… visu­al­iz­ing your tags :)

The “Tag­ging” book by Gene Smith is out. I am still await­ing a paper copy, but had a chance to look at the online ver­sion already. It looks really com­pre­hen­sive, con­cise and cov­er­ing all impor­tant tag­ging con­cepts. Which is not easy for such a mov­ing tar­get topic.

Besides, my elas­tic tag maps visu­al­iza­tion is fea­tured on p.102f. Nice!

There is an inter­est­ing dis­cus­sion with David Wein­berger (author of “Every­thing is mis­cel­la­neous”) going on at the Well about folk­sonomies and metadata.

> Tag maps v5

PS: 12 days to go, wish me luck!

My the­sis is due pretty soon, so I am cur­rently writ­ing A LOT and make some on–the–go beau­ti­fi­ca­tions to my experiments.

First one is the emerg­ing top­ics his­togram. I fol­lowed my own advice and ver­ti­cally cen­tered the stacked his­togram. Addi­tion­ally, I never liked those sharp edges, so now I do not only “fade out” tags visu­ally, but also fade them in, result­ing in a much more organic pic­ture, and largely improved read­abil­ity of the chart. New color scheme: old tags are cold, freshly intro­duced ones in warm color. This is all very much inspired by the fab­u­lous last.fm charts by Lee Byron — thanks!

new inter­ac­tive ver­sion here

and some pix:

Another visual exper­i­ment on tag­ging: How do indi­vid­u­als use tags — com­pared to the com­mu­nity? Do you use pri­vate lan­guage or are you a main­stream tag­ger? When you tag with “design” — do the oth­ers think it is “art”?

On the left: the per­sonal tags for the per­sonal book­marks — ordered by fre­quency — the con­tain­ing box per is log-scaled so you get an impres­sion of the long–tail posi­tion of a tag. Which means: Often used tags are large, bright and go to the top.

On the right: com­mu­nity tags for the tagged ressources.

In the mid­dle: tags with the same name are con­nected. If a line is hor­i­zon­tal, the ind­vid­ual and the com­mu­nity essen­tially agree on the rel­e­vance of the tag for the ressources. The steeper it is — the larger the dis­agree­ment. If no line starts at a tag, it means it is not present in the other list

So in the pic­ture above, you can see my tags. Same facts you can read from the pic­ture: • “m.a.thesis” is a very often used, but pri­vate tag of mine. • The ressources I tag in gen­eral are mostly tagged with “design” by the com­mu­nity. I, how­ever, use the tag “design” much less often. • “news”, “seman­tic web”, “web­dev” are tags I use often, but not the com­mu­nity. etc.

And often course, you can click indi­vid­ual tags to see what the com­par­i­son is like for sub­sets of the book­marks. That’s espe­cially inter­est­ing for obscure tags like “guru” — you can see what the tag­ger “means” by look­ing at the dis­tri­b­u­tion of the com­mu­nity book­marks (in this case “design — art — pro­gram­mer — artist”). Interesting!

Some more shots:

I wish I could say “click here for the inter­ac­tive ver­sion” as usual — but unfor­tu­nately, del.icio.us offers a JSON API, but did not put a crossdomain.xml file on their server. Which means the visu­al­iza­tion (which runs nicely on my hard­disc) can­not load data when put in the web. Bum­mer. I hope I can fig­ure some­thing out.

So for now — I can only offer a down­load link. Click the index.html. You might have to adjust you Flash player secu­rity set­tings in order to load the com­mu­nity tags. Caveat: The appli­ca­tion is still a bit buggy and pretty heavy con­cern­ing proces­sor ressources.

I am cur­rently work­ing on trends in indi­vid­ual tag­ging behav­iour. You might have seen a first, ani­mated ver­sion of my stud­ies based on tag maps. The orig­i­nal ani­ma­tion shows the emer­gence of pre­vi­ously rarely used tags over time. Now I dug deeper and made a richer visu­al­iza­tion for inves­ti­gat­ing this topic.

For the impa­tient: » Check out the inter­ac­tive ver­sion here

And here’s the explanation:

It has been shown before (for a plau­si­bil­ity argu­ment, also check out the mar­vel­lous clouda­li­cious tool, where you can track tag pro­por­tions for any web­site on the web), that tag pro­por­tions for ressources sta­bi­lize over time. Which means that the tag cloud rep­re­sent­ing a tag pro­file for a resource does not change much, once a suf­fi­cient num­ber of tags has been col­lected. In a folk­son­omy, this is gen­er­ally con­sid­ered a good sign, since this indi­cates a cer­tain agree­ment on how to judge a cer­tain ressource and what vocab­u­lary to use.

For tag­ging indi­vid­u­als, and com­mu­ni­ties, this might — at first glance — hold true as well. Con­sider the fol­low­ing the visu­al­iza­tion of a tag­ging com­mu­nity’s evo­lu­tion, for example:

Each tag is assigned a band, with the thick­ness indi­cat­ing the over­all summed usage of a tag over time (time runs left to right). Thus, a ver­ti­cal cut through the graph cor­re­sponds to tak­ing a tag cloud snap­shot at this time point. The ver­ti­cal order is based on the over­all fre­quency of the tags. The color is used to to give an impres­sion of the long tail dis­tor­tion — if all tags would appear equally often, you would see a lin­ear tran­si­tion from red to green instead of the skewed dis­tri­b­u­tion. So — what do we see? Appar­ently, most of the bands seem to grow in par­al­lel, indi­cat­ing a sta­ble growth pro­por­tion for all tags. Of course, we can­not see much for the smaller tags, and there are some edgy parts of the graph which might indi­cate dif­fer­ent behav­ior at spe­cific time points, but over­all — pretty sta­ble impression.

