But off course my brain is not on hold, even though it functions a bit slower when its varm ;-) The little gray cells needs exercise. Like Mr. Hercule Poirot would have put it. So what am I contemplating these days?

Well I made my first map of users and their tags:

The map doesn’t say much, but I like to look at it ;-) It like when you learn to program, and you study methods and functions, loops and logic. Then you make your first little program, a Hello world. It’s only a little program that prints Hello world on the screen. But all the sudden the lines of code isn’t just lines of code, It’s a sort of physical representation of ones thoughts. The map is made by the software Pajek. After my holiday I will continue my work with Pajek and with UCINET (Another social network analysis software).

Another thing thats occupying my thoughts these days are clarification of concepts. It started when my supervisor Jesper started asking questions about some of the generally accepted terms. This has lead my to elaborate a lot on which terms I prefer and why I do so. I have constructed a Wiki with the help of our Wiki expert Hans Andersen. My Wikics (Wiki + Charles + Seger) is constructed for my work with concepts, and it is hosted by our IT-lab.

When I get back from my holiday I also has to write a paper about my employment of informetric methods.

So thats my summer laid out for you ;-)

Here is a pdf of my presentation: presentation-of-charles-phd-project-folksonomies-umea-2008
It is a very open ended short presentation, so that I could get a lot of feed back. IT worked ;-)

And here is a selection of all the comments. Thank you Tanja for the minute, I wouldn’t have managed to get all points without help.

Comments:

Jesper: It’s important that you look closer on yours research questions.

What’s your unit of analysis?

The dataset should answer the research question.

Maybe your study is to general.
You could split it up in 2 or 3 parts: tags, Information objects and functions
- Then you can get a better overview over the connection to the users.

Kim: “the anonymous professor” has had a blogpost of the visualization of very large datasets.

About connectivity… There is a collection in WoS [Web of Science] named network connectivity.

Raf: When you make a social network analysis, whats the link between two users?
You can “follow” users with similar interests.

Sara: Can you see inlinks or subscriptions as a object for connectivity (How users are connected through their subscriptions)

Tjeck bloglines, maybe you can follow users subscription here.
Kim: I’m not sure you can do that, these data are most often private.

Birger: Try to triangulate / cross check your study

Björn [Swedish]: If you have a group of users, maybe you can:

See how they connect through an information object
and
See how they defines the same information object
And lastly compare the two?

Kim: Can you not just study the users who employed notes in their posts?
You can then make a co-word analysis on that data…

Birger: Find focus! What do you want to test? Maybe your case should be defined differently, with a group of users in center.

Birger: How will you measure success?
Find criteria!

Jesper: See diffusion theory - how well does people connect through a 3. person

Richard Klavans: Adoption theory are better, a more precise speed of adoption

Sara: Has the dates you collected any meaning?
Can you reduce the data on the basis of the dates?

Birger: You can also cut a year back in the data, and then cut another year. Then you will have a benchmark.

Jesper: You need to define the central concepts in your study.
Connectivity!
Operationalize the concept.

How will you connect the users you investigate?
The way you connect them will reflect their connectivity.

THANK YOU ALL FOR THESE VALUABLE COMMENTS

VanderWal writes about the differences between the terms collaborative and collective.

Collaborative is consensus seeking and “usually aims at completeness”. It’s when the group of users’ effort is to reach a common agreement about the object in question. This could for example be what tag to use in describing an information object. Many studies of folksonomies has this approach about the users tags.

The collaborative approach reminds me Hidderley & Rafferty’s (1997) presentation of the concept of democratic indexing.
Democratic indexing is indexing where a group of users are given a set of keywords describing an information object. The users then chose the keywords which best reflects their view of the information object. The keywords chosen are then piled into a set and presented to other users, who chose which of these keywords the prefer. Democratic indexing is thus a reconciliation process, where users collaborative chose the terms used in indexing (Lancaster, 2003, p. 12).

Back to VanderWals post…
Collective is when each users perception of the information object is important.

“The [information] object is the focus of collective, the individual’s voices and annotations are held separate as each individual is working as an individual.”

This describes an approach that I find much more interesting. I think that it is in collective approach, we really can tab in to the full potential of folksonomies. I am interested in utilizing the power of folksonomies without disregarding each user’s individual choices (tags). The user’s choice of one term over another constitutes a decision based on the user’s interest, context and overall preferences. The terms chosen by the users encode different meaning. User’s who add the same tags to a resource, must be interested in the same information tagged by others with the same tag. Shirky gives an example of people interested in motion pictures, some describe their interest as film, others movies or cinema. The point is, according to Shirky (2005) that it should be this way, because “[the] movie people do not want to hang around cinema people”.

