Social Media - Developing Understanding, Infrastructure & Engagement (Social Media Enhancement)

社交媒体 - 发展理解、基础设施

• 批准号: ES/M001628/1
• 负责人: Peter Edwards
• 金额: $ 69.05万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FM001628%2F1
• 关键词: Social; Media; Developing; Understanding; Infrastructure

There is now a broad consensus that new forms of social data emerging from people's day-to-day activities on the Web (Twitter, Facebook, etc.) have the potential to transform the social sciences. However, there is also agreement that the current analytical techniques fall short of the standards required for academic research and policy making. Areas in which social media data have the potential to provide insights include: social order and civil society, politics and policy making, sentiment, commerce, health, information and sentiment diffusion, creativity and the arts. In this proposal we outline the case for an enhancement to our existing funding for the RCUK dot.rural Digital Economy Hub (based at the University of Aberdeen) to support investigations into the challenges surrounding social media data and the social sciences. Aspects of the work will involve analysis of social media data in a number of contexts, including: transport disruption around the 2014 Commonwealth Games (Glasgow), news stories about Scottish independence and UK-EU relations, island communities in the Western Isles. Guided by insights from these case studies we will: - develop a suite of software tools to support various aspects of data analysis and curation; - provide guidance on ethical considerations surrounding analysis of social media data; and- deliver training workshops for social science researchers.Finally, researchers will attend a range of festivals (food, music and science) to engage the public on this important issue.

现在有一个广泛的共识，即从人们在网络上的日常活动（Twitter， Facebook等）中出现的新形式的社会数据有可能改变社会科学。然而，人们也一致认为，目前的分析技术还达不到学术研究和政策制定所需的标准。社交媒体数据有可能提供见解的领域包括：社会秩序和公民社会、政治和政策制定、情感、商业、健康、信息和情感传播、创造力和艺术。在本提案中，我们概述了增强RCUK .农村数字经济中心（位于阿伯丁大学）现有资金的案例，以支持对社交媒体数据和社会科学挑战的调查。这项工作的各个方面将涉及在许多背景下分析社交媒体数据，包括：2014年英联邦运动会（格拉斯哥）期间的交通中断，关于苏格兰独立和英国-欧盟关系的新闻报道，西部群岛的岛屿社区。根据这些案例研究的见解，我们将：-开发一套软件工具，以支持数据分析和管理的各个方面；-就社交媒体数据分析的道德考量提供指导；并为社会科学研究人员提供培训讲习班。最后，研究人员将参加一系列节日（食品、音乐和科学），让公众参与到这个重要问题上。

项目成果

A Curated Corpus for Sentiment-Topic Analysis

• 发表时间: 2016-05
• 作者: Ebuka Ibeke;Chenghua Lin;Christopher Coe;A. Wyner;Dong Liu;M. Barawi;N. Yusof

The social sciences and the web: From 'Lurking' to interdisciplinary 'Big Data' research

社会科学和网络：从“潜伏”到跨学科“大数据”研究

• DOI: 10.1177/2059799116630665
• 发表时间: 2016
• 期刊: Methodological Innovations
• 作者: Bone J

ADOVA: Anomaly Detection in Online and Virtual spAces

ADOVA：在线和虚拟空间中的异常检测

• 发表时间: 2015
• 作者: Emele CD

A novel artificial bee colony based clustering algorithm for categorical data.

• DOI: 10.1371/journal.pone.0127125
• 发表时间: 2015
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Ji J;Pang W;Zheng Y;Wang Z;Ma Z
• 通讯作者: Ma Z

Statistics-Based Lexical Choice for NLG from Quantitative Information

基于统计的 NLG 定量信息词汇选择

• 发表时间: 2016
• 作者: Li X