How­ever, this does not make much sense. For indi­vid­u­als and com­mu­ni­ties, the top­ics of inter­est evolve over time, so there must be some hid­den vari­abil­ity not cap­tured by the visu­al­iza­tion and the under­ly­ing lin­ear model.

So I decided to pro­vide an alter­na­tive visu­al­iza­tion for the data based on a decay model, where tags “age” over time and finally get “for­got­ten” if they are not used any­more. This idea is loosely based on the Yules-Simon mem­ory model for tag gen­er­a­tion pre­sented in this paper.

A rad­i­cally dif­fer­ent pic­ture emerges. Not only does the over­all shape now nicely dis­play phases of com­mu­nity activ­ity over time, but also the life cycle of sin­gle tags is much more trans­par­ent. You can rollover sin­gle lay­ers high­light it and dis­play the cor­re­spond­ing tag name. Great fun.

» Check out the inter­ac­tive ver­sion here

What I am now curi­ous about: – Is there a cor­re­la­tion between time-dependency and over-all fre­quency of tags? In other words, are fre­quent tags more evely dis­trib­uted over time, whilst the low fre­quency tags tend to be more vari­able over time? – Is there a cor­re­la­tion between tem­po­ral syn­chro­niza­tion and gen­eral co-occurrence? Which means — do related tags also appear and dis­ap­pear together over time?

I think the answer is YES to both ques­tions, but that would def­i­nitely need some sta­tis­ti­cal analy­sis (any bored neu­ro­sci­en­tists around to help me? ;)

To-dos for the visu­al­iza­tion: – Imple­ment a slider, so you can see how a lin­ear and decayed tag cloud would have looked like at a spe­cific time point. – Sta­men got it right: Maybe I should have plot­ted from the ver­ti­cal cen­ter. Or at least pro­vide an optional inver­sion of the sort­ing. Because right now, all the top (green) lay­ers are really dis­torted, mak­ing visual analy­sis really hard. – Put some num­bers on the axis – Show sin­gle tag­ging events on rollover. Or even “unfold” the layer to improve read­abil­ity and avoid misconceptions.

A very nice paper on the “laissez-faire librar­i­an­ship” often asso­ci­ated with tag­ging vs. more struc­tured seman­tic web approaches. Most notable is that the dis­cus­sion is put in the con­text of Husserl’s the­ory of reflec­tions, inten­tion­al­ity and intersubjectivity.

A PHENOMENOLOGICAL FRAMEWORK FOR THE RELATIONSHIP BETWEEN THE SEMANTIC WEB AND USER-CENTERED TAGGING SYSTEMS

D. Grant Camp­bell Fac­ulty of Infor­ma­tion and Media Stud­ies Uni­ver­sity of West­ern Ontario
Lon­don, Ontario N6A 5B7, Canada

Abstract This paper uses Husserl’s the­ory of phe­nom­e­nol­ogy to pro­vide a model for the rela­tion­ship between user-centered tag­ging sys­tems, such as del.icio.us, and the more highly struc­tured sys­tems of the Seman­tic Web. Using three aspects of phe­nom­e­no­log­i­cal theory—the move­ment of the mind out towards an entity and then back in an act of reflec­tion, mul­ti­plic­i­ties within unity, and the shar­ing of inten­tion­al­i­ties within a community—the dis­cus­sion sug­gests that both tag­ging sys­tems and the Seman­tic Web fos­ter an inter­sub­jec­tive domain for the shar­ing and use of infor­ma­tion resources. The Seman­tic Web, how­ever, resem­bles tra­di­tional library sys­tems, in that it relies for this inter­sub­jec­tive domain on the con­scious imple­men­ta­tion of domain-centered stan­dards which are then encoded for machine pro­cess­ing, while tag­ging sys­tems work on implied prin­ci­ples of emergence.

As promised, here is an update to the tag maps appli­ca­tion I intro­duced below along with some explanations.

For the impa­tient: HERE’S THE LINK

(Update again: The lat­est ver­sion can be found here)

And for the curi­ous: Here’s the expla­na­tions: (more…)

You might have seen the tag clouds posted below. I cal­cu­late tag posi­tions based on co-occurrence, such that tags used together are placed closer to each other. Addi­tion­ally, tags are scaled áccord­ing to fre­quency.
A gen­eral prob­lem I have with the result­ing rep­re­sen­ta­tion (and com­mon tag clouds as well) is the fact, that every tag occur­rence is weighted equally. As a result, these tag clouds never rep­re­sent the cur­rent state of inter­est, but a very slug­gishly chang­ing sum­mary of your archive. How­ever, your inter­ests and the cor­re­spond­ing vocab­u­lary keeps mov­ing on. So I am cur­rently inves­ti­gat­ing trends in tag clouds and how groups of related tags emerge and dis­ap­pear again.

A first glimpse into the dynam­i­cal nature of tag structures.

I am cur­rently orga­niz­ing my lit­er­a­ture on tag­ging. When I started with research on that topic about a year ago, you could count the num­ber of sub­stan­tial con­tri­bu­tions on one hand. Over the cur­rent year, how­ever, the num­ber of papers on this topic has sky-rocketed, which makes the whole area hard to over­see at the moment.

I will start with an overview of my sub­jec­tive must-reads for now (all linked to citeulike):

(more…)