References
Hidderley, R. & Rafferty, P. (1997) Democratic indexing: an approach to the retrieval of fiction. In: Information service and use. 17 (2-3). p. 101-109.

Lancaster, F. W. (2003). Indexing and abstracting in theory and practice. London, Facet.

Shirky, C. [2005]. Ontology is Overrated: Categories, Links, and Tags. In: Clay Shirky’s Writings about the Internet Economics & Culture, Media & Community, Open Source. URL: http://www.shirky.com/writings/ontology_overrated.html

I gave a short presentation of delicious and some models on users information behaviour, and then I opened up for discussion in plenum. The implicit lack of control in folksonomies like delicious can still stir a big craze among librarians, and it is always interesting to discuss control in different contexts. Unfortunately I only had 45 min (included discussion), I think that I could have used more time.

The presentation can be seen here (in Danish):

Mødet med Brugerne

All in all - I think it went rather well… In fact it went superb :-)

René Steffensen took the following photo of Thomas Vibjerg Hansen, Trine Schreiber and me:

http://www.flickr.com/photos/renesteffensen/2513678273/

]]> http://www.folket.org/index.php/2008/deff_brugernes_dag/feed/ http://www.folket.org/index.php/2008/network-with-me/ http://www.folket.org/index.php/2008/network-with-me/#comments Thu, 15 May 2008 08:48:12 +0000 Charles http://www.folket.org/?p=46 As I have been raving on about, everything is social these days. It seem like everyone is connected through facebook, linkedIn and other networks. I have connected with folks I haven’t seen for 20 year, and it’s actually quite interesting. I think these tools are a bit addictive ;-)

Talking about Facebook…

LoL

Many interesting viewpoints have emerged. It started with a question by Liddy Nevile:

I would like us to think carefully again about calling it social tagging - I suspect that ’social’ tagging has a theoretical implication - that it’s tagging done ‘for society’ or ‘by society’ and we should not be careless about these terms. Different motivation might mean different ways of thinking about and using the process of tagging.
What do you think???

Pete Johnston replied :

Tagging may be social or “non-social”. It becomes “social” when it’s - to some degree at least - “negotiated”

And put a refernce to a post he made back in November 2006: The “social” in social tagging

My thoughts on the matter is that the process of adding tags to resources, does not have to be social (as I defined in an earlier post about what does social means), but it can be. On the other hand the collection of all the users applied tags must be some sort of social organization. It becomes social when it no longer just concerns one user, but is something that involves many users and the ties between them. I find that the social aspect starts when one see the tags as something that is tying users together.

So here’s a list of some of the hardware I use in my work:

White board
A White board is a great tool for seeing connections and thinking. I probably use mine most to think about ideas/problems. I draw/write them on the white board, and then I walk (literally) around my office looking at the white board - It usually helps.

Pencil
I use a Caran d’Ache fixpencil 3. When I was a child, I used to go with my farther to his work on Saturdays. My father is an architect, and he always used these kinds of pencils, so naturally enough I always drew with them. Last year my father asked me what I wanted for Christmas, all I could say was “‘One of your pencils”. And I got one - Thanx Dad :-D

Journal
Moleskine cahier journal (soft cover, extra Large: 19 x 25 cm)

Which always are with me, ready for new ideas to be plotted down.

Post It (7 x 12 cm)
Post-it are superb for plotting down ideas at night (when its dark). This way I don’t wake up my family, just because I wake up with an idea to measure tags.

Mobile Phone
I use a Nokia N73 mobile phone with extended 2 gb. memory card. The two main uses of my phone is: Calendar (synchronized with Outlook) and the camera (Carl Zeiss optics) I use this device to keep track of meetings and to document my every day life by uploading to my flickr account.

One of the reasons for me to buy just this phone was N73s ability to take pictures in poor lightening conditions.

Laptop
I use a HP Compaq nc8430 which suits my needs. I am not really a tech geek when it comes to computers, I am satisfied when I can trust the machine.

Theres probably many tools which I forgotten to write about.

Wikipedia has many more or less helpfull definitions. In the introduction there’s a rather good sentence

“…its meaning is at times vague, suggesting that it is a fuzzy concept.”

