Sunday, July 19, 2009
Social media: narcissism, ADHA, stalking
This is a pretty accurate depiction of the what goes on with the users of social media. It makes a good-looking t-shirt!
Friday, July 17, 2009
Personalisation vs. Social
I've been thinking of this personalisation-thing a lot lately. I quite cannot get my head around it, so this blog post is just to mull over the ideas.
By personalisation it is meant that, for example on a learning resource portal, the offer is tailor made for one of the users of the system. There are three commonly known ways of doing this:
Also, not all the users are always interested in doing the work of filling in a profile or rating resources. In one of my studies (Vuorikari, Sillaots, Panzavolta, Koper, 2009) we found very different types of users behaviour, in this case related to how ppl tag (which could be also used for collaborative filtering).
About 33% of ppl tagged content (the arrows going away from the user group in the image), 32% used tags for searching but did not tag themselves (the arrows going towards a user), whereas 35% of ppl did not tag nor used tags at all (in the image the arrow going from LOM towards the group indicating that they used LOM based search methods only).
In this case, I'm interested in the 32% group, who clearly got benefit from tagging that other folks did, but did not do any work themselves (kinda freeriders, if you wish, but I don't mean to be negative).
If we were to use the tagging and bookmarking information