OUseful.Info, the blog…

As you’re probably aware by now, yesterday Google announced its Google+ social network. A key part of every social network is a user’s personal profile page, the “social object” that other people can actually connect to.

Google has offered personal profile pages for some time, (here’s my rather basic Google Profile: Tony Hirst), but they’ve never really been a part of anything, and they’re not really linkable to – which means there’s little reason for PageRank based search algorithms such as Google’s to return Google Profile pages in the top results for you if anyone ever searches for you.

(PageRank is the algorithm that gave Google its early edge in the search engine wars; links from one page to another count as “votes” regarding the quality of the page that is linked to. Crudely put, if people link to you, those links contribute to your PageRank and you’re more likely to make it to the top of a search results page.)

Until now, that is (or at least, until a couple of weeks ago… I missed this announcement at the time it was made…): Authorship markup and web search, a technique for “supporting markup that enables websites to publicly link within their site from content to author pages”.

The method is described as follows:

To identify the author of an article, Google checks for a connection between the content page (such as an article), an author page, and a Google Profile.

A content page can be any piece of content with an author: a news article, blog post, short story …
An author page is a page about a specific author, on the same domain as the content page.
A Google Profile is Google’s version of an author page. It’s how you present yourself to the web and to Google.
…
In confirming authorship, Google looks for:

Links from the content page to the author page (if the path of links continues to a Google Profile, we can also show Profile information in search results)
A path of links back from your Google Profile to your content.
These reciprocal links are important: without them, anyone could attribute content to you, or you could take credit for any content on the web.
….
The rel=”author” link indicates the author of an article [so for example: <a rel="author" href="https://profiles.google.com/tony.hirst/">Google Profile: Tony Hirst</a>]

Source: Authorship

Here’s why you might be tempted to do this…:

Many of you create great content on the web, and we work hard to make that content discoverable on Google. Today, we will start highlighting the people creating this content in Google.com search results.

As you can see …, certain results will display an author’s picture and name — derived from and linked to their Google Profile — next to their content on the Google Search results page.

Source: Highlighting content creators in search results; [my emphasis]

So… if you want to assert authorship and be recognised as the author in the Google search results, you need to start linking all your content back to your Google Profile Page…

…and so start feeding PageRank juice to your Google profile page…

…so that when folk search for you on the web, they’re more likely to see that page…

This is a harsh reading, of course: authorship can also be asserted by linking within a domain to a page that you have asserted to Google that represents you: The rel=”author” link indicates the author of an article, and can point to .. an author page on the same domain as the content page: Written by <a rel="author" href="../authors/mattcutts">Matt Cutts</a>. The author page should link to your Google Profile using rel=”me”.

(I wonder why <link rel=”author” href=”../authors/mattcutts”/> isn’t supported? Or maybe it is?)

Algorithmically, the assertion of authorship might also help in Google’s fight against spamblogs, which republish content blindly from original sources. That is, by asserting authorship of a page, if someone reposts your content, google will be able to identify you as the original author and return a link back to your page in the search results listing, rather than the republished page.

I imagine there might also be personal reputation benefits – for example, if people +1 a page you have claimed authorship of, it might give you a “Reputation Rank” boost for the subject area associated with that page?

Some threads that I can see tangling:

• as Google starts to fight back against content farms such as Demand Media (e.g. New York Times on Google’s War on Nonsense), the Digger seems keen to get into education: Murdoch signals push into education;
• for a long time I’ve imagined some sort of sensemaking spectrum that leads from news stories, through analysis and feature articles, to a more academic take on subject (if I can get my act together, I’d like to try to pull a workshop together in the Autumn between media and education folk to look at this…); I’m not necessarily suggesting a bigger role for “celebrity academics”, more a consideration of how academics can make content available to the media to add depth and deepened engagement to a story, and how the media can provide timeliness and news hooks to education as a way of adding contextual relevance. Here are two short (2 minute) takes on it, one from Martin Bean, the OU VC, in hist ALT-C 2010 keynote, and the other from Guardian editor, Alan Rusbridger, on the Radio 4 Media Show:
  • Martin Bean, ALT-C 2010 Keynote

  • Alan Rusbridger, on BBC R4′s The Media Show

• the OU starts a new sort of campaign: Youtube learning campaigns, such as this one on The History of English…

So where’s all this going? And what role might openly licensed content created by academics as part of their daily duties have to play in it?