Another is that social means Interactions between people (social interaction)

The German Wikipedia has a better definition

“In der Umgangssprache bedeutet „sozial“ den Bezug einer Person auf eine oder mehrere andere Personen”

[In colloquial language social means the reference of a person to one or more other persons] Translated by me

Oxford English Dictionary says social is the

“Capable of being associated or united to others”
“United by some common tie”

Oxford Dictionary of Sports Science & Medicine in Medicine [requires login]:

“Pertaining to the interaction humans have with one another, either as individuals or in groups.”

Good old Merriam Webster dictionary:

“…of or relating to human society, the interaction of the individual and the group…”

It seems like the term social only mostly is defined by the a jointing term. Social interaction is clearly described in many dictionaries while social tends to lack proper definition.

So what is social in the context of my research?
Social tagging: is a term often used for user generated metadata, the action where a user index an information object. What so social about the actual indexing (tagging)? I truly believe the result of the tagging, the folksonomy is some sort of manifestation of a social nature, but the process of tagging is an individual action. Maybe the folksonomy can be regarded as a social organization (thank you Jesper for the definition).

I don’t think I come any closer to a definition right now - But the quest continues.

Problem defined:
• How does Dogear support social navigation?

Methods used:
By log file analysis the users information behaviour were charted. Log file analysis is the analysis of user logs stored on a server (for more on this subject see the discussion section of this paper). The log files were from a 8 month period and consisted of 2579 users and 58532 bookmarks in Dogear. Included in the log file were the following user actions: creating-, deleting- and editing a bookmark, bookmark clicks, user bookmark owner identifier and a date- and timestamp.

Findings:
98,7 % of the users used tag of people links to browse trough the bookmark collection. The most frequently used way to browse bookmarks were to click on another user’s name.

Discussion:
Millen & Feinberg (2006) states that they among other methods use log file analysis to study user’s information behaviour. I think that log file analysis is a powerful tool which can give data about user actions on a particular website/information system. A log file analysis consists of an analysis of a series of user log files (Haigh & Megarity, 1998). These user log files are server stored data about user browser request to the server. When a user wants to view a web page, the users internet browser makes a request to the server the webpage is hosted by. In this request there are system data about the user.
Normally this data is:

• -IP-address (unique identifier of the server the user is using)
• - Which browser is making the request
• - Screen resolution of the user
• - URL for the file requested
• - Protocol used for the request
• - Size of the file requested
• - Referring URL (which webpage the user comes from)
• - Internet browser and operating system used by the requesting computer
• - Date- and time stamp of the request (Haigh and Megarity, 1998)

This user log data is stored on the server every time the browser makes a request for data. So if a user activate a hyperlink on a web page, and immediately regrets the action and activates another hyperlink (or clicks stop in the browser), this is registered as a visit on the web page. There are off course many way that this data could be filtered out. That is why, any log file study need to be very explicit in the description of the method used.

There are several challenges with using log file analysis in regard to measuring users’ information behaviour. Two major issues concerning the log file study’s reliability and validity shall be mentioned here.
The first one is about using log files as a measure of web traffic. As a server log, consist of requests made to the server, the users accidental click on a hyperlink is registered as a visit and a view of the page in question. There is of course many ways the secure validity in this, but Millen &Feinberg (2006) do not describe how they collected the user data, which methods they used as data filtering or how they made the log file analysis.
Another challenge in using log files to investigate users information behaviour is mentioned by Ingwersen & Järvelin (2005), who warn about using log file analysis alone and not combining it with other more qualitative approaches. A log file lacks the ability to say anything about the user’s intensions and thoughts during the transaction (p. 248). So to say that the users wants or likes to use a certain system (here Dogear) from a log file analysis is interpreting the data. But I like the study nevertheless, and not just because the results suits me ;-)

References:
Haigh, S., Megarity, J. (1998). Measuring web site usage: log file analysis. In: National Library of Canada, August 4,
URL: http://www.collectionscanada.gc.ca/9/1/p1-256-e.html

Ingwersen, P., Järvelin, K. (2005). The turn: Integration of Information Seeking and Retrieval in Context. Berlin: Springer.

Millen, D. R. Feinberg, J. (2006). Using Social Tagging to Improve Social Navigation. In Workshop on the Social Navigation and Community-Based Adaptation Technologies. Conjunction with Adaptive Hypermedia and Adaptive Web-Based Systems (AH’06). June 20th, 2006, Dublin, Ireland.
URL: http://www.sis.pitt.edu/~paws/SNC_BAT06/crc/millen.pdf

Millen, D. R., Feinberg, J., Kerr, B. (2005). Social bookmarking in the enterprise. In Queue. 3 (9).

I don’t think readers will notice the difference ;-)