Filtering reality

I’m reading an interesting just-published paper by Meryl Alper, “War on Instagram”, about how (read it at New Media & Society or without the paywall at The paper discusses how photojournalists are using smartphones and in particular Instagram and Hipstamatic to produce documentary images that are heavily filtered, like Damon Winter’s “A Grunt’s Life” series for the New York Times.

Photos taken with Hipstamatic iPhone app as an embedded photojournalist for the NY Times.

Photos taken by Damon Winter with Hipstamatic iPhone app as an embedded photojournalist for the NY Times. (

Another example is Lowy’s Hipstamatic photo of Hurricane Sandy, which made it to the front page of Time Magazine:


Yesterday, Talan posted a link to Filter Fakers, a website that provides us with the useful community service of alerting us to Instagram photos that are incorrectly tagged #nofilter. As Talan wrote, “who cares?”


Photojournalists care, it seems.

Lowy’s concession to his critics – “toning down” the illustrative style of the very Hipstamatic photo filters that won him acclaim – touches upon an endless discussion about understanding all photography as a manipulated interaction between style and substance, and a timeless debate over the ethics of combining photojournal- ism with aesthetics. (Alper 2013: 4)

[S]cholars such as Luc Boltanski (1999) have argued that the aestheticization of what we see in the media emotionally and morally insulates viewers from the suffering of others. (5)

That’s a point made by Susan Sontag, too, as Alper notes on page 7: a worry is that “aestheticizing war leads to anesthetizing war”.

Part of the concern is, it seems, the eternal “but who is the author?” question. Alper quotes news photographer Nick Stern, who wrote that

It’s not the photographer who has communicated the emotion into the images. It’s not the pain, the suffering or the horror that is showing through. It’s the work of an app designer in Palo Alto who decided that a nice shallow focus and dark faded border would bring out the best in the image.

Does that matter, though? And aren’t our images always mediated through the work of others? If not through the code written by app designers in Palo Alto, then by the mechanics of a camera designed and redesigned by a series of people? No photographer is in control of the whole process. The best one can do is choose between different apps, cameras, processes, chemicals, software, papers all made by other people. It’s interesting how the idea of the lone genius still remains.

The place of these images in a stream – or alternatively, on the front page of Time Magazine – is also worth considering. Alper argues that the meaning of an iconic and disturbing war photo such as the famous photo of the naked Vietnamese girl running from napalm would have had a very different effect in a news feed between “photos of cocktails and kittens on an Instagram feed” (7).

I’m not convinced that this is particularly different from the ways we encountered photographs a few decades again. On television, in a news broadcast sandwiched between commercials and soap operas, or in a newspaper with ads and trivia on the next page. The very reproducibility of the photograph means that it will be encountered in many different settings, and not always in serious, museum or documentary style contexts.

The roughness of the smartphone image also claims a kind of authenticity, and Alper quotes two different  embedded war photojournalists who chose to use smartphones to mimic the soldiers’ own photographs. Alper discusses some definitely problems with this too simple idea:

Winter and Guttenfelder’s rationale falls into an anthropological trap, justifying the use of the iPhone and Hipstamatic as “naturalistic” because they empathize with how soldiers produce their own images of the war. The professional embedded photojournal- ist using Hipstamatic performs a sort of imagined autoethnography of soldiers’ own media-making practices. This performance is based on individual photographers’ highly time-bound conception of the kind of photos these soldiers would take if imbued with professional skills and competencies, as if that were the only distinction between the lived experiences of soldiers and embedded photojournalists. Embedded photojournalists are not observers, but rather, participant observers: their presence invariably alters the setting of their shots, regardless of the type of camera and the degree to which the device becomes silent and unnoticed.

The “imperfect” Hipstamatic photographs taken by embedded photojournalists are potentially misleading because they feel as though they might come from the “subjec- tive” perspective of troops rather than the objective perspective of the embedded photo- journalist. Adopting the perspective of soldiers might be appealing for photojournalists because soldier participation and visibility in the representation of war can often appear to be a “bottom up” alternative to “top down” political and military positioning (e.g., Andén-Papadopoulos, 2009; Smith and McDonald, 2011). This appeal to the vernacular in professional war media production is a reflection of what Turner (2010) calls the “demotic turn” in popular culture, or the increased visibility of “ordinary people” in media production without a necessarily more democratic public sphere.