Just so I don’t forget the development timeline such as it is, here are a few quick notes-to-self as much as anything about my “List Intelligence” tinkering to date:

• List Intelligence uses (currently) Twitter lists to associate individuals with a particular topic area (the focus of the list; note that this may be ill-specified, e.g. “people I have met”, or topic focussed “OU employees”, etc)
• List Intelligence is presented with a set of “candidate members” and then:
  1. looks up the lists those candidate members are on to provide a set of “candidate lists”;
  2. identifies the membership of those candidate lists (“candidate list members”) (this set may be subject to ranking or filtering, for example based on the number of list subscribers, or the number of original candidate members who are members of the current list);
  3. for the superset of members across lists (i.e. the set of candidate list members), rank each individual compared to the number of lists they are on (this may be optionally weighted by the number of subscribers to each list they are on); these individuals are potentially “key” players in the subject area defined by the lists that the original candidate members are members of;
  4. identify which of the candidate lists contains most candidate members, and rank accordingly (possibly also according to subscriber numbers); the top ranked lists are lists trivially associated with the set of original candidate members;
  5. provide output files that allow the graphing of individuals who are co-members of the same sets, and use the corresponding network as the basis for network analysis;
  6. optionally generate graphs based on friendship connections between candidate list members, and use the resulting graph as the basis for network analysis. (Any clusters/communities detected based on friendship may then be compared with the co-membership graphs to see the extent to which list memberships reflect or correlate to community structures);
• the original set of candidate members may be defined in a variety of ways. For example:
  1. one or more named individuals;
  2. the friends of a named individual;
  3. the recent users of a particular hashtag;
  4. the recent users of a particular searched for term;
  5. the members of a “seed” list.
• List Intelligence attempts to identify “list clusters” in the candidate lists set by detecting significant overlaps in membership between different candidate lists.
• Candidate lists may be used to identify potential “focus of interest” areas associated with the original set of candidate members.

I’ll try to post some pseudo-code, flow charts and formal algorithms to describe the above… but it may take a week or two…

“A booktalk in the broadest terms is what is spoken with the intent to convince someone to read a book.” Wikipedia

Whilst putting together yesterday’s post about personal art collections online (for a wider take on this, see Mia Ridge’s The rise of the non-museum (and death by aggregation), which offers all manner of food for thought around personal collection building…), I started thinking again about how we might use recorded discussions or book talks focussing on particular books as a component in the “content scaffolding” around works that might be used as resources in an informal learning context.

(For an earlier foray in to the book talk world, see my post on BBC “In Our Time” Reading List using Linked Data.)

So the (really simple and obvious) idea is this (and I fully appreciate other sites out there may already exist that do this: if so, please let me know in the comments): how about we build a lookup service that allows you to search by author, book title, ISBN (or cross ISBN), and it returns details for the book as well as links to audio or video recordings of book talks around the book.

I’ve started trying to cobble together a few resources around this, setting up (a not yet complete set of) scrapers (in various states of disrepair) on Scraperwiki to collate books and book talk audio links from:

• TechNation (scraper)
• Authors@Google (scraper) [only author names? No book info? Maybe if the date of upload was captured we could guess at the book tour from the scheduling of it?]
• BBC Radio 4′s A Good Read (scraper)
• BBC Radio 4′s Book Club (scraper)
• BBC Radio 4′s Start The Week (scraper)
• BBC Radio 4′s In Our Time (scraper) [okay, this isn't strictly discussing books; but it is abut ideas and there are links to books in the programme notes]
• Philosophy Bites (scraper) [again, not about books per se, but a good context for conversational sensemaking around ideas contained in easily linked to books on the topic written by the author?]
• [probably untold other podcasts...]
• Guardian Books podcast
• BBC Combined book related podcasts

