Social media analytics: analysis and visualisation of news diffusion using NodeXL

Pages149-160
Date11 February 2019
Publication Date11 February 2019
DOIhttps://doi.org/10.1108/OIR-03-2018-0093
AuthorWasim Ahmed,Sergej Lugovic
SubjectLibrary & information science,Information behaviour & retrieval,Collection building & management,Bibliometrics,Databases,Information & knowledge management,Information & communications technology,Internet,Records management & preservation,Document management
Social media analytics: analysis
and visualisation of news
diffusion using NodeXL
Wasim Ahmed
Northumbria University, Newcastle upon Tyne, UK, and
Sergej Lugovic
Zagreb University of Applied Sciences, Zagreb, Croatia
Abstract
Purpose The purpose of this paper is to provide an overview of NodeXL in the context of news diffusion.
Journalists often include a social media dimension in their stories but lack the tools to get digital photos of the
virtual crowds about which they write. NodeXL is an easy to use tool for collecting, analysing, visualising and
reporting on the patterns found in collections of connections in streams of social media. With a network map
patterns emerge that highlight key people, groups, divisions and bridges, themes and related resources.
Design/methodology/approach This study conducts a literature review of previous empirical work
which has utilised NodeXL and highlights the potential of NodeXL to provide network insights of virtual
crowds during emerging news events. It then develops a number of guidelines which can be utilised by news
media teams to measure and map information diffusion during emerging news events.
Findings One emergent software application known as NodeXL has allowed journalists to take group photos
of the connections among a group of users on social media. It was found that a diverse range of disciplines utilise
NodeXL in academic research. Furthermore, based on the features of NodeXL, a number of guidelines were
developed which provide insight into how to measure and map emerging news events on Twitter.
Social implications With a set of social media network images a journalist can cover a set of social media
content streams and quickly grasp situational awarenessof the shape of the crowd. Since social media
popular support is often cited but not documented, NodeXL social media network maps can help journalists
quickly document the social landscape utilising an innovative approach.
Originality/value This is the first empirical study to review literature on NodeXL, and to provide insight
into the value of network visualisations and analytics for the news media domain. Moreover, it is the first
empirical study to develop guidelines that will act as a valuable resource for newsrooms looking to acquire
insight into emerging news events from the stream of social media posts. In the era of fake news and
automated accounts, i.e., bots the ability to highlight opinion leaders and ascertain their allegiances will be of
importance in todays news climate.
Keywords Twitter, Social media, Social network analysis, Fake news, Information diffusion, Bots
Paper type Research paper
Introduction
Social media platforms generate substantial amounts of information on a range of topics
and have become important channels of information flow in the twenty-first century (Bruns
et al., 2014). Originally, social media were created to allow members of the public to connect
to one another for personal use but their use now stretches beyond this. One area that has
benefited from the advent of social media is newsrooms because journalists are likely to
include a social media element to their stories. Indeed, citizens may now also expect media
sources to provide a social media element. One social media platform that has risen in
popularity for its ability to diffuse news rapidly across the world is Twitter.
Twitter boasts an impressive 328m monthly active users with 1bn unique visits to
tweets across the World Wide Web (About Twitter, n.d.), and Twitter is utilised by a
subset of the global human population (Ahmed, 2017; Andrew Perrin, 2015; Holmberg and
Thelwall, 2014). Due to the number of active users of Twitter emerging news events may
appear to be reported on Twitter prior to reaching traditional media outlets. It is not
surprising, therefore, that tweets in themselves have become to appear on television and
Online Information Review
Vol. 43 No. 1, 2019
pp. 149-160
© Emerald PublishingLimited
1468-4527
DOI 10.1108/OIR-03-2018-0093
Received 15 March 2018
Revised 18 June 2018
15 September 2018
Accepted 17 September 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1468-4527.htm
149
Social media
analytics

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