Authors:
Vânia Moutinho
1
;
Pavel Brazdil
1
and
João Cordeiro
2
Affiliations:
1
LIAAD, INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200, Porto and Portugal
;
2
LIAAD, INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200, Porto, Portugal, HULTIG – Centre of Human Language Technology and Bioinformatics, Universidade da Beira Interior, Rua Marquês d’ Ávila e Bolama, 6200, Covilhã and Portugal
Keyword(s):
Text Mining, Temporal Analysis, Clustering of News, Evolution of Occurrence, Time-wise Differences.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Clustering and Classification Methods
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Text and Semi-Structured Data
;
Soft Computing
;
Symbolic Systems
;
Web Mining
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 evol
ution 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.
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