It might also be appropriate to try to pull in “quality” book reviews* to annotate book listings, given that part of my idea at least is to find ways of enriching reading book references with discussion around them that can help folk make sense of the big ideas contained within the book, as well as maybe encouraging them to buy the book (the all required sustainability model: in this case, Amazon referral fees! Note that several of the sites use Amazon referrals as part of their own sustainability model. So it would only be fair to use their affiliate codes at least part of the time if their playable audio content was embedded on the site (even if that content is openly licensed… Share and share alike, right?! That is, trickle back a portion of any income you do make off the work of others, even if it is openly licensed for commercial use;-)

Another strand to all of this, of course, is sensemaking annotations around books pulled from “OERs” (what is is about education that makes the sector want its content to be somehow regarded as “special” and deserving of all sorts of qualification?!;-)

*Maybe the Guardian Platform API or one of the New York Times APIs could play a role here?

So, as ever, I’ve made a start, and as ever, that’ll probably be the end of it…. Sigh… Nice thought while it lasted though…

PS if I were to do next steps, it would probably to take the scraped data and try to normalise it in some ad hoc way in a triple store, maybe on the Talis platform? Note that in the current incarnation, some of the scraped BBC data contains multiple book references in a single record, and thise should be spearated out; also note that a lot of book references are informal (author/title), though I did manage to grab ISBNs (I think?!) from the IT COnversations/Tech Nation pages.

PPS In passing, I note that some of the older archived episodes of A Good Read have been split into chapters covering the different books reviewed in the programme? Was this some sort of experimental enrichment, or just the start of a more general roll out of chapterisation…?

A few months ago, the art discovery website Artfinder appeared on the scene, providing a place to go to view art (online) from galleries around the world, build your own collections, receive recommendations about other artworks you might like to see (and maybe go and visit for real) and so on. A “Magic Tour” feature allows you to select three art works you like from sets of four, and then view a personalised art collection based on recommendations derived from your selection. Where quality prints of a work are available, there is an option to buy the print (for example, via MemoryPrints).

A couple of other related things that have crossed my radar over the course of the year include the Google Art Project, which offers very high definition reproductions of artworks from galleries around the world, and the JISC funded OpenART project, “a partnership between the University of York, the Tate and technical partners, Acuity Unlimited, will design and expose linked open data for an important research dataset entitled ‘The London Art World 1660-1735′”.

Today, I noticed the launch of a new BBC site, Your Paintings [announcement], which offers you the ability to create art collections, locate artworks by physical gallery location and so on… Hmmmm… (As yet, the URLs don’t seem to support content negotiation as a result of adding a .json or .xml suffix to pircture or gallery page; that is, as yet, the service doesn’t appear to be offering linkable data (hyperdata?) views over the content).

There was a time when Microsoft used to be charged with unfairly influencing the market, announcing it was about to release some feature or product that a rival was trying to market, effectively stifling competition through brand and market dominance. If you read the tech blogs, Google, Facebook, Apple, Twitter, et al. currently find themselves in a regular situation where the services, applications or features they release are heralded as being likely to wipe out competition in a niche discovered, created, or developed by a startup elsewhere (only in many cases it doesn’t quite work out that way…Bit.ly surviced Twitter’s shortener, Google Buzz threatened no-one, Facebook Places or Google Latitude haven’t squashed Foursquare, etc.).

The BBC has itself faced challenges regarding “anticompetitive”/fair trading behaviour, for example in local online news (local news video), catchup services/internet TV (Canvas) or (BBC Jam).

Now I’m generally a fan of the BBC, but I do wonder what additional value Your Paintings brings, especially given that it’s not apparently being launched with any additional technical capacity building features (i.e. it’s not (yet?) making metadata freely available for others to build on, though a couple of recent tweets suggest this may be on the timeline…)?