These photos, constructed around an image of the hypothetical soldier, do not account for the polyvocality of multiple soldier perspectives and voices, speaking for troops by speaking through their imagined mode of photography. (11-12)

Alper doesn’t really discuss the soldiers’ own photographs, other than as a contrast to the professional photojournalists’ photographs, but in her conclusion she raises the #nofilter question that I started this post with. Obviously, there is no real way in which a photograph can be “unfiltered”:

Whether or not a photo has been processed with the sepia tinge of the Sutro filter, or the washed-out Walden, all photos taken though a mobile photo app such as Instagram or Hipstamatic are in some way “filtered.” Technically, even basic Instagram photos take the shape of a square, versus the automatic rectangular dimensions of an iPhone’s built- in camera. Ideologically, “#nofilter” serves a social and cultural purpose for those who employ it. The claim to clearly demarcate the real from the artificial says more perhaps about the person taking the photo than about the photo itself.

I’m reading as much as I can find right now about ways in which technology filters and mediates self-representations, like through selfies or with a Fitbit or on Tumblr or Instagram – so if you know of any work I should be reading, please let me know!

07. November 2013 by Jill
Categories: Visualise me | 3 comments

note for post on surveillance being cool

Facebook is just as interesting in reading between the lines as Google is. In the Facebook Third Quarter Earnings Conference Call on October 30, Mark Zuckerberg explained that one of Facebook’s main goals is “understanding the world”:

What I mean by this is that every day, people post billions of pieces of content and connections into the graph and in doing this, they’re helping to build the clearest model of everything there is to know in the world. A big part of why this works is that people can share things with any audience they want. They don’t have to share publicly with everyone at the same time; they can share with just their friends. So this means that the model of the world that people are building in our systems includes things that people only want to share with just a few people. This has the potential to be really powerful, but right now, we actually do very little to utilize the knowledge that people have shared to benefit everyone in our community.


05. November 2013 by Jill
Categories: Uncategorized | Leave a comment

Oxford University Press’s excellent Tumblr page

I was very impressed with Oxford University Press’s Tumblr page, which is actually exciting enough to be consistently on Tumblr’s trending blogs list (you can only see the trending list in the mobile app, not on the website) and thought their obvious skill in finding tidbits from academic books that appeal to Tumblr’s young demographic might mean they’d have good books on digital culture. But although they have an interesting series on Digital Politics (check out the upcoming Tweeting to Power: The Social Media Revolution in Politics by Jason Gainous and Kevin M. Wagner) I can’t find anything interesting on digital culture or new media from a humanities perspective. Their media studies section is astounding: they list the subcategories as “television, radio and film” – that’s it!? This is 2013, for goodness sakes! Am I missing some great books, or is Oxford simply not very interested in digital culture?

10. October 2013 by Jill
Categories: Blogging | Leave a comment

Adapting your social media rhetoric to Tumblr or Facebook

There’s a whole rhetoric to Tumblr, and as I wrote yesterday, animated gifs are an important part of it. Compare, for instance, The White House’s official Tumblr page to the now suddenly quite staid-seeming Facebook communication. Here’s the Tumblr image they posted the day before the government shutdown:


Even the italic font used is the one commonly used on subtitling of loops from videos. And here’s the version they put on Facebook:


Until yesterday I hadn’t realised that The White House was even on Tumblr, and I certainly hadn’t considered their alternate rhetorical strategies. Are there other sites where they speak differently again? Instagram has the same image as Facebook, and Twitter has the text.

Do you know of other social media actors that use different strategies on Tumblr and Facebook?

05. October 2013 by Jill
Categories: Blogging | Leave a comment

I should have written about animated gifs on Tumblr in the 2nd edition of Blogging!

Of course once anything is published you realise all the things you would love to add. Looking at how my seventeen-year-old was reading about the US government shutdown not in newspapers or on Twitter but through Tumblr’s animated gifs and reblogged screenshots of tweets (and some lengthier Tumblred analyses as well) I realised, again, how much duller – and certainly less animated – my own social media feeds are. I don’t think I mentioned animated gifs in Blogging 2nd ed, which was clearly an oversight.

underconstruction-animatedAnimated gifs are not at all what they were in the 90s. You remember, the little moving pixellated icons, like this the “under construction” icon?

