The Epiphany Project @ Museums Development East Midlands Digital Technology Workshop
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My research aims to discover how feasible a source of evidence public social media provides to indicate how inspiring museums are. This deck describes my first Case Study, during which Social Media content about Belper North Mill was captured, placed in a Neo4J graph database, and analysed in the run-up to their March launch event and during Twitter's #MuseumWeek.
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The Epiphany Project @ Museums Development East Midlands Digital Technology Workshop
- 1. Monitoring Belper Mill’s Twitter for their March 2014 Launch Event A case study from the Epiphany Project Information Science PhD Research David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro09/04/20141
- 2. Questions this talk (tries to) answer • Project background – why am I doing this? • What am I doing for Belper Mill specifically? • What have I found so far? • What remains to be done for Belper Mill? • How can you keep in touch? 2 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 3. The Epiphany Project: aim and objectives • Does public social media contain evidence that museums have inspired people? • Build a model of “inspiration” • Ensure it’s relevant to museums • Use the model to mine / organise social media • Look for potential evidence of inspiration • Assess value of evidence with museum staff 3 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 4. Definition of “inspiration” An experience, or set of experiences, combining rational thoughts and emotions, resulting in the expression or enactment of fresh ideas. 4 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 5. Planning method and schedule 5 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 6. Work context 6 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 7. Technical vision for the system 7 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Museums Display objects Hold exhibitions Inspire… People Visit museums Follow museums and write about experiences using… Social media Enable social networks and content publication Epiphany system API Client Finds followers and their blogs from Focused web crawler Pass URLs to Harvests content from Content analyser Pass content to Data stores Graph database Business intelligence Links back to Logic / rules Visual- isation
- 8. The Derwent Valley Mills network 8 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Derwent Valley Mills Visitor Guide http://www.derwentvalleymills.org/images/stories/DVM_VisitorGuide_12pp_2012.pdf Name Twitter Name # Followers* Belper Mill @BelperMill 313 Cromford Mills @CromfordMills 2369 Darley Abbey @DarleyAbbey 1145 Derby Museums @DerbyMuseums 2734 Derby Silk Mill @DerbySilkMill 2340 Derwent Valley Mills @DVMillsWHS 2295 John Smedley @JohnSmedley 3957 Masson Mills @Masson_Mills 4 Willersley Castle @WillersleyHotel 424 * Figures captured on 12th March 2014
- 9. Potential effectiveness of the DVM network Name Screen Name # Followers Following 1 Dermot O'Leary radioleary 2168124 John Smedley 2 Times Fashion TimesFashion 1618672 John Smedley 3 Lonely Planet lonelyplanet 1448692 Derwent Valley Mills 4 Carroll Trust carrolltrust 1255216 Derwent Valley Mills, Cromford Mills 5 Jonah Lupton JonahLupton 730335 John Smedley 6 Martin Zwilling StartupPro 723561 John Smedley 7 Tim Lovejoy timlovejoy 610795 John Smedley 8 E!'s Fashion Police e_FashionPolice 601711 John Smedley 9 GHOST PROTOCOL GHOSTPROTOCOLS 448433 Derwent Valley Mills, Cromford Mills 10 MI6 Crown Carroll CrimeConspiracy 409272 Derwent Valley Mills, Cromford Mills 9 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Top 10 followers by sheer “popularity”
- 10. Potential effectiveness of the DVM network 10 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Name Screen Name # Followers Following Carroll Foundation ConspiracyCase 374307 Derwent Valley Mills BillionDollar-ID BillionDollarID 302972 Derwent Valley Mills, Cromford Mills Minimalhome Minimalhome 60921 John Smedley HistoryClub Magazine HISTORYmag 49718 Derwent Valley Mills, Cromford Mills collca Collca 43292 Derwent Valley Mills, Cromford Mills History News TheHistoryBrew 33446 Derwent Valley Mills, Cromford Mills Culture24 Culture24 30535 Derby Museums Mercedes-Benz Museum MB_Museum 24481 Derwent Valley Mills Museums Association museum_news 22898 Derwent Valley Mills, Cromford Mills, Derby Museums Matthew Ward HistoryNeedsYou 22552 Derwent Valley Mills, Cromford Mills, Derby Museums Top 10 followers with “architecture”, “history” and “heritage” in biogs
- 11. Derwent Valley Mills network on Twitter 11 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro New follower relationships between 1st March and 12th March 2014
- 12. Potential effectiveness of the DVM network Belper Mill Cromford Mills Darley Abbey Derby Museums Derby Silk Mill Derwent Valley Mills John Smedley Masson Mills Willersley Castle Total Belper Mill 100 37 15 27 27 42 4 0 16 168 Cromford Mills 5 100 12 21 20 44 3 0 8 113 Darley Abbey 4 26 100 45 50 39 4 0 6 174 Derby Museums 3 18 19 100 48 24 2 0 4 118 Derby Silk Mill 4 21 25 56 100 27 3 0 4 140 Derwent Valley Mills 6 46 19 29 28 100 3 0 8 139 John Smedley 0 2 1 2 2 2 100 0 1 10 Masson Mills 0 0 0 0 0 25 0 100 0 25 Willersley Castle 12 44 16 24 24 41 8 0 100 169 12 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Matrix of shared followers (as a percentage of each organisations total number of followers) on 12th March 2014
- 13. Potential effectiveness of the DVM network 13 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Who Belper Mill shares its new followers with on the network 12th March 2014
- 14. Belper Mill’s Twitter promotion of launch 14 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Belper Mill’s Hootsuite schedule (promoting their launch event on 29th March) 18th March 2014
- 15. Monitoring impact of promotion on network 15 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro Starting to monitor the reaction to the Tweets and their impact on the network 18th March 2014
- 16. Next steps – after the launch • Keep monitoring until mid April • Add the following to the graph: • Retweets • Tweets linked to the event on the 29th (using the Hashtag #MillOpening) • Find out how much value the network really adds • (Hopefully) contribute data to audience plan? 16 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 17. Next steps – analysis of potential audience • Capture at least 200 tweets from all 11,000 users • Index them and run a better search: • Use more detailed topic keywords • Find more relevant people / cut out the spam • Start to use some of Lboro’s emotion research • Spread the search beyond Twitter: • Start following links from Twitter with a web crawler 17 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
- 18. Summary • The Epiphany Project: • Trying to find museum inspiration in Social Media • Monitoring Twitter networks • It seems DVM network has some potential • Finding relevant users and content • Employing sophisticated search techniques • Trying to find data that’s USEFUL for museums • Follow @EpiphanyLboro on Twitter 18 09/04/2014 David Gerrard – d.m.gerrard@lboro.ac.uk @EpiphanyLboro
Editor's Notes
- This was a presentation given to the Museums Development East Midlands Digital Strategies Program on 25th March 2014. There’s a blog post about the overall event here: http://museumsdigital.wordpress.com/2014/03/28/inspirational-technology/… but suffice to say this talk was one of four inspiring presentations from Jonathan Wallis (@JonathanMuseum), Spencer Clark (@ATS_Heritage) and Cora Glasser (@glassball_news) – and if I vaguely held my own with their excellent talks then I’m very happy indeed.The presentation is an overview of the first “release” (i.e. three-month case study) for my PhD research into museums, social media and the nature of inspiration.This is the full deck of slides – containing a couple that I didn’t have time to present on the day.
- This is a summary slide explaining what the rest of the presentation contains. The focus of the talk was centred heavily upon the analysis of the Twitter network surrounding Belper Mill (http://belpernorthmill.org) – one of the eight museums taking part in Museum Development East Midlands’ Digital Strategies Programme (see http://mdem.org.uk/digital-strategies-programme-update).Some of the slides in this deck on SlideShare were hidden for the actual talk due to time constraints. I’ve tried to indicate which those were and the reasons why I hid them in these notes.
- So the aim of my research is to see how feasible a source of evaluation and impact data public social media is for museums. I have chosen the term “inspiration” to underpin my PhD research as it’s a key term used by the UK Museums Association to help define museums. (By their definition, a museum is somewhere that educates, entertains and inspires – see http://www.museumsassociation.org/about/frequently-asked-questions).As social media analysis requires heavy use of computers to capture and analyse data, and computer systems require models to facilitate their development (well, you can do it without a model, but good luck), one of the key objectives of the research is to build a model of inspiration that enables collection and analysis of social media data.One of the other key objectives is to work as closely as possible with the museum sector to validate the model and try and ensure the data / information it is used to collect is as relevant, useful and valuable to the museum sector as possible.
- This slide was hidden in the original presentation as I decided it wasn’t completely relevant to the talk… It was a bit too general about my work as a whole, and (as at the point this talk was given I was only a quarter of the way through my model development, data collection and analysis work) it was a bit too high-level / general about my PhD project as a whole and thus didn’t focus enough on the specific work I’d done for Belper Mill.But for the sake of SlideShare, it’s worth including, I think. So here are the notes I wrote for it.This definition of inspiration comes from my literature review (covering in the main Museum Studies, Psychology, Politics, Aesthetic Philosophy and a tiny little bit of Neuroscience).The working definition was then taken out to the museum sector over a series of six meetings / interviews with 11 participants (nearly all museum sector professionals – one volunteer who has professional PR experience). I also went to Let’s Get Real 2013 and spoke to other delegates.The working parts are: Experiences (which hopefully makes the definition more museum friendly – it’s about tangible experience of real places and objects).Rational thoughts – i.e. reasoned consideration of factual information.Emotion – it’s not “inspiration” unless the facts cause an emotional “kick”, though. Inspiration is something you feel.Expression / enactment of fresh ideas – there has to be an output or change of some sort, or else it’s just “admiration”.The consultation added the parts about a “set of experiences” (sometimes inspiration builds slowly across a series of visits) and the “expression / enactment” vs “admiration” parts.
- This slide was also hidden in the original presentation as it was too much information about my project management method. I originally thought it worth including to get the point across that the work I was discussing was an “in-progress” subset of a bigger project, but it was easier just to say that, in the end.But for the sake of completeness here, the project uses an Agile Systems Development methodology in which the work is broken down into project segments called “Releases”, so called because a working, and (hopefully) useful piece of the system should be released at the end of each project segment. I have scheduled four releases that map onto the four quarters of 2014. These are shown in my “Project Backlog”, which I manage using Trello (https://trello.com).The schedule above was based upon the output of my literature review, and a consultation with museum sector professionals. (My talk at the MDEM Digital Program meeting on 2nd December 2013 was part of that consultation process – there are some other SlideShare slides about that up here already).Because this is an academic project, I also often refer to the project segments as “Case Studies”, as that’s by and large what they are. So each segment of work will (hopefully) involve doing something of potential use for / with a museum. This is how I hope to fulfil the objective of ensuring the greatest possible relevance to the museum sector.The Belper Mill case study is the first list on the Trello board shown. The key tasks relate to audience analysis (current and potential) and evaluation of the impact of an event (Belper Mill’s 2014 opening night sound and light show, which was yet to take place when I gave the presentation). As it turned out, Belper Mill got involved in another event (Twitter’s #MuseumWeek), so I ended up analysing both.
- This is a “work context” diagram for the project. These diagrams are suggested as a way of thinking about the overall problem you are trying to solve while keeping technology (and potential technical solutions) out of the picture as much as possible. (This is to avoid the risk of being led by the nose by technology to a potentially inappropriate, or at least ineffective, solution). Using this diagrams is discussed in Mastering the Requirements Process, by Robertson and Robertson (http://www.volere.co.uk/masteringrequirementsprocess.htm) – they suggest that diagrams like this are an important part of building a business case for a project. I used it as a way of working towards the “ensuring relevance to museums” as it allowed me to think about the research questions I was asking in the context of the type of work that museums need to do.The key opportunities that mining social media for evidence of inspiration might present to museums are shown to the right of the diagram. Evidence of inspiration could be used to:Help plan audience development (i.e. one could refer to the social media surrounding another museum or cultural institution that tells a similar story to yours, and look at the people they are inspiring as examples of the type of audience you might attract.Help evaluate the impact of an event, though this is easier to pull off if you’ve made a conscious effort to think about how to tie your event back to social media, by using a hashtag, for example, or by encouraging people to use social media while at the event itself.Help provide “near live” feedback for museum staff about the event while it is taking place. This is often suggested as one of social media’s key advantages for event impact evaluation – social media as a feedback channel can provide information much closer to “real time” than other forms of quantitative analysis (e.g. measuring footfall and / or box-office takings) or qualitative analysis (e.g. interviewing visitors). This means feedback via social media might arrive in a timely fashion that enables tweaks to an event while there’s still time to make them. (This is suggested with the caveat that it’s important not to overreact to responses – it ought to be obvious when there’s an aspect of an event / exhibition worth tweaking as it will be a major talking point among multiple visitors – though it would also be safer to check such issues “by hand” with ‘real’ visitors on the ground before changing anything, rather than just relying on Twitter or Facebook comments).The second step of the animation shows the main areas of focus for the work I’ve been doing for Belper Mill. The rest of the diagram will be attended to by the remaining case studies. (I hope the animation shows up on SlideShare – if not, take my word for it that the Museum Promotional Activities, Museum Events and Audience Development boxes were all highlighted, as these were the parts addressed, at least in part, by the first release / case study).
- This was originally hidden to save time, too. There’s much more information about it elsewhere on the web, if you’d like to see it. (See link below).This shows an “architectural vision” for how the final system might end up. I won’t dwell on it too much, but again, I’ve included it to show which bits I’ve been doing for Belper Mill – namely a piece that talks to Twitter, a database that holds the data it finds, and a method for reading data, and displaying information from the database. Hopefully, you’ll be able to see how much of the architecture was touched on by the first release / case study, if the animation works in SlideShare. Again – the rest will come later. (Some of it before the end of this case study…)If you’d like a more detailed discussion of the architectural vision, it’s available in the paper I presented at Museums and the Web 2014 (the week after this one). The paper can be found here: http://mw2014.museumsandtheweb.com/paper/the-epiphany-project-discovering-the-intrinsic-value-of-museums-by-analysing-social-media/I suspect that my University’s IP people might despair that I’ve put a slide like this up, but note – this is the architectural VISION – and if I thought that the final result would end up anything more than vaguely like this, I might have been a bit more circumspect. It’s a direction of travel, but it’s extremely unlikely to end up being much like this once I’ve learned all the lessons my project is going to teach me.
- This is an introduction to the Derwent Valley Mills network, of which Belper Mill is one of the locations. One of the clear opportunities that working with Belper Mill afforded was the fact that it is part of a well-defined network, and that a reasonable proportion of the other organisations on the network are also active on Twitter. This meant I could widen the context of the analysis to include some of the other organisations (i.e. the ones listed).Find out more about the Derwent Valley Mills World Heritage site at: http://www.derwentvalleymills.org/
- This shows the “top ten most popular users” in the overall Derwent Valley Mills World Heritage Site by out and out popularity across the whole network, and which organisations they are following. Two things of note here:John Smedley gets a lot of popular followers.Three out of the ten (4, 9 and 10) are “follow spam”, all from the same or a very similar source – I don’t know who these people are but they’ve got spamming down to a fine art – they’ve also crowded out the top 20 or so pages of Google results when you search from them. The spam is all about some government conspiracy or other (something to do with an allegedly corrupt organisation called the Carroll Foundation Trust), so I suspect it’s Anonymous or someone like them.The spam shows how easy it is to distort a “picture” of “reality” when that “picture” is actually based upon a rather simplistic measure. Which is a rather stuffy way of suggesting that there might be more useful ways to slice and dice this data than just “who has the most popular followers”.
- This is very similar to the previous table, except I’ve restricted the search to those accounts that have “architecture”, “history” or “heritage” in their Twitter biographies.It shows some potentially more relevant results, but is still susceptible to spam (i.e. because the Carroll Trust “fraud” is “the biggest in history”) it gets to the top. So I need to find a better way of searching – which is what the next case study (or two) will focus upon.
- This is the sort of visualisation I’ve been able to produce after capturing Twitter data about the overall network and putting it in the graph database. A “graph database” is, essentially, a database that stores information about the relationships between things, and makes the information about those relationships just as important to the overall picture as the information about the actual things themselves.The graph database in question is Neo4J (http://www.neo4j.org/ - there’s a completely free community edition), and the visualisations are an out-of-the-box feature. Neo4J comes with a query engine that runs in Chrome using HTML5, and the results of some queries can be displayed in this “node-edge-node” directed graph format. So all such visualisations in this presentation are straight out of the Neo4J box.This particular image shows new follower relationships on the network – i.e. those people that have started following one or more of the organisations in the network since the analysis started on the 1st March. The red dot in the middle of the large cluster of salmon-pink dots on the right is Belper Mill. It’s has A LOT of new followers in March. We haven’t come up with a definitive reason why that might be yet, but they did sign up to Twitter’s #MuseumWeek just before the start of March, so that might be it. <<STOP PRESS>> I’m almost certain that is the reason – as more seasoned Social Media pros tell me that “you always get loads of new followers when a hashtag you are using is trending on Twitter – like #MuseumWeek was).The purple dots are the other organisations in the Derwent Valley Mills network.The green dots are followers who were already in the network on the 1st March when data was initially captured. They appear in this diagram because they started following one of the other organisations in the network since 1st March.The salmon-pink dots are brand new followers, who have joined the network for the first time since 1st March.Another interesting feature is the big cluster of shared new follow relationships between Derby Museums and Derby Silk Mill.
- This matrix shows how well each organisation shares its followers with the other organisations. The figures are a percentage of the overall total of its followers that each organisation shares. Therefore the totals on the right show who are the best “sharers”. I’ve highlighted the greatest areas of overlap (i.e. above 35%) in red. It’s interesting to note that the heritage organisations in the list (Belper and Cromford Mills, Derwent Valley Mills World Heritage and the two Derby Museums) appear to have more follower sharing going on between them than with the “non-heritage” organisations (in particular John Smedley – which is still a working textile mill / company, not a museum).
- This shows similar information to the previous slide (i.e. who is sharing followers with who) but is restricted to new follower information (i.e. follower relationships that have formed since I started monitoring on the 1st March). It has a bit more of a Belper-Mill-centric perspective than the previous slide, however. The red dot at the top is Belper Mill, and all the relationship links to followers from Belper have come into being since 1st March. The purple dots at the bottom are those other organisations that have followers in common.The green dots are “pre-existing” users (i.e. people who were following one of the organisations in the network before 1st March, but who have started following Belper Mill since), while the salmon pink ones are brand new (i.e. they’ve entered the overall network since March 1st).The most effective “sharers” in this diagram, therefore, are the ones with the most connections around them, in this case Cromford, the Silk Mill, Derby Museums and Derwent Valley Mills. Interestingly, Darley Abbey doesn’t do as well in this picture as it did in the previous one – it seems as if lots of its connections were made before this analysis started.
- This shows Belper Mill’s Hootsuite schedule all lined up with promotional Tweets for the 29th March event.
- This shows how some of those Tweets appear in the graph as they are sent out. This specifically shows Belper Mill (the red node), Cromford Mill (the purple node in the middle of the yellow cluster to the right), and their tweets in the run-up to the 29th March event. The yellow nodes (dots) are the tweets from Belper and Cromford’s timelines, and the cluster of green nodes between Belper and Cromford are those followers that existed in the network when data was initially captured that were mentioned in the tweets themselves. The blue nodes around the edge are Twitter User accounts mentioned in Tweets that do not follow any of the Derwent Valley Mills organisations.This diagram starts to indicate the potential for this system to build pictures of how networks grow around conversations and concepts (it would be an easy job to filter this query by keywords included in tweets, for example).
- This describes work still to be done for Belper Mill. The key activity is to include retweets of their tweets (to show how their messages spread) and mentions of them and their #MillOpening hashtag that occurred throughout the launch period. Similar analysis of their use of the #MuseumWeek hashtag will also be included.As it’s possible to use data collected in this way to link back to followers that may be shared between Belper and the other organisations in the Derwent Valley Mills network, there may also be the potential to see whether shared followers provide a particularly “fertile” ground for messages and ideas to spread around the network. In other words, it’s potentially useful to know how well shared around followers are by organisations on the network, but it would be even better to know that if we also knew what value a well-connected, cohesive network of followers was actually adding.That kind of query will take a bit of working out, but I’m pretty sure it’s possible… Watch this space.
- So here’s a quick summary. As mentioned in an earlier slide, this talk was a pre-cursor to my presentation and demo at Museums and the Web 2014 in Baltimore, for which I’d got a slightly more up-to-date picture, so it’s worth checking out those slides, too. (Coming VERY soon – if they’re not there already).