Having come across aNobii today (via @maireadoconnor), a service that offers “an online reading community built by readers for readers allowing you to shelve, find and share books”, I wonder: is this another area where the BBC could just “step in”, presumably as a way of building community around the wide variety of programming it offers that have good hooks in to books?

[Disclaimer: I've ranted before about the BBC not making more use of structured markup around book identifiers, but if they were to get into reading groupsm this would presumably provide the technical underpinnings...? (e.g. BBC "In Our Time" Reading List using Linked Data.) So I maybe should be careful what I wish for...]

So the point of this post? Just to note my confusion about what it is the BBC actually does, and how it does it… I know that it’s not just about the telly and the radio, but I’m not sure what it is about when it comes to the web?

And it’s not just confusion about the BBC’s role. It also extends to the public facing role of the OU, which I personally view as having more a “public service education” remit than the rest of the UK HE sector (whether this is a view than can survive the increasingly businesslike culture of higher education I don’t know…). In other words: to what extent should the OU be doing more in the way of education related online public service broadcasting?

PS so I wonder:

How much has the BBC allocated to its opening salvo on a Your Paintings AdWords campaign…?

Interesting? Guardian Education writes:

BPP, which offers undergraduate and postgraduate business and law degrees at 14 UK study centres, said it was in talks about managing the business side of the universities’ campuses. Talks with three are at a “serious stage”, but commercial negotiations are yet to begin.

Under the model, universities would control all academic decisions, while BPP would be responsible for managing the campus estate, IT support, the buying of goods and services and other “back office” roles. BPP would not hold equity in the universities.

Private university BPP launches bid to run 10 publicly funded counterparts

So: you take on the estate, make it more efficient in terms of space utilisation, and then maybe work the space harder in terms of conference hosting, and maybe the delivery of BPP’s own courses….?

As the focus for this week’s episode [airs live Tues 21/6/11 at 19.32 UK time, or catch it via the podcast] in the OU co-produced season of programmes on openness with Click (radio), the BBC World Service radio programme formerly known as Digital Planet, we’re looking at one or two notions of diversity…

If you’re a follower of pop technology, over the last week or two you will probably have already come across Eli Pariser’s new book, The Filter Bubble: What The Internet Is Hiding From You, or his TED Talk on the subject:

Eli Pariser, :The Filter Bubble”, TED Talks

It could be argued that this is the Filter Bubble in action… how likely is it, for example, that a randomly selected person on the street would have heard of this book?

To support the programme, presenter Gareth Mitchell has been running an informal experiment on the programmes Facebook page: Help us with our web personalisation experiment!! The idea? To see what effect changing personalisation settings on Google has on a Google search for the word “Platform”. (You can see results of the experiment from Click listeners around the world on the Facebook group wall… Maybe you’d like to contribute too?)

It might surprise you to learn that Google results pages – even for the same search word – do not necessarily always give the same results, something I’ve jokingly referred to previously as “the end of Google Ground Truth”, but is there maybe a benefit to having very specifically focussed web searches (that is, very specific filter bubbles)? I think in certain circumstances there may well be…

Take education, or research, for example. Sometimes, we want to get the right answer to a particular question. In times gone by, we might have asked a librarian for help, if not to such a particular book or reference source, at least to help us find one that might be appropriate for our needs. Nowadays, it’s often easier to turn to a web search engine than it is to find a librarian, but there are risks in doing that: after all, no-one really knows what secret sauce is used in the Google search ranking algorithm that determines which results get placed where in response to a particular search request. The results we get may be diverse in the sense that they are ranked in part by the behaviour of millions of other search engine users, but from that diversity do we just get – noise?