Nowadays animated gifs are more like this.


That’s a “reaction gif” of Oprah being moved. There are whole repositories full of reaction gifs for any occassion: happy, shocked, bored, annoyed, etc. I chose this one to show you largely because it’s “only” half a MB large, and the first ones I picked were 2 MB each, which of course is one of the issues with the animated gif. They are bloated giants and horrible if your internet connection isn’t fast or if you’re paying by the megabyte. Or if you like me have a tendency to clutter your computer with too many files so you don’t have enough free memory for the computer to keep all these huge gifs running at the same time. Video would be more efficient, but animated gifs are so versatile that they stay popular.

This piece by Stallio is a glorious example of animated gif art, though I suspect this is not the dominant aesthetic.


Pioneering net artist Olia Lialina is also working in animated gifs now. Here’s an example of her work:olia-lialina-animated-hoola-hoop

Lialina knows her history, cares about file size (this one’s only 169 kb) and specifically uses the transparency that gifs allow, which is not at all used by the video-style gifs. So I could put those hoolahoopers onto any background I wanted. You can see how that works on Lialina’s website.

Other examples are the subtitled comic-like gifs laying out a sequnece from a few minutes of, say, The Colbert Report.

This essay by Daniel Rourke provides a nice brief catalogue of the different kinds of animated gifs, with an interesting introduction where he talks about Walter Benjamin’s idea of the mimetic and how these gifs speak without words. Their silence is certainly also interesting. Rourke’s piece seems one of just a few scholarly works on animated gifs. I found nothing relevant when I searched Google Scholar for “animated gif”, but if you add in “tumblr” you get a few essays. Tumblr is certainly a hub for this, as are Reddit and 4chan.

If you know of more academic work on animated gifs, or simply have some favourites you’d like to share, I’d love to hear about it!

04. October 2013 by Jill
Categories: Blogging, Digital Art, social media | 2 comments

The second edition of my book “Blogging” is out!

Hooray! When I came home from Chercher le texte, the 2013 Electronic Literature Organization conference, I found a copy of the new and revised edition of my book Blogging waiting for me in my mailbox!

Cover of Jill Walker Rettberg: Blogging 2nd ed (Polity Press, 2013)

The second edition of my book Blogging!

A lot has changed in blogging since the first edition came out in 2008. Blogs are still important, but we often read them through other social media sites, finding links to blog posts on Facebook or Twitter. Blogs have grown increasingly image-centric, and the second edition discusses how this changes blogs, and how new image-centric ecosystems like Pinterest, Instagram and Tumblr can be seen as a form of blogging. Microblogging and reblogging are another new development, as are the more specialised and often commercialised blogs we see now.

Right now you can buy the book in the UK (or online from, for instance) and it will be released in the US in a few more weeks.

If you want to see what kinds of things I talk about, you can browse through the texts and blogs I have referenced in the new edition. I’ll post the table of contents too, later.


02. October 2013 by Jill
Categories: Blogging | Tags: , , | 1 comment

No digital texts in English literature classes, please! Digital dualism and educational policy

I hadn’t realised that the UK curriculum for GCSE English Literature (for 14-16 year olds) explicitly excludes any kind of electronic literature, as Alexander Pask-Hughes writes in a post on Cyborgology today. He quotes the  proposed content descriptions – I suppose “proposed” means they’re not yet approved, but don’t know much about the UK system so fill me in here if I’m wrong:

Study of high quality English literature should be the principal focus of study for this GCSE. Digital texts must not be included. GCSE specifications in English literature should be designed on the basis that students’ reading should include whole texts.

Alexander Pask-Hughes reads this in terms of “digital dualism”, a worldview where the digital is seen as fundamentally different from and often less valuable than the non-digital.

In Norway, the digital is very explicitly included in school curricula, and “digital skills” are defined as one of five basic skills to be part of every subject in schools, along with orals skills, reading, writing and numeracy. One of the goals for high school students in Norwegian is that they should be able to

beskrive samspillet mellom estetiske virkemidler i sammensatte tekster, og reflektere over hvordan vi påvirkes av lyd, språk og bilder (“Describe the interplay between aesthetic techniques in multimodal texts, and reflect over how we are affected by sound, language and images.”)

