The Royal College of General Practitioners Annual Conference (RCGPAC) 2019 has embraced the use of social media to disseminate information to conference delegates and a wider audience beyond the conference hall. In an experiment at RCGPAC 2019, social media analysis was shared live from the conference hall throughout the conference, summarising the top content, identifying the main contributors and encouraging delegates to use the conference hashtag (#RCGPAC) to aid identification and dissemination of tweets. This idea emerged after an analysis of tweeting from the 2018 conference showed that a substantial proportion of tweets had omitted the official conference hashtag and were therefore less likely to reach their intended audience. Throughout the conference I shared social media analysis in a tweet thread and an ongoing Wakelet summary capturing the most popular tweets. This analysis has, in turn, fed into GP Online articles.
Conferences are an important way of sharing new medical and scientific knowledge. Twitter is an important way of summarising and sharing information from conference. This blog sets out to answer the question: “Have we reached peak tweeting at medical conferences?”. Popular social media tools produce quite misleading results, combining tweets and retweets, tweeters and retweeters, reporting potentially huge audiences based on questionable assumptions. Instead, this analysis uses raw data, breaking down results for tweeters and retweeters. It reports on 3 years of tweeting (2016-18) about four conferences (two public health, one anaesthetics, one quality improvement conference). The answer to the question whether we have passed peak tweeting is: “It’s too early to say whether we have passed the peak, but we quite possibly have, and conference tweeting is certainly evolving”.
Now of course 3 data points do not demonstrate a trend: you need 10-12 points or more for a run chart. Nonetheless, it is of interest that compared with 2017 there were fewer people generating original content at each of these medical conferences in 2018. These four conferences had quite different contributors and audiences, but the findings are consistent. Perhaps the pattern is real, and reflective of wider changes in conference tweeting. The number of tweets also dropped overall, but that may be explained by an increase in number of characters allowed in a tweet (from 140 to 280, November 2017). There was also less retweeting between 2017 and 2018 for three of the conferences.
Nonetheless, there is great content out there, and conference tweeting is maturing, and is likely to continue to evolve. We see the emergence of rapporteurs, specifically setting out to record the conference proceedings in imaginative ways. The Intensive Care Society State of the Art conference is leading the way in this area, and Helen Bevan and colleagues at NHS Horizons continue to generate fabulous content in their general and conference tweeting.
I also highlight that there are some limitations to current social network analysis:
- Reports of conference audience/ reach on social media (Symplur, Twitonomy, Followthehashtag) are typically wildly optimistic and should be ignored. Their reports on influencers are potentially useful, but should be interpreted with caution.
- Replies that do not use the conference hashtag are not captured, and sometimes include rich information. This requires more sophisticated tools and analytical approaches adopted from qualitative research methods.
- Retweets are under-represented in NodeXL reports, and this can sometimes result in very odd results.
That’s me signing out of social media analysis for the time being. I’m off to retrain as a GP, returning to a clinical training grade for the first time in almost 20 years.
Recently we had a discussion about communication in one of our teams. It’s a regular bugbear in any department:
- Do we miss important messages in the dozens or hundreds of emails we receive in a day? (Disclosure – I have switched off emails when preparing this blog, so I can concentrate)
- How should we manage circulars? (When I started work we used to have a paper system with sign off sheets that took many months to circulate around even a relatively small department. While we don’t have paper circulars any more, we still have plenty of emails with links to reports, conferences, consultations, and it remains difficult to keep on top of all this information)
- Are meetings a waste of time? (They don’t need to be, but frequently are, usually because of problems with communication. Well described by Guy Browning).
- How do we update colleagues about our work (i.e. internally)? (There are lots of different approaches – weekly information exchange, huddles, notice boards, posters, and of course quarterly and annual reports for corporate objectives)
- How do we communicate with the outside world (i.e. externally)? (Many public services still don’t even have an up to date website, let alone a blog or social media feed; also peer reviewed journals, freedom of information requests, public committees and other forums).
A group of 3 team members met to discuss options. We weren’t all sure why we were there as the meeting invite hadn’t given context, or if it had it was hidden away. At least had managed to arrive, on time, with only one person missing. We started to explore options. In the spirit of better communication I have written up the meeting as a blog that can be shared on social media.
This blog is also available as a PDF to download.
It is important for healthcare workers to understand how health news is reported. Social media provides ways to understand who makes and shares health stories, the potential audience, and the stories themselves. Back in January 2017 Prof Chris Oliver and I prepared a research paper on this topic which we submitted to two international medical journals in February and March 2017. It was not accepted for publication – perhaps it was too early for this important topic.
I came across the paper again recently when working through files as I prepare to move job (February 2019). The timing of this analysis – just at the point that Trump acquired the keys to the White House, and just when Chris and I were trying to work out what social network analysis reports could tell us – makes this a potentially important piece of work, so Chris and I have decided to share the paper in a way made possible by social media – a blog. Download the full paper here.