As part of the web personalisation/search experiment, we found that for many people, the effects of changing personalisation settings had no noticeable effect on the first page of results returned for a search on the word “platform”. But for some people, there were differences… From my own experience of making dozens of technology (and Formula One!) related searches a day, the results I get back for those topics hen I’m logged in to Google are very different to when I have disabled the personalised reslults. As far as my job goes, I have a supercharged version of Google that is tuned to return particular sorts of results – code snippets, results from sources I trust, and so on. In certain respects, the filter bubble is akin to my own personal librarian. In this particular case, the filter bubble (I believe), works to my benefit.

Indeed, I’ve even wondered before whether a “trained” Google account might actually be a valuable commodity: Could Librarians Be Influential Friends? And Who Owns Your Search Persona?. Being able to be an effective searcher requires several skills, including the phrasing of the search query itself, the ability to skim results and look for signals that suggest a result is reliable, and the ability to refine queries. (For a quick – and free – mini-course on how to improve your searching, check out the OU Library’s Safari course.) But I think it will increasingly rely on personalisation features…which means you need to have some idea about how the personalisation works in order to make the most of its benefits and mitigate the risks.

To take a silly example: if Google search results are in part influenced by the links you or your friends share on Twitter, and you follow hundreds of spam accounts, you might rightly expect your Google results to be filled with spam (because your friends have recommended them, and you trust your friends, right? That’s one of the key principles of why social search is deemed to be attractive.)

As well as the content we discover through search engines, content discovered through social networks is becoming of increasing importance. Something I’ve been looking at for some time is the structure of social networks on Twitter, in part as a “self-reflection” tool to help us see where we might be situated in a professional social sense based on the people we follow and who follow us. Of course, this can sometimes lead to incestuous behaviour, where the only people talking about a subject are people who know each other.

For example, when I looked at the connection of people chatting on twitter about Adam Curtis’ All Watched Over By Machines of Loving Grace documentary, I was surpised to see it defined a large part of the UK’s “technology scene” that I am familiar with from my own echochamber…

#awobmolg echo chamber

So what do I mean by echochamber? In the case of Twitter, I take it to refer to a group of people chatting around a topic (as for example, identified by a hashtag) who are tightly connected in a social sense because they all follow one another anyway… (To see an example of this, for a previous OU/Click episode, I posted a simple application (it’s still there), to show the extent to which people who had recently used the #bbcClickRadio hashtag on Twitter were connected.)

As far as diversity goes, if you follow people who only follow each other, then it might be that the only ideas you come across are ideas that keep getting recycled by the same few people… Or it might be the case that a highly connected group of people shows a well defined special interest group on a particular topic….

To get a feel for what we can learn about our own filter bubbles in Twitterspace, I had a quick look at Gareth Mitchell’s context (@garethm on Twitter). One of the dangers of using public apps is that anyone can do this sort of analysis of course, but the ethics around my using Gareth as a guinea pig in this example is maybe the topic of another programme…!

So, to start with, let’s see how tightly connected Gareth’s Twitter friends are (that is, to what extent do the people Gareth follows on Twitter follow each other?):

The social graph showing how @garethm’s friends follow each other

The nodes represent people Gareth follows, and they have been organised into coloured groups based on a social network analysis measure that tries to identify groups of tightly interconnected individuals. The nodes are sized according to a metric known as “Authority”, which reflects the extent to which people are followed by other members of the network.

A crude first glance at the graph suggests a technology (purple) and science (fluorine-y yellowy green) cluster to me, but Gareth might be able to label those groups differently.

Something else I’ve started to explore is the extent to which other people might see us on Twitter. One way of doing this is to look at who follows you; another is to have a peek at what lists you’ve been included on, along with who else is on those lists. Here’s a snapshot of some of the lists (that actually have subscribers!) that Gareth is listed on:

The flowers are separate lists. People who are on several lists are caught on the spiderweb threads connecting the list flowers… In a sense, the lists are filter bubbles defined by other people into which Gareth has been placed. To the left in the image above, we see there are a few lists that appear to share quite a few members: convergent filters?!