Of course, Norwegian includes not just literature but language and culture, and has a decades-long tradition of including analyses of advertising, for instance. So adding digital and multimodal texts to the mix doesn’t necessarily mean there’s a general acceptance that poetry could be digital as easily as printed.

In the EU, digital competencies are defined as one of eight key competencies for life-long learning, and are seen as a transversal skill set that should be learnt across subjects in schools, not just in one single subject. That’s great if it works, but also means that nobody has sole responsibility for digital competencies.

Perhaps classing “digital competencies” as a skill set also allows us to keep that digital dualism. Digital skills mean being able to use technology. Maybe that allows us to continue to see technology as separate from the rest of our society and culture, and to continue to see digital skills as separate from the other key skills we learn at school.

01. September 2013 by Jill
Categories: Electronic literature, Teaching | 1 comment

An intensity chart of my levels of busy-ness since 2007

I just noticed the year view of iCal gives me a nice intensity chart of how busy my life has been over the last few years, at least in terms of how many meetings and calendar events  I have.

Calendar-2007  Calendar2008

In 2007 it looks as though my spring was fairly light, but things heat up for Scott and my wedding in early June, and the rest of the year is fairly busy too. I was on sabbatical in the academic year of 2007/8, but still had lots of appointments, it seems. Our daughter was born in April, and the rest of the year was busy in a way not tracked by calendars.

Calendar2009  Calendar2010

By mid-2010 I was pregnant again, and I wonder whether my pregnancy exhaustion forced me to be a little less busy, because the calendar’s not very busy. I remember I was napping every afternoon and still going to bed by nine pm. Benji was born in February 2010 and you can very clearly see my parental leave – and how things got very busy again when I was back at work in the autumn, although Scott and I were each only working 50% that semester.

Calendar2011  Calendar2012

2011 and 2012 look pretty steady – you can’t even really spot my summer holidays, which seems a little sad.


This last year very clearly shows the election campaign all spring, though. A lighter summer, and hopefully the next few months will keep some of that nice yellow, as I’m on sabbatical again.

I suppose this isn’t a very useful visualisation, but I had forgotten that all my calendar events for the last several years are actually archived and probably I could get more information out of them than this. It’s also nothing to what dedicated self-trackers are tracking. Here’s a snippet from Chris Dancy’s calendar where he tracks everything he does in great detail.


My simple iCal view won’t yield the kind of self-analysis that Chris Dancy’s calendar will, but it’s interesting because it’s generated entirely without my intending it to be generated – I’m just using my calendar to keep track of my appointments, and when I suddenly click on the Year view, I see my life, portrayed in levels of busy-ness from yellow to red.

29. August 2013 by Jill
Categories: Visualise me | Leave a comment

Tutorial: How to explore a network graph of electronic literature in Gephi

Update July 2014: a newer dataset is available that includes 44 dissertations (here is the gephi file), and the final paper is now published: Rettberg, Jill Walker. 2014. “Visualising Networks of Electronic Literature: Dissertations and the Creative Works They Cite.” ebr: electronic book review, July 2014. 

We’ve been doing a lot of work lately using Gephi to visualise connections between authors, creative works, critical writing and events in the ELMCIP Electronic Literature Base. It’s pretty easy to get started, and here’s a writeup of the quick tutorial we gave participants in our Visualising Electronic Literature workshop last week.

First of all you’ll need to download and install Gephi, which is open source and available for Mac OS X, Linux and Windows. Then download this ready-made .gephi file which contains information about 32 PhD dissertations on electronic literature and the creative works they reference. To make that file I entered information about the dissertations and links to the creative works they reference in the ELMCIP Electronic Literature Knowledge Base and then exported that information and imported it into Gephi. Here’s the list of dissertations and you can follow the links yourself. I’ll explain how to do the export and import in a separate tutorial next week, so that you can create your own electronic literature datasets to visualise.

First you

Figure 1: When you first open the .gephi file you’ll see a tangle of nodes in the middle.

When you open the .gephi file you’ll see a tangle of nodes in the middle (Figure 1). There are three tabs at the top. This one is the overview, which is where you can set up your visualisation. The  middle top tab lets you see the Data Laboratory, where you can view all your data as a spreadsheet – which is what it really is. This is useful for sorting or seeing what nodes are actually in there, and for things like ranking the nodes according to how many references they have pointing to them. The third tab opens the Preview window which is where you make your visualisation pretty and export it as an image or PDF file.

