NewsTweet: A Dataset of Social Media Embedding in Online Journalism
Abstract
The inclusion of social media posts---tweets, in particular---in digital news stories, both as commentary and increasingly as news sources, has become commonplace in recent years. In order to study this phenomenon with sufficient depth, robust large-scale data collection from both news publishers and social media platforms is necessary. This work describes the construction of such a data pipeline. In the data collected from Google News, 13% of all stories were found to include embedded tweets, with sports and entertainment news containing the largest volumes of them. Public figures and celebrities are found to dominate these stories; however, relatively unknown users have also been found to achieve newsworthiness. The collected data set, NewsTweet, and the associated pipeline for acquisition stand to engender a wave of new inquiries into social content embedding from multiple research communities.
Keywords
Cite
@article{arxiv.2008.02870,
title = {NewsTweet: A Dataset of Social Media Embedding in Online Journalism},
author = {Munif Ishad Mujib and Hunter Scott Heidenreich and Colin J. Murphy and Giovanni C. Santia and Asta Zelenkauskaite and Jake Ryland Williams},
journal= {arXiv preprint arXiv:2008.02870},
year = {2020}
}