Between 2016 and 2021 I have been exploring how to use social media and social network analysis to understand healthcare and public health topics. The list of peer reviewed papers and blogs below (click “Continue reading” below) – and the brief description beneath each reference – provides a summary of this work. I have tried to keep each publication original, making new discoveries and advances along the way. Hopefully these publications, and the blogs and pages on the ScotPublicHealth site, will help others make further advances over time, and also understand the pitfalls in social media analysis.
Thank you to all co-authors who have helped make this such an enlightening and enjoyable body of work. It has been a truly international collaboration, across multiple clinical fields, with new connections from Hong Kong, across Europe, and North America, plus Australasia and South America along the way in conference abstracts and social media conference summaries.
This concludes planned work on this topic, though I do have a lot of data saved – e.g. on #FOAMed, #VaccinesWork, #Covid19UK and other topics, that could be analysed more fully at a future date.
Dr Graham Mackenzie, GPST3, Edinburgh, Scotland
DG Mackenzie. Improving the quality and impact of public health social media activity in Scotland during 2016: #ScotPublicHealth. JPH 2017 https://doi.org/10.1093/pubmed/fdx066
Describes efforts to bring together tweeting across the Scottish Public Health community.
G Mackenzie, AD Murray, CW Oliver. Virtual attendance at an international physical activity meeting using Twitter – How can data visualisation provide a presence? BJSM 2017 http://dx.doi.org/10.1136/bjsports-2016-097373
An early look at how social network analysis can describe social media activity at an international conference (even when you’re not there). Used automated NodeXL summary reports to provide a quick snapshot.
G Mackenzie. Twitter big data and infectious disease conferences. Lancet Infectious Diseases 2018 https://doi.org/10.1016/S1473-3099(18)30011-2
Brought together a few conference summaries, using the most retweeted posts.
Sarah Hudson and Graham Mackenzie. “Not your daughters Facebook”: Twitter Use at the European Society of Cardiology Conference 2018. Heart (British Cardiac Society) October 2018. http://dx.doi.org/10.1136/heartjnl-2018-314163
Looked at the content of the most shared posts at a cardiology conference.
Kjetil Søreide, Graham Mackenzie, Karol Polom, Laura Lorenzon, Helen Mohan, Julio Mayol. Tweeting the meeting: Quantitative and qualitative twitter activity during the 38th ESSO conference. EJSO February 2019. https://doi.org/10.1016/j.ejso.2018.11.020
Used methods introduced in BJSM blog (see below) to describe social media “influencers” at a medical conference.
Jeremy Yuen-Chun, Graham Mackenzie, Marc Smith. Social Media Analytics: What You Need to Know as a Urologist. European Urology Focus 2019. https://doi.org/10.1016/j.euf.2019.08.005
Provided an overview of the techniques as applied to a urology conference.
Cevik M, Ong DSY, Graham Mackenzie. How scientists and physicians use Twitter during a medical congress. Clinical Microbiology and Infection 2019. https://doi.org/10.1016/j.cmi.2019.04.030
Used multivariable analysis of tweeting at ECCMID infectious diseases conference to dissect the importance of different tweet components (see also ACSCC18 paper).
Alaa El-Hussuna, Pär Myrelid, Stefan D. Holubar, Paulo G. Kotze, Graham Mackenzie et al. Biological treatment and the potential risk of adverse postoperative outcome in patients with inflammatory bowel disease: An open source expert panel review of the current literature and future perspectives. Crohn Colitis 360 2019. https://doi.org/10.1093/crocol/otz021
Provided social media metrics around an open source research project coordinated via tweets.
R Grossman, D Mackenzie, D Keller, N Dames, P Grewal, et al. #SoMe4Surgery: from inception to impact. BMJ Innovations 2020. http://dx.doi.org/10.1136/bmjinnov-2019-000356
A long range view of the #SoMe4Surgery network, combining data over a period of 5 months.
Antonio Passaro*, Graham Mackenzie*, Matteo Lambertini*, Gilberto Morgan, Stefan Zimmerman, Pilar Garrido, Giuseppe Curigliano & Dario Trapani.
*contributed equally. European Society for Medical Oncology (ESMO) 2018 Congress Twitter analysis: from ethics to results through the understanding of communication and interaction flows. ESMO Open 2020. http://dx.doi.org/10.1136/esmoopen-2019-000598
An analysis of an oncology conference, separating out commercial influencers.
Graham Mackenzie, Kjetil Søreide, Karol Polom, Laura Lorenzon, Helen Mohan, Delia Cortés Guiral, Julio Mayol. Beyond the hashtag – an exploration of tweeting and replies at the European Society of Surgical Oncology 39th clinical conference (ESSO39). EJSO 2020. doi:10.1016/j.ejso.2020.02.018
A follow on to the ESSO38 conference, looking at replies as well as tweets that used the hashtag at ESSO39 (see also #BJSConnect paper).