Basic navigation

You zoom in and out using a scroll bar on a mouse or moving two fingers up and down on a touchpad. You can move the whole network around by right-click-and-dragging (cmd + click the mouse to drag on a Mac).

You can turn on labels by clicking the T icon at the bottom, but this gets pretty hard to read. You can adjust the size of the labels by using the controls at the bottom (hint: if you click that tiny upwards arrow on the bottom right you get more controls:

View labels and adjust the way nodes and edges look using the bottom menu bar. Click the little arrow on the right to get more controls.

Figure 2: View labels and adjust the way nodes and edges look using the bottom menu bar. Click the little arrow on the right to get more controls.

Figure 3: More controls hidden away at the bottom.

Figure 3: More controls hidden away at the bottom.

You can also use the arrow with a question mark on the left of the graph window Gephi-arrow-icon to select a node and see information about it in the upper left of the workspace. The little hand icon Gephi-hand-icon lets you move individual nodes – which if you want to analyse this as a network you should only do to make the graph more legible, for instance to be abel to read the labels clearly.

You may like to switch between the Overview and the Preview views often. You do that right at the top of the workspace. Preview gives you a far more legible graph, and you can adjust settings there so as to show labels more clearly.

Some basic terms

We’re doing a network analysis, so each PhD dissertation and each creative work is a node. The connections between them are edges, and in this graph an edge is drawn when a dissertation references a creative work. That means it’s a directional edge: it’s a one-way link from the dissertation to the creative work – the creative work doesn’t reference the dissertation. If you were visualising your Facebook network, you would have undirected edges, because if you’re friends with someone on Facebook, they’re also friends with you.

This is also a bipartite or two mode network, because there are two types of node: PhD dissertations and creative works. If you click on the Data Laboratory tab you can see that the nodes and edges have types corresponding to this.

How to layout your network

A good way to start exploring your data is to apply a layout algorithm to it. You do this from the Layout section, circled in red in Figure 4. I’ve selected the ForceAtlas 2 algorithm, which is good for finding community structures. It clusters nodes that have many shared edges, assuming that shared edges indicates similarity. In this network, you can see some dissertations almost only reference creative works not referenced by any other dissertation – like the node surrounded by a ring of other nodes towards the top of Figure 4. Other dissertations share references, like the ones on the right hand side of the network. In the middle you see lots of nodes that are referenced by many different dissertations. The unconnected nodes are dissertations for which I have not yet entered references.

When you select ForceAtlas 2, you need to press Run to see the layout, and you need to stop it when you are satisfied. You can play with settings until you get a layout you are happy with. I found that setting the Scaling and Gravity to 20 made the network more legible. You can also tick the “Prevent overlap” box to space nodes out a bit more.

Figure 3:

Figure 4: The ForceAtlas 2 layout is useful for finding community structures.

It would be useful to see the difference between creative works and PhD dissertations, so let’s partition our network to show the two types of node in different colours. You do that in the window in the upper left of the workspace, as circled in red in Figure 5. Remember to click the green refresh button so you can see what node attributes you can partition the network by.

Figure 3: Partition the network by type to clearly see which nodes are PhD dissertations and which are Creative works. In this view, Creative works are blue and PhD dissertations are red.

Figure 5: Partition the network by type to clearly see which nodes are PhD dissertations and which are Creative works. In this view, Creative works are blue and PhD dissertations are red.

Next you can rank the nodes by the number of inbound links, or their in-degree. All edges in this network point from PhD dissertations to Creative works, so PhD dissertations have an in-degree of zero. All the creative works have an in-degree of at least 1, but some have far higher in-degree. If you run the “Average degree” algorithm in the Statistics window on the right of the workspace, you can see the average degree  and then you will be able to view the actual degree of each individual node in the Data Laboratory (Figure 6). You can see that afternoon, a story has the most references from dissertations, 10 of 32 dissertations cite it.

Figure 4: You can view nodes in the Data Laboratory to see their individual degree - that is, how many creative works they reference, or how many dissertations reference them.

