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http://hdl.handle.net/1893/33412
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DC Field | Value | Language |
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dc.contributor.author | Ahmed, Wasim | en_UK |
dc.contributor.author | Lugovic, Sergej | en_UK |
dc.date.accessioned | 2021-10-12T07:09:32Z | - |
dc.date.available | 2021-10-12T07:09:32Z | - |
dc.date.issued | 2019-02-12 | en_UK |
dc.identifier.uri | http://hdl.handle.net/1893/33412 | - |
dc.description.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 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.iso | en | en_UK |
dc.publisher | Emerald | en_UK |
dc.relation | Ahmed 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-03-2018-0093 | en_UK |
dc.rights | Publisher 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.com | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | en_UK |
dc.subject | en_UK | |
dc.subject | Social media | en_UK |
dc.subject | Social network analysis | en_UK |
dc.subject | Fake news | en_UK |
dc.subject | Information diffusion | en_UK |
dc.subject | Bots | en_UK |
dc.title | Social media analytics: analysis and visualisation of news diffusion using NodeXL | en_UK |
dc.type | Journal Article | en_UK |
dc.identifier.doi | 10.1108/oir-03-2018-0093 | en_UK |
dc.citation.jtitle | Online Information Review | en_UK |
dc.citation.issn | 1468-4527 | en_UK |
dc.citation.volume | 43 | en_UK |
dc.citation.issue | 1 | en_UK |
dc.citation.spage | 149 | en_UK |
dc.citation.epage | 160 | en_UK |
dc.citation.publicationstatus | Published | en_UK |
dc.citation.peerreviewed | Refereed | en_UK |
dc.type.status | AM - Accepted Manuscript | en_UK |
dc.contributor.funder | University of Sheffield | en_UK |
dc.author.email | wasim.ahmed@stir.ac.uk | en_UK |
dc.citation.date | 24/10/2018 | en_UK |
dc.contributor.affiliation | Management, Work and Organisation | en_UK |
dc.identifier.isi | WOS:000458411500009 | en_UK |
dc.identifier.scopusid | 2-s2.0-85055420180 | en_UK |
dc.identifier.wtid | 1760275 | en_UK |
dc.contributor.orcid | 0000-0001-8923-1865 | en_UK |
dc.date.accepted | 2018-09-17 | en_UK |
dcterms.dateAccepted | 2018-09-17 | en_UK |
dc.date.filedepositdate | 2021-10-11 | en_UK |
rioxxterms.apc | not required | en_UK |
rioxxterms.type | Journal Article/Review | en_UK |
rioxxterms.version | AM | en_UK |
local.rioxx.author | Ahmed, Wasim|0000-0001-8923-1865 | en_UK |
local.rioxx.author | Lugovic, Sergej| | en_UK |
local.rioxx.project | Project ID unknown|University of Sheffield|http://dx.doi.org/10.13039/501100000858 | en_UK |
local.rioxx.freetoreaddate | 2021-10-11 | en_UK |
local.rioxx.licence | http://creativecommons.org/licenses/by-nc/4.0/|2021-10-11| | en_UK |
local.rioxx.filename | C0CCE3E9-CC24-4A1B-A28B-CA204A533AEB.pdf | en_UK |
local.rioxx.filecount | 1 | en_UK |
local.rioxx.source | 1468-4527 | en_UK |
Appears in Collections: | Management, Work and Organisation Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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C0CCE3E9-CC24-4A1B-A28B-CA204A533AEB.pdf | Fulltext - Accepted Version | 1.63 MB | Adobe PDF | View/Open |
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