mohamed

A Fuzzy Approach to Text Classification With Two-Stage Training for Ambiguous Instances

• DOI: 10.1109/tcss.2019.2892037
• 发表时间: 2019-03
• 期刊: IEEE Transactions on Computational Social Systems
• 影响因子: 5
• 作者: Han Liu;P. Burnap;Wafa Alorainy;M. Williams

Disrupting networks of hate: characterising hateful networks and removing critical nodes

• DOI: 10.1007/s13278-021-00818-z
• 发表时间: 2022-12-01
• 期刊: SOCIAL NETWORK ANALYSIS AND MINING
• 影响因子: 2.8
• 作者: Alorainy, Wafa;Burnap, Pete;Giommoni, Luca
• 通讯作者: Giommoni, Luca