Association and Temporality between News and Tweets

Vânia Moutinho, Pavel Brazdil, João Cordeiro

2019

Abstract

With the advent of social media, the boundaries of mainstream journalism and social networks are becoming blurred. User-generated content is increasing, and hence, journalists dedicate considerable time searching platforms such as Facebook and Twitter to announce, spread, and monitor news and crowd check information. Many studies have looked at social networks as news sources, but the relationship and interconnections between this type of platform and news media have not been thoroughly investigated. In this work, we have studied a series of news articles and examined a set of related comments on a social network during a period of six months. Specifically, a sample of articles from generalist Portuguese news sources published on the first semester of 2016 was clustered, and the resulting clusters were then associated with tweets of Portuguese users with the recourse to a similarity measure. Focusing on a subset of clusters, we have performed a temporal analysis by examining the evolution of the two types of documents (articles and tweets) and the timing of when they appeared. It appears that for some stories, namely Brexit and the European Football Cup, the publishing of news articles intensifies on key dates (event-oriented), while the discussion on social media is more balanced throughout the months leading up to those events.

Paper Citation

in Harvard Style

Moutinho V., Brazdil P. and Cordeiro J. (2019). Association and Temporality between News and Tweets. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 500-507. DOI: 10.5220/0008362105000507

in Bibtex Style

@conference{kdir19,
author={Vânia Moutinho and Pavel Brazdil and João Cordeiro},
title={Association and Temporality between News and Tweets},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={500-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008362105000507},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - Association and Temporality between News and Tweets
SN - 978-989-758-382-7
AU - Moutinho V.
AU - Brazdil P.
AU - Cordeiro J.
PY - 2019
SP - 500
EP - 507
DO - 10.5220/0008362105000507
PB - SciTePress