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Data for Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-written vs. Automated News

DataONE2020-06-08 更新2024-06-08 收录

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读者感知

数据链接：

https://search.dataone.org/view/sha256:1504d6dfac35bcc27a70b6221e12141cbe263ed4fc6a6776e9c75fef217189a2 数据链接链接失效反馈

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资源简介：

Provides the coding for the paper \"Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-written vs. Automated News\"

应用场景：

创建时间：

2023-11-22

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读者感知

We conducted an online experiment to study people’s perception of automated computer-written news. Using a 2 2 2 design, we varied the article topic (sports, finance; within-subjects) and both the a

DataCite Commons2025-05-11 更新290

Replication Data for: \"Automatisch interessant?\"

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受众研究

This is the full dataset as well as the R script and stimuli to replicate results from the manuscript by Andreas Graefe and myself on the influence of involvement on the perception of computer-generat

DataONE2017-03-14 更新70

Factors Influencing the Rejection of Automated Journalism: A Systematic Literature Review

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新闻编辑室接受度

Purpose: Automation in journalistic processes is increasingly being discussed in media research and practice. Automated journalism (AJ) enables the fast production of numerous articles in real-time an

DataCite Commons2022-06-03 更新70

RA-MDS

文档摘要

读者感知

RA-MDS数据集是由香港中文大学和腾讯AI实验室合作创建，专注于读者感知的多文档摘要问题。该数据集包含45个主题，每个主题涉及10篇新闻文档和平均215条读者评论，总计约19,000个标注的方面。数据集的创建过程涉及专家进行数据收集、方面标注和摘要撰写。RA-MDS数据集旨在通过结合新闻文档和读者评论，提高多文档摘要的质量，特别关注于捕捉读者兴趣和新闻内容的关键信息，以生成更全面和准确的摘要。

arXiv2017-08-03 更新190

Replication Data for: "Automatisch interessant?"

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用户参与度研究

NIAID Data Ecosystem70