Figure 6: You can view nodes in the Data Laboratory to see their individual degree – that is, how many creative works they reference, or how many dissertations reference them.

You make the frequently-cited nodes appear bigger by selecting the Ranking tab instead of the Partition tab, selecting Edges and the attribute by which to rank them (In-degree) and then you click on the tiny diamond-shaped icon next to the colour wheel in the upper left of that tab so they’re sized instead of coloured differently (Figure 7). You can choose a minimum and maximum size that you think shows the variation well.

Figure 5: Make frequently-cited creative works bigger by ranking them.

Figure 7: Make frequently-cited creative works bigger by ranking them.

Now let’s see how this looks in Preview (Figure 8). Click the refresh button at the bottom to see your graph – and you’ll have to click refresh every time to make any changes, too. The default view gives you curved edges. It’s useful to know that in network analysis this means that the edges are directed, and you can read the direction by following the curves in a clockwise direction. So don’t use curved edges just because you think they’re pretty – or if you do, realise that people who know network analysis are going to read meaning into your pretty curves. In this graph we actually do have directed edges, so curved edge lines are appropriate.

Figure 8: Adjust the size of labels, the background colour, the colour of edges and other details in Preview, then you can export your graph as an image or a PDF.

Figure 8: Adjust the size of labels, the background colour, the colour of edges and other details in Preview, then you can export your graph as an image or a PDF.

In Figure 8, I’ve ticked the “Show Labels” box, and I’ve reduced the font size a lot. I’ve also ticked the “Shorten label” box and set the maximum length to 15 characters. I set the colour of the edges to be light grey.

It’s still quite hard to read the labels of the nodes because the labels overlap. To fix this you’ll have to go back to the Overview. can try running the ForceAtlas 2 layout algorithm again with “Prevent Overlap” ticked, or you can try the “Label Adjust” algorithm instead, or you can simply drag individual nodes around so they overlap less. You can also try running ForceAtlas 2 with increased Scaling.

One way of simplifying the graph is to filter out the nodes that are less frequently cited. You do this from the Filter tab on the right – it may be hiding behind the Statistics tab, so check the tabs at the top of this part of the workspace.

Figure 9: Filter by degree by selecting Topology, then pulling the Degree option down into the Queries section below. Set the degree to 2 and click the Filter button and all creative works that are referenced by only one dissertation will disappear from your graph. (They'll come back if you click Filter again.)

Figure 9: Filter by degree by selecting Topology, then pulling the Degree option down into the Queries section below. Set the degree to 2 and click the Filter button and all creative works that are referenced by only one dissertation will disappear from your graph. (They’ll come back if you click Filter again.)

If you run the ForceAtlas 2 layout algorithm again now, you’ll see the nodes pull together in a different way. In Figure 10 you can see how the graph clusters differently without the infrequently-cited works.

Figure 10: Run the ForceAtlas 2 layout algorithm again to see how these nodes cluster without the infrequently cited nodes.

Figure 10: Run the ForceAtlas 2 layout algorithm again to see how these nodes cluster without the infrequently cited nodes.

Now you can turn labels on in the Overview and more or less read it. You can also use the hand icon Gephi-hand-icon to drag nodes slightly around so the labels don’t overlap, or just to click on an individual node and see what it connects to (Figure 11).

Figure 11: Turn on labels (at the bottom of the screen) and click nodes to see which nodes connect to which. Use the hand tool to drag individual nodes around for increased legibility.

Figure 11: Turn on labels (at the bottom of the screen) and click nodes to see which nodes connect to which. Use the hand tool to drag individual nodes around for increased legibility.

When you’re happy, switch to Preview again and make it pretty.

Figure 12: Make your final adjustments in Preview.

Figure 12: Make your final adjustments in Preview.

Now you can think about what the connections mean. I think the clusters correspond pretty clearly to genres of electronic literature. I can see interactive fiction, kinetic poetry, installation-based visual poetry with physical interfaces, generative narratives and poetry and in the middle, a big tangle of “classics” that are cited by a lot of different dissertations.

For more details, read the draft of my paper on this dataset for ELO2013 in Paris next month, or Scott Rettberg’s analysis of canonicity as expressed in the Electronic Literature Knowledge Base (PDF) where he uses similar visualisations of a slightly different dataset. Here’s the description of our panel, which will also include analyses of Brazilian electronic literature and of embodiment in electronic literature, using the Knowledge Base as a dataset.