In order to try to looking outside these filter bubbles, we can get an overview of the people that Gareth’s friends follow that Gareth doesn’t follow (these are the people Gareth is likely to encounter via retweets from his friends):

Who @garethm’s friends follow that @garethm doesn’t follow…

My original inspiration for this was to see whether or not this group of people would make sense as recommendations for who to follow, but if we look at the most highly followed people, we see this may not actually make sense (unless you want to follow celebrities!;-)

Popular friends of Gareth’s that he doesn’t follow…

By way of a passing observation, it’s also worth noting that the approach I have taken to constructing the “my friends friends who aren’t my friends” graph tends to place “me” at the centre of the universe, surrounded by folk who are a just a a friend of a friend away…

For extended interviews and additional material relating to the OU/Click series on openness, make sure you visit Click (#bbcClickRadio) on OpenLearn.

It’s generally taken as read that folk hate doing documentation*. This is as true of documenting data and APIs as it is of code. I’m not sure if anyone has yet done a review of “what folk want from published datasets” (JISC? It’s probably worth a quick tender call…?), but there have certainly been a few reports around what developers are perceived to expect of an API and its associated documentation and community support (e.g. UKOLN’s JISC Good APIs Management Report and API Good Practice reports, and their briefing docs on APIs).

* this is one reason why I think bloggers such as myself, Martin Hawksey and Liam Green Hughes offer a useful service: we do quick demos and geting started walkthroughs of newly launched services, demonstrating their application in a “real” context…

At a recent technical advisory group meeting in support of the Resource Discovery Taskforce UK Discovery initiative (which is aiming to improve the discoverability of information resources through the publication of appropriate metadata, and hopefully a bit of thought towards practical SEO…) I suggested that a Q and A site might be in order to support developer activities: content is likely to be relevant, pre-SEOd (blending naive language questions with technical answers), and maintained and refreshed by the community:-)

In much the same way that JISCPress arose organically from the ad hoc initiative between myself and Joss Winn that was WriteToReply, I suggested that the question and answer site with a focus on data that I set up with Rufus Pollock might provide a running start to UK Discovery Q&A site: GetTheData.

API connections to OSQA, the codebase that underpins GetTheData, are still lacking, but there are mechanisms for syndicating content from RSS feeds (for example, it’s easy enough to get a feed out of tagged questions out, or questions and answers relating to a particular search query); which is to say – we could pull in ukdiscovery tagged questions and answers in to the UK Discovery website developers’ area.

Another issue relates to whether or not developers would actually engage in the asking and answering of questions around UK Discovery technical issues. Something I’ve been mulling over is the extent to which GetTheData could actually be used to provide QandA styled support documentation for published data or data APIs, concentrating a wide range of data related Q&A content on GetTheData (and hence helping building community/activity through regularly refreshed content and a critical mass of active users) and then syndicating specific content to a publisher’s site.

So for example: if a data/api publisher wants to use GetTheData as a way of supporting their documentation/FAQ effort, we could set them up as an admin and allow them rights over the posting and moderation of questions and answers on the site. (Under the current permissions model, I think we’d have to take it on trust that they wouldn’t mess with other bits of the site in a reckless or malevolent way…;-)

API/data publishers could post FAQ style questions on GetTheData and provide canned, accepted (“official”) answers. Of course, the community could also submit additional answers to the FAQs, and if they improve on the official answer be promoted to accepted answers. Through syndication feeds, maybe using a controlled tag filtered through a question submitter filter (i.e. filtering questions by virtue of who posted them), it would be possible to get a “maintained” lists of questions out of GetTheData that could then be pulled in via an RSS feed into a third party site – such as the FAQ area of a data/api publisher’s website.