Over the past year I have been learning and adapting methods for studying and summarising social media activity around health conferences and awareness campaigns.
This blog ties up that work, bringing the key pieces of work together in one place. My hope is that other people and organisations can use these techniques to plan, monitor and evaluate their own social media activities.
I am taking a sabbatical over the next few months, returning to the front line of clinical work in a care of the elderly unit in a large teaching hospital. I will not be able to extract and analyse tweets between April and July (inclusive). I will continue to monitor selected campaigns that relate to the clinical attachment (eg #EndPJParalysis and #EndPJParalysis which recently announced a 70 day campaign, beginning 17 April 2018).
This blog lists the main learning points from my activities over the past year, with links to the relevant blogs.
This blog takes a real life example (the Royal College of Physicians Edinburgh Public Health symposium 2017 – #rcpePH17) to illustrate ways to use social media in planning, running and summarising the outputs of the conference. You can also read a PDF version of this blog. Read a more recent application of some of these techniques to study infectious disease conferences in a Media Watch article for Lancet Infectious Diseases (February 2018).
This is the latest in a series of blogs exploring the use of social media in public health and healthcare. The blogs have used social network analysis to study awareness raising campaigns (#VaccinesWork, National Clean Air Day, Antibiotic Awareness Week 2016), conferences (European Public Health conference 2016, Quality2017), and key influencers (exploring whether the 85:3% rule applies to tweeting about health and healthcare).
You can also read and download the blog in a PDF.
This blog attempts to share some key methodological pitfalls in planning, conducting and sharing the results of a social network analysis. It is structured around 5 main ideas:
- Finding a needle in a haystack
- Filtering out the minnows and sticklebacks
- Working out the size of pond for the big fish
- Slicing out the spam
- The ones that got away – and how to include them in the final analysis
The work has reminded me of work on cell culture when I was a medical student: I worked in a lab in Dallas, Texas, for 4 months November 1994-February 1995, studying adrenal tumour cells. This was my first time working abroad, and I was a little star struck, working in Parkland Hospital, famous as the hospital that treated JFK on 22 November 1963, and home to Nobel Prize winners including Alfred Gilman. My research did not reach such heights. Results were disappointing and unpredictable, week after week, and I was running out of time. Research is marked as much by its “failures” as its “successes”; both are an essential part of learning, though the stumbles are shared less than the leaps forward.
Between 25 and 28 January 2018 thirty teams of healthcare workers, tech specialists and entrepreneurs will work together to develop new digital innovations in Public Health in a Product Forge hackathon (follow the tweets over the weekend using #PublicHealthPF). I have been asked to provide some thoughts in introduction. Preparation will be important for all participants, so here is my initial advice under 4 headings. You can view the presentation that I have produced for the event here (I also plan to record this as a short “film”).
This blog is the last in a series of articles on use of Twitter “big data” to study health awareness campaigns. World Diabetes Day happens every year on 14 November. Want to know why? Scroll down to find answer in “top tweet” summaries below…
During November 2017 there was a focus on HIV testing across Europe:
- #EuroTestWeek (17-24 November) across Europe, organised by European HIV-Hepatitis testing week
- #HIVTestWeek (18-25 November) for the UK campaign organised by HIV Prevention England.
Both campaigns asked me to map the tweets over the course of the week. I am not associated with or funded by either campaign. I am doing this out of interest, as a Public Health doctor, in personal time. As for previous analyses written up on the ScotPublicHealth blog I am interested to see how different campaigns unfold. Of particular interest here is how tweeters observe the geographical “boundaries” of the campaigns – for UK, Europe, worldwide. I am also interested to see whether the tweeters and tweet content differ between the different campaigns and across the week. As ever, the ideal tweet grabs attention (image), shares information (in image and text, but also linking to further information using a URL), and links to others (by mentioning other users/ tagging others in an image, and a hashtag).
I looked at the campaigns in a number of ways:
- Simple counts of Twitter activity (number of tweeters, tweets, estimated views of these tweets) – the hashtags are under review by the Symplur healthcare hashtags website but if accepted information will be available for the full period of the campaign. Followthehashtag also provides estimates, breaking “tweets” down into tweets, replies and retweeter, plus an estimate of “audience”.
- Geographical maps of tweeters/ retweeters using the Followthehashtag website: to look at spread of the message across the world (limit typically 1,500 tweets so will only be able to capture snapshots of larger campaigns).
- Social network analysis using NodeXL, looking at connections (people tweeting using the hashtags, retweeting or replying to these tweets, or mentioned in the tweets). This tool extracts up to 18,000 tweets and it is possible to combine extracts to look at longer period.
- Summarising top content using my “top tweets” analysis of NodeXL extracts – see examples of this approach on my Storify page.