In future tutorials I’ll explain how to actually get data out of the Electronic Literature Knowledge Base and into Gephi, so you can get your hands on different kinds of data to analyse. And I’ll also explain how to convert this two-mode network into a one-mode network and what that means.

Do ask if you have any questions or ideas!

28. August 2013 by Jill
Categories: Digital Humanities, Electronic literature, ELMCIP, Social Network Analysis | 3 comments

Figshare for sharing academic papers with their datasets

My paper for Chercher le texte, the Electronic Literature Organization’s 2013 conference in Paris next month, is about ready and I’ve uploaded it to the ELO conference website and to Figshare.

Figshare was new to me. It’s an open access non-peer-reviewed research repository built to contain more than just papers: the idea is that you share your datasets, images, posters or whatever – and if you like a traditional paper as well – and Figshare sets you up with a nice website for your research materials all citation ready.

My paper is a network analysis of links to creative works of electronic literature from dissertations on electronic literature, so Figshare makes it easy to share the paper along with that data, allowing anyone else who is interested to import the same data into Gephi or some other software and do their own exploration of it. Excellent! It’s like GitHub for academics! Of course, some academics already use GitHub in fascinating ways, but I do like the idea of a site specifically for academic datasets, and I especially appreciate the citation information they provide. It also provides versioning, which is useful for this kind of data – I hope to get more PhD dissertations analysed before the conference, and when I do, I’ll update the dataset and the paper too – and Figshare will keep track of that for me.

My ELO2013 article, with its datasets, on Figshare

Figshare’s view of my paper with its datasets. Note how easy it would be to cite this. And sharing in social media is nicely integrated too, although the embed option doesn’t work with selfhosted WordPress blogs  like mine.

I would like Figshare even better if there was some layer of peer-review here. You could leave uploads open to everyone, but with some kind of peer-review on top of that to give the best work a stamp of approval from your peers, you could make this sort of publication the only kind we would need. On the other hand, you do to some extent get this from the shares and views – although my own two shares are the only ones here, and at least 20-30 of my views, maybe more, are because I used this URL when I had participants in our workshop last week download the dataset as a test set to learn to use Gephi.

Another point is that Figshare was very obviously built for the natural sciences, and there are very few humanities papers in there. I’m not sure how much that matters. Less community for us humanists, certainly, but we can still use it for sharing.

I’ve never done research before the last year or so where I’ve thought of myself as using datasets – traditionally that’s not how we think about our work in the humanities. Obviously doing visualisations with data from the ELMCIP Electronic Literature Knowledge Base does generate datasets that others could reuse. What I do have from previous research is piles of screenshots of works and blogs that I’ve written about but not used in my publications. Most of that is sort of half-lost on forgotten hard drives. Perhaps if sites like Figshare become part of our workflow, even we humanists will start thinking about our notes and screenshots and other materials as datasets that could be shared?

Figshare also promises to help write your data management plan for grant applications, because they provide the services required by funding agencies – a system for keeping data safe. Not private or confidential, but archived, permanently. I’m not sure I’d trust a private company with that, to be honest. Figshare was started by a PhD student and is owned by Digital Science, a subsidiary of Macmillan Publishing that “creates software and tools rather than content”. Which sounds good, but how long will they be around? How independent are they? What is their plan for monetizing this? This is exactly the sort of system universities should be working together to provide, for example through GÉANT, the European network that among other things provides Eduroam, secure roaming wifi for students and employees at hundreds of universities worldwide. Actually, most universities’ open access research archives, such as my own university’s BORA, probably support uploading datasets along with papers. But I don’t think they suggest it – you can upload multiple files, but it’s certainly not the default expectation, and poking around BORA I couldn’t find any examples of research publications archived with their datasets.

There’s also a shift here to a culture of sharing research before it’s quite finished, and preprints before they’re in a journal. My paper here is less finished than it will be when it goes to publication, so it’s not really a preprint, just a draft of a conference presentation that I plan to do further work on. I’d certainly love any feedback on it at this point, though!

26. August 2013 by Jill
Categories: Digital Humanities, Electronic literature, social media | 1 comment

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