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What Makes a Tweet Fly? Analysis of Twitter Messaging at Four Infection Control Conferences

Published online by Cambridge University Press:  22 August 2017

Brett G. Mitchell*
Affiliation:
Faculty of Arts, Nursing and Theology, Avondale College of Higher Education, Wahroonga, New South Wales, Australia School of Nursing and Midwifery, Griffith University, Nathan, Queensland, Australia
Philip L. Russo
Affiliation:
Faculty of Arts, Nursing and Theology, Avondale College of Higher Education, Wahroonga, New South Wales, Australia School of Nursing and Midwifery, Griffith University, Nathan, Queensland, Australia School of Nursing and Midwifery, Deakin University, Burwood, Victoria, Australia
Jonathan A. Otter
Affiliation:
National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare-Associated Infection and Antimicrobial Resistance, Imperial College London in partnership with Public Health England (PHE), London, United Kingdom
Martin A. Kiernan
Affiliation:
Richard Wells Research Centre, College of Nursing, Midwifery and Healthcare, The University of West London, United Kingdom
Landon Aveling
Affiliation:
Faculty of Arts, Nursing and Theology, Avondale College of Higher Education, Wahroonga, New South Wales, Australia
*
Address correspondence to: Brett G. Mitchell, School of Nursing, Clinical Education Centre, 185 Fox Valley Road, Wahroonga, NSW, Australia, 2076 (brett.mitchell@avondale.edu.au and Twitter: @1healthau).

Abstract

OBJECTIVE

To examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences.

DESIGN

A cross-sectional study.

METHODS

An independent company was commissioned to undertake a Twitter ‘trawl’ each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of ‘retweets.’

RESULTS

In total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9–2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7–2.4) and the media (OR, 1.8; 95% CI, 1.6–2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05–0.08).

CONCLUSION

Twitter is a useful tool for information sharing and networking at infection control conferences.

Infect Control Hosp Epidemiol 2017;38:1271–1276

Type
Original Articles
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

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