Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33412
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dc.contributor.authorAhmed, Wasimen_UK
dc.contributor.authorLugovic, Sergejen_UK
dc.date.accessioned2021-10-12T07:09:32Z-
dc.date.available2021-10-12T07:09:32Z-
dc.date.issued2019-02-12en_UK
dc.identifier.urihttp://hdl.handle.net/1893/33412-
dc.description.abstractPurpose 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 awareness” of 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 today’s news climate.en_UK
dc.language.isoenen_UK
dc.publisherEmeralden_UK
dc.relationAhmed W & Lugovic S (2019) Social media analytics: analysis and visualisation of news diffusion using NodeXL. Online Information Review, 43 (1), pp. 149-160. https://doi.org/10.1108/oir-03-2018-0093en_UK
dc.rightsPublisher policy allows this work to be made available in this repository. Published in Online Information Review by Emerald. Ahmed, W. and Lugovic, S. (2019), "Social media analytics: analysis and visualisation of news diffusion using NodeXL", Online Information Review, Vol. 43 No. 1, pp. 149-160. The original publication is available at: https://doi.org/10.1108/OIR-03-2018-0093. This author accepted manuscript is deposited under a Creative Commons Attribution Non-commercial 4.0 International (CC BY-NC) licence. This means that anyone may distribute, adapt, and build upon the work for non-commercial purposes, subject to full attribution. If you wish to use this manuscript for commercial purposes, please contact permissions@emerald.comen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en_UK
dc.subjectTwitteren_UK
dc.subjectSocial mediaen_UK
dc.subjectSocial network analysisen_UK
dc.subjectFake newsen_UK
dc.subjectInformation diffusionen_UK
dc.subjectBotsen_UK
dc.titleSocial media analytics: analysis and visualisation of news diffusion using NodeXLen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1108/oir-03-2018-0093en_UK
dc.citation.jtitleOnline Information Reviewen_UK
dc.citation.issn1468-4527en_UK
dc.citation.volume43en_UK
dc.citation.issue1en_UK
dc.citation.spage149en_UK
dc.citation.epage160en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderUniversity of Sheffielden_UK
dc.author.emailwasim.ahmed@stir.ac.uken_UK
dc.citation.date24/10/2018en_UK
dc.contributor.affiliationManagement, Work and Organisationen_UK
dc.identifier.isiWOS:000458411500009en_UK
dc.identifier.scopusid2-s2.0-85055420180en_UK
dc.identifier.wtid1760275en_UK
dc.contributor.orcid0000-0001-8923-1865en_UK
dc.date.accepted2018-09-17en_UK
dcterms.dateAccepted2018-09-17en_UK
dc.date.filedepositdate2021-10-11en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorAhmed, Wasim|0000-0001-8923-1865en_UK
local.rioxx.authorLugovic, Sergej|en_UK
local.rioxx.projectProject ID unknown|University of Sheffield|http://dx.doi.org/10.13039/501100000858en_UK
local.rioxx.freetoreaddate2021-10-11en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nc/4.0/|2021-10-11|en_UK
local.rioxx.filenameC0CCE3E9-CC24-4A1B-A28B-CA204A533AEB.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1468-4527en_UK
Appears in Collections:Management, Work and Organisation Journal Articles

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