Additional activity (i.e. community sourced questions and answers) around the data/API on GetTheData could also be selectively pulled in to the official support site. (We may also be able to pull out the lists of people who are active around a particular tag???) In the medium term, it might also be possible to find a way of supporting remote question submission that could be embedded on the API/data site…

If any data/API publishers would like to explore how they might be able to use GetTheData to power FAQ areas of their developer/documentation sites, please get in touch:-)

And if anyone has comments about the extent to which GetTheData, or OSQA, either is or isn’t appropriate for discovery.ac.uk, please feel free to air them below…:-)

After a relaxing day spent finishing off Steven Levy’s In the Plex, here are a handful of very quick reflections:

- Google is an AI company: their scope for supervised training algorithms (with training signals coming from user actions and corrections), as well as unsupervised training (the algorithms for which are made available, for a fee, via the Google Prediction API) is ubrivalled;

- Google is a hardware company: when I used to run robotics outreach activities, I used to joke that Lego was the world’s biggest manufacturer of tyres. Nowadays, I’m as likely to quip that at one point in its history at least, Google was the world’s biggest computer manufacturer (not strictly true – I think they’re third or fourth…?)

- Google has unprecedented tracking ability: through Google cookies, Double Click cookies, Google Analytics and the Chrome browser, they have the potential to track a ridiculous amount of web usage… (Are there any services that allow you to use e.g. your DoubleClick cookie to get a view over what data has been collected and stored against that cookie on DoubleClick Google’s databases? That is, can I turn my cookies back on the companies that set them and demand to see what data is associated with them, VRM style?)

- Google has a channel to *huge* audience through AdSense text ads, DoubleClick display ads, and embedded YouTube videos. I’m largely blind to Google AdWords – I avoid right hand side ad-filled columns like the plague – but if Google started putting my upcoming calendar events or priority email headers into the AdSense display box alongside page contextual ads, I might start looking at them as I go to look at my personal messages… Imagine it: the AdSense block, (with a publisher’s permission), including updates from members of your social circle, as well as ads… I guess if the presence of updates (“Personal network messages”, compared to “Sponsored Links”) in the AdSense block increased ad click-thrus, it would make commercial sense anyway..? If I was watching a YouTube video and an urgent/priority message hit my GMail inbox, I could get a lower third alert box appearing in the movie to tell me. And so on…

If you haven’t read it yet, I recommend it: Steven Levy’s In the Plex.

As for me, I’m going to chase this reference that I came across in the book…: David Gelertner’s Mirror Worlds: or The Day Software Puts the Universe in a Shoebox… How it Will Happen and What it Will Mean

I’ve been tinkering with some of my “List Intelligence” code again, and thought it worth capturing some examples of the sort of network exploration recipes I’m messing around with at the moment.

Let’s take @jiscCetis as an example; this account follows no-one, is followed by a few, hasnlt much of a tweet history and is listed by a handful of others.

Here’s the follower network, based on how the followers of @jiscetis follow each other:

There are three (maybe four) clusters there, plus all the folk who don’t follow any of the @jisccetis’ followers…: do these follower clusters make any sort of sense I wonder? (How would we label them…?)

The next thing I thought to do was look at the people who were on the same lists as @jisccetis, and get an overview of the territory that @jisccetis inhabits by virtue of shared list membership.

Here’s a quick view over the folk on lists that @jisccetis is a member of. The nodes are users named on the lists that @jisccetis is named on, the edges are undirected and join indivduals who are on the same list.

Plotting “co-membership” edges is hugely expensive in terms of upping the edge count that has to be rendered, but we can use a directed bipartite graph to render the same information (and arguably even more information); here, there are two sorts of nodes: lists, and the memvers of lists. Edges go from members to listnames (I should swap this direction really to make more sense of authority/hub metrics…?)

Another thing I thought I’d explore is the structure of the co-list membership community. That is, for all the people on the lists that @jisccetis is a member of, how do those users follow each other?

It may be interesting to explore in a formal way the extent to which the community groups that appear to arise from the friending relationships are reflected (or not) by the make up of the lists?

It would probably also be worth trying to label the follower group – are there “meaningful” (to @jisccetis? to the @jisccetis community?) clusters in there? How would you label the different colour groupings? (Let me know in the comments…;-)