Social media mining for journalism

Pages2-6
Published date11 February 2019
DOIhttps://doi.org/10.1108/OIR-02-2019-395
Date11 February 2019
AuthorArkaitz Zubiaga,Bahareh Heravi,Jisun An,Haewoon Kwak
Guest editorial
Social media mining for journalism
The exponential growth of social media as a central communication practice, and its
agility in capturing and announcing breaking news events more rapidly than traditional
media, has changed the journalistic landscape: social media has been adopted as a
significant source by professional journalists, and conversely, citizens are able to use
social media as a form of direct reportage. This brings along new opportunities for
newsrooms and journalists by providing new means for newsgathering through access to
a wealth of citizen reportage and updates about current affairs, as well as an additional
showcase for news dissemination.
In addition to being a big opportunity and having changed the day-to-day practices in
the newsrooms, social media has introduced a number of challenges when it comes to
newsgathering, verification, production, reporting and dissemination. These include
real-time monitoring of streams, event detection, noise filtering, contextualisation, source
and content verification, fact checking, annotation and archiving. The development of
more advanced algorithms and tools for journalists requires not only furthering research in
computational techniques, but also engaging more closely with journalists to understand
how they work, what problems they are facing when using social media and how their
day-to-day workflows can be improved.
Social media are increasingly becoming the go-to platforms to get the news. A 2018
survey by the Pew Research Center found that as many as 62 per cent Americans use social
media to get the news[1]. Likewise, news organisations are now employing full-time social
media editors, and major news organisations such as Reuters[2] or the BBC[3] recommend
their journalists to make frequent use of social media.
Research looking into social media use in journalism has also increased substantially in
recent years. After Kwak et al.s (2010) work highlighting the presence of news in social
media, now cited over 5,000 times, an increasing number of works have studied social media
as a platform that can be leveraged, inter alia, for researching, gathering and verifying
breaking news (Diakopoulos et al., 2012; Heravi and Harrower, 2016; Tolmie et al., 2017;
Zubiaga et al., 2018; Konstantinovskiy et al., 2018), for broadening the audience by
maximising the diffusion of news (Diakopoulos and Zubiaga, 2014; McCollough et al., 2017)
or for news analytics (Castillo et al., 2014; Zubiaga et al., 2016).
This special section provides a gateway to look into a variety of research questions
from both theoretical and practical perspectives. We highlighted four major topics of
interest to the special section when we launched the call for papers. These include:
newsgathering from social media, aiming to study algorithmic approaches to facilitating
collection and research around newsworthy content with social media as a source
(Zubiaga, 2018; Khare et al., 2015; Heravi et al., 2014); social media news analytics,
wheretheobjectiveistoanalysenewsreadership from the perspective of social media as
well as to perform additional analyses that give insights into how news circulates
and is consumed online (Diakopoulos et al., 2010); data and computational journalism,
which aims to leverage social media data to enable computationally assisted production of
journalistic content (Gray et al., 2012; Heravi and McGinnis, 2015; Heravi, 2018);
and ethics and digital citizenship, where ethical aspects of gathering eyewitness content
Online Information Review
Vol. 43 No. 1, 2019
pp. 2-6
© Emerald PublishingLimited
1468-4527
DOI 10.1108/OIR-02-2019-395 This paper forms part of a special section Social media mining for journalism.
2
OIR
43,1

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