Graham Mackenzie, Martha Gulati, C. Michael Gibson. The American College of Cardiology Scientific Sessions 2019: Impact of Twitter, Hashtag Drift and Confusion. ACC.org/Cardiology Magazine online publication 2020. https://www.acc.org/latest-in-cardiology/articles/2020/03/26/12/42/acc19-impact-of-twitter-hashtag-drift-and-confusion
An exploration of the confusion arising when multiple events use the same hashtag at the same time.
D. Graham Mackenzie, Sarah Hudson, Martha Gulati. Who influences tweeting at international cardiology conferences? European Heart Journal 2020. https://doi.org/10.1093/eurheartj/ehaa162
Looked at influencers across 3 international conferences, and whether tweeting removes the usual conference hierarchy.
Sharp SP*, Mackenzie DG*, Ong DSY*, Mountziaris PM, Logghe HJ, Ferrada P, Wexner, SD. Factors influencing the dissemination of tweets at the American College of Surgeons Clinical Congress 2018. American Surgeon 2020. https://doi.org/10.1177/0003134820950680
Used similar method to ECCMID conference, using multivariable analysis to dissect the importance of different tweet components at a surgical conference.
Mackenzie G, Gulati M. ACC.20: Impact of Social Media at the Virtual Scientific Sessions During the COVID-19 Pandemic. Clinical Cardiology 2020. https://doi.org/10.1002/clc.23387
Looked at dialogue beyond the hashtag, and compares 3rd party analysis tools with data direct from Twitter.
Mackenzie G, Grossman R, Mayol J. Beyond the hashtag – describing and understanding the full impact of the #BJSConnect tweet chat May 2019. BJS Open 2020. https://doi.org/10.1093/bjsopen/zraa019
As with the ESSO39 paper this looked at replies beyond the hashtag, but this time for a tweet chat.
Mackenzie DG, Ong DSY, Ashiru-Oredope D. World Antibiotic Awareness Week and European Antibiotic Awareness Day, November 2018: An analysis of the impact of Twitter activity. IJAA 2000. https://doi.org/10.1016/j.ijantimicag.2020.106209
Explored the impact of different hashtags in global and European antibiotic awareness campaigns, using multivariable analysis. It also (in supplementary materials) demonstrates how to look at historical activity on Twitter using methods described in a ScotPublicHealth blog.
Martischang, R., Tartari, E., Kilpatrick, C. Mackenzie G et al. Enhancing engagement beyond the conference walls: analysis of Twitter use at #ICPIC2019 infection prevention and control conference. Antimicrob Resist Infect Control 10, 20 (2021). https://doi.org/10.1186/s13756-021-00891-1
Used artificial intelligence (unsupervised learning) and Bayesian approaches to study conference tweeting, and quantifies unique audience (total number of followers and number interacting through replies and retweeting).
Quentin Durand-Moreau, Graham Mackenzie, Anil Adisesh, Sebastian Straube, Xin Hui S Chan, Nathan Zelyas, Trisha Greenhalgh, Twitter Analytics to Inform Provisional Guidance for COVID-19 Challenges in the Meatpacking Industry, Annals of Work Exposures and Health, 2021. https://doi.org/10.1093/annweh/wxaa123
Used social media data to capture a broad range of news stories around Covid-19 in meat processing plants.
O. Sgarbura, G. Mackenzie, M.Holmberg, SJ Wigmore, K. Soreide. Social Media for the Hepato-Pancreato-Biliary community (#SoMe4HPB): connecting a specialized online group for scientific and clinical knowledge dissemination. https://doi.org/10.1016/j.hpb.2021.01.017
Used a NodeXL “user search” to collect information over a longer period on a surgical topic.
Graham Mackenzie. A year and a day of #Covid19uk tweets. Lancet Infectious Diseases 2021 https://doi.org/10.1016/S1473-3099(21)00222-X
Used NodeXL analysis of TAGS data over a period of over a year to produce a summary of 366 days in 366 tweets by 366 Twitter users, accompanied by a graph of new tweeters each day to look at peak UK interest in the pandemic (e.g. coinciding with early days of pandemic, government announcements, and first anniversary of lockdown).
Blogs in BMJ stable of journals
Social media activity at ISPAH 2018: running to keep up. Blog by Graham Mackenzie 2018. https://blogs.bmj.com/bjsm/2018/11/26/social-media-activity-at-ispah-2018-running-to-keep-up/
Introduces Venn diagram approach to describing potential social media influencers at a conference.
Graham Mackenzie, Trish Greenhalgh. Learning about COVID-19 outbreaks in meatpacking plants from non-viral tweets. BMJ Opinion, 2020. https://blogs.bmj.com/bmj/2020/05/29/learning-about-covid-19-outbreaks-from-non-viral-tweets/
Uses NodeXL graph gallery reports from multiple searches to source a large number of news stories about Covid-19 in meat processing plants (see also AWEH paper).
Mackenzie G. Viewing the covid-19 pandemic through the lens of social media. BMJ Opinion, 2020. https://blogs.bmj.com/bmj/2020/10/12/graham-mackenzie-viewing-the-covid-19-pandemic-through-the-lens-of-social-media/
Uses NodeXL data to capture tweeting about Covid-19 during the early stages of lockdown in the UK.