课题基金 / 基金详情

DATADRIVEN: Data-driven campaigns: intended and unintended consequences for democracy

DATADRIVEN: Data-driven campaigns: intended and unintended consequences for democracy
数据驱动:数据驱动的运动:对民主的有意和无意的后果
批准号:
ES/XX00052/1
负责人:
Sanne Kruikemeier
金额:
$53.97万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Data-driven political campaigns are on the rise. Concerns have been voiced that practices like onlinepolitical microtargeting techniques are harmful for democracy. These concerns grew after the unexpectedoutcome of the US presidential elections in 2016, the Brexit vote in the UK, and several recent electionsin Europe. However, it is unclear if data-driven campaigns using online microtargeting techniques are anactual threat to democracy. The project will focus on both the intended and unintended consequences ofdata-driven targeting and digital persuasion. In light of ongoing political and societal turmoil, investigatinghow citizens may be persuaded in a turbulent age and in a changing media landscape has never beenmore important. The study will focus on micro (consequences for citizens), meso (consequences forpolitical elites), and macro level effects (consequences for democracy). The project will address fourresearch questions: (RQ1) How do organizations shape elections campaigns by targeting potential votersonline during elections? (RQ2) What are the constitutional and legislative frameworks shaping the extentand nature of data-driven campaigning in European countries? (RQ3) How are data-driven targetingpractices perceived? (RQ4) To what extent do data-driven targeting practices actually affect voters? Theproject is novel as it (1) extends and empirically tests a theoretical framework of data-drivencampaigning, while (2) using a mixture of research methods and a (3) comparative perspective.DATADRIVEN will offer a deeper understanding of online data-driven targeting techniques during electionsin four European countries (i.e., Netherlands, Germany, Austria, and United Kingdom).
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: