LitLong Edinburgh: exploring the literary city

Update: LitLong 2.0 launched at the 2017 Embra BookFest; see article

Edinburgh has just celebrated its 10th anniversary as UNESCO city of literature (Facebook | Twitter). The original city of literature, here’s Edinburgh’s literary story and details of tours and trails (guided | self guided | virtual – a bit lacking in the maps department, mind). Edinburgh is also home to the Scottish Poetry Library (Facebook | Twitter), the world’s first purpose built institution of its kind, it says here, and the Scottish Storytelling Centre (Facebook | Twitter), ditto, adjacent to John Knox House. Not forgetting the Book Festival (Facebook | Twitter), the “largest festival of its kind in the world“. 

The UK has one other city of literature, Norwich (see City of stories), and further literary cities include Dublin (great writers museum), and, pleasingly, Dunedin (about). Update: Nottingham has a bid in! If But I know this city! (tweets | David Belbin | report) is anything to go by, it should be successful. And there’s even Literary Dundee (@literarydundee). Unexpected update: Literary Odessa.

I suspect not entirely coincidentally, 30 March saw the launch of LitLong (@litlong), the latest output from the AHRC funded Palimpsest project (@LitPalimpsest) at the University of Edinburgh (see Nicola Osborne’s liveblog and #litlonglaunch, esp @sixfootdestiny). An “interactive resource of Edinburgh literature” currently based around a website with an app to come launched for iOS, LitLong grew out of the prototype Palimpsest app developed three years ago, taking a multidisciplinary team 15 months to build – geolocating the literature around a city is no trivial matter! See about LitLong for some of the issues.

550 works set in Edinburgh have been mined for placenames from the Edinburgh Gazetteer, with snippets selected for “interestingness” and added to the database, resulting in more than 47,000 mentions of over 1,600 different places. The data can be searched by keyword, location or author, opening up lots of possibilities, such as why is Irvine Welsh’s Embra further north than Walter Scott’s Edinburgh? Do memoir writers focus on different areas than crime writers? See too Mapping the Canongate.

Part of the point of Palimpsest is to allow us to explore and compare the cityscapes of individual writers, as well as the way in which literary works cultivate the personality of the city as a whole.

On the down side, while there is a handful of contemporary writers in the mix, the majority of the content necessarily comes from copyright free material available in a digitised corpus, ie old stuff they made you read at school. Plus search results can be rather overwhelming (339 hits for the Grassmarket) – filters for genre, time period, might be an idea. However the data is to be made available enabling interested parties to play around as they wish, with open source code and data resources on GitHub.

I’ve had a look at the data around Muriel Spark, who would surely be delighted to be considered contemporary. The prime of Miss Jean Brodie (1961) has a section set in Cramond, near where I grew up. Drilling down using the location visualiser quickly brings us to:

“I shouldn’t have thought there was much to explore at Cramond,” said Mr. Lloyd, smiling at her with his golden forelock falling into his eye.

Searching the database brings up three pages of Cramond results to explore, including 17 Brodie snippets. Note that here you can filter by decade or source.

A search for Cammo, even closer to home, brought up a quote from Irvine Welsh’s Skagboys, although the map shown was different depending on which tool I used:

Edinburgh is a city of trees and woods; from the magnificence of the natural woodlands at Corstorphine Hill or Cammo, to the huge variety of splendid specimens in our parks and streets, Alexander argued, a pleasing flourish to his rhetoric. — Trees and woodlands have an inherent biodiversity value, whilst providing opportunities for recreation and environmental education.

location visualiser map - quill not in park

location visualiser map – quill in back gardens rather than the “natural woodlands” #picky

database search map - not Cammo!

database search map – not Cammo!

At the other end of the scale a search for ‘Bobby’ brings up 72 snippets from Eleanor Atkinson’s book, that’s a lot to handle…TBH I don’t really want them, I want a nice map of locations mentioned in the book, or at least a list, to create my own Greyfriars Bobby trail. At the moment it’s not possible to switch between the text and the map from the location visualiser, although you can do this snippet by snippet from the database search.

As things stand LitLong feels like an academic project rather than a user friendly tool – some use cases might be an idea.Hopefully the same approach will be applied to other cities in due course.


Mapping #some

Update, Feb 2015: Tourists v locals: city heat maps showing geolocated tweets; tourists in CPH can be found in the city centre and at the airport, duh…but interesting concept! Here’s more…

Eric Fisher (Flickr | Twitter):

Cue #SoMe klaxon! Week 4 of #mapmooc looked at social media as spatial data, how social media can be used with maps, advantages and pitfalls…and just how easy it actually is to plot it on a map.

On Twitter few tweets are geotagged.  We’re up to a grand total of three in the #mapmooc TAGS archive – two by me plus:

But not:

See the difference in @asudell‘s stream:


#vandymaps are also having issues:

Seems that tweets made with the web client only get geolocation information (coordinates) in TAGS if they are tagged individually, but not if the user has merely added location in Settings, which TAGS doesn’t collect (htow about the vanilla Twitter API?). OTOH mobile apps, with inbuilt GPS, _do_ offer geocoordinates simply when location is turned on. At least I think that’s right – thanks to @derekbruff and @asudell for sorting this out!

(Update: @derekbruff has set up a #vandymaps archive, and is investigating geotagging tweets. Checking the #mapsmooc archive reveals that two of my own tweets, where I added location via the Twitter Web client, are the only ones with data in the geo_coordinates field. I’ve extracted the data from the user_lang field and will take a closer look PDQ.)

But even a small set of tweets can offer potentially interesting results – see What’s happening in our vicinity from Field Office (an arts project currently going on in CPH) – a snapshot of geotagged tweets using the app, plus the Esri Public Information Map, in the week’s mapping assignment. This shows the real time effects of extreme weather events and other natural disasters, including geotagged social content from Twitter, Flickr, and YouTube. As noted in the forums however this is a rather blunt instrument with a poor signal to noise ratio.

Tweetmap Alpha is a further tool to filter geotagged tweets. As we know geotagging and privacy kinda go together. GeoSocial Footprint looks at the location information you divulge on Twitter in the light of potential privacy concerns. A footprint is made up of GPS enabled tweets, social check-ins, natural language location searching (geocoding) and profile harvesting. It states that “14 million tweets per day contain embedded GPS coordinates and up to 35% of all tweets containing additional location information”, which seems rather higher than in my experience.

Geolocating tweets the hard way

Back in lesson 1, it was noted that locations relevant to a particular tweet could include:

  • the locations mentioned in the message itself
  • the user’s location when they created the message
  • the user’s home location
  • the locations implied by the message

What are you plotting when you plot location? Where people live, where they work, where there is free wifi?

And from a thread, the following methods can be used to determine the spatial origin of tweets:

  • gelocation (geotags?)
  • Geo-IP and user designations (haven’t a clue)
  • the location from the user’s profile

So, there’s more to it than geotagging via GPS. See for example Tweak The Tweet, which uses “a hashtag-based syntax to help direct Twitter communications for more efficient data extraction”.

A bunch of maps were presented on the forums, including a lone Facebook example (Mapping the world’s friendships), leading to extensive discussions on sentiment analysis and how it might/not work. Happy days!

For starters, at least three university projects use Twitter to understand [emotions] in the USA, including…

Other projects which may/not be connected to the above: Emography | Tweetfeel | Twittermood | We feel fine | Mappiness (UK). Enough already! Update, June 2014: Five Labs ” analyzes your Facebook posts to predict the personalities of you and your friends”.

More clues on sophisticated methods IRT geolocation no doubt to be found in:

I could also do with:

A nice story to finish, in the warm up to week 5.  #mapmoocer Tony Targonski created a map of Seattle on an earlier Coursera MOOC: “Larger circles mean more social activity. Greener colour represents more “positive” than expected; redder is less “positive” than expected. In this case “positive” refers to valence (a commonly used measure of sentiment), and “expected” is the predicted valence score based on the walkability measure of the block (overall more walkable places correlate with more positive sentiment).”

Which is an interesting point IRT Happy Denmark. They’re not happy, they just bike a lot (like I didn’t know).

#mapmooc statistics week 4 (7-13 August):

  • 656 (558; 374; 206) tweets, 202 (181, 117, 82) RTs, 264 (212, 112, 61) links (all +/- due to time zone differences)
  • top tweeters: @MapRevolution, @DougOfNashville, @PublicUniverse
  • n=246 (230, 152, 129); 157 (155 (102, 74) have tweeted only once
  • 61 (54, 40, 30) threads 9 (9 (11, 12)%
  • top conversationalists: @MapRevolution, @derekbruff, @annindk

Postscript: among its rather nice web apps Esri offers a social media app (hopefully a bit more stable than the gallery app) plus stuff on making a social media map in minutes – come in! See the Horn of Africa Drought Crisis Map for an example.

As a quick test I took a look at Denmark’s most popular hashtag,#dkpol. Danes aren’t big tweeters, but they are big mobile users and #dkpol people are a pretty vociferous bunch, but the results were rather underwhelming. Putting #SoMe on a map seems to be less about creating a meaningful map and more about simply harvesting the data – see We are on Albert Drive for an example of what can be done. To be revisited.