The Journal of Web Science > Vol 3 > Issue 2

Spreading One’s Tweets: How Can Journalists Gain Attention for their Tweeted News?

Claudia Orellana-Rodriguez, University College Dublin, Ireland, Derek Greene, University College Dublin, Ireland, Mark T. Keane, University College Dublin, Ireland
Suggested Citation
Claudia Orellana-Rodriguez, Derek Greene and Mark T. Keane (2017), "Spreading One’s Tweets: How Can Journalists Gain Attention for their Tweeted News?", The Journal of Web Science: Vol. 3: No. 2, pp 16-31.

Publication Date: 07 Dec 2017
© 2017 C. Orellana-Rodriguez, D. Greene, and M. T. Keane
Computational journalismSocial mediaNews eventsTwitterAttention to NewsJournalism


Open Access

This is published under the terms of CC BY-NC-ND 2.0.

In this article:
1. Introduction 
2. Related Work 
3. Do News Categories Differ? 
4. Predicting Engagement 
5. Guidelines: Helping Journalists Gain Attention 
6. Conclusion: Caveats, Criticisms & Future Work 


Traditional news media face many serious concerns as their distribution channels are gradually being taken over by third parties (e.g., bloggers, citizen journalists, and news aggregators). If traditional media is to remain competitive, it needs to develop innovative strategies around these channels, to maximize audience engagement with the news it provides. In this paper, we focus on the issue of developing one such strategy for spreading news on Twitter. Using tweet corpora from two national news ecosystems – 1.7M tweets from 200 journalists in Ireland and 1.2M tweets from 364 journalists in the UK – and audience responses to these tweets, we develop predictive models to identify the features of 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). Using these findings, we suggest a set of guidelines for journalists, designed to help them maximize engagement with the news they tweet. Finally, we discuss how such analyses can inform innovative dissemination strategies in digital media.