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  5. Spreading the News: How Can Journalists Gain More Engagement for their Tweets
 
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Spreading the News: How Can Journalists Gain More Engagement for their Tweets

Author(s)
Orellana-Rodriguez, Claudia  
Greene, Derek  
Keane, Mark T.  
Uri
http://hdl.handle.net/10197/8427
Date Issued
2016-05-25
Date Available
2017-04-18T14:27:14Z
Abstract
News media face many serious concerns as their distribution channels are gradually being taken over by third parties (e.g., people sharing news on Twitter and Facebook, and GoogleNews acting as a news aggregator). If traditional media is to survive at all, it needs to develop innovative strategies around these channels, to maximize audience engagement with the news they provide. In this paper, we focus on the issue of developing one such strategy for spreading news on Twitter. Using a corpus of 1M tweets from 200 journalist Twitter accounts and audience responses to these tweets, we develop predictive models to identify the features of both journalists and news tweets that impact audience attention. These analyses reveal that different combinations of features influence audience engagement differentially from one news category to the next (e.g., sport versus business). From these findings, we propose a set of guidelines for journalists, designed to maximize engagement with the news they tweet. Finally, we discuss how such analyses can inform innovative dissemination strategies in digital media.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Start Page
107
End Page
116
Copyright (Published Version)
2016 ACM
Subjects

Machine learning

Statistics

Computational journal...

Social media

Audience engagement

News events

DOI
10.1145/2908131.2908154
Language
English
Status of Item
Peer reviewed
Journal
Nejdl, W., Hall, W., Parigi, P. and Staab, S. (eds.). WebSci '16: Proceedings of the 8th ACM Conference on Web Science
Conference Details
ACM Web Science 2016 (WebSci ’16), Hannover, Germany, 22-25 May 2016
ISBN
9781450342087
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

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414.47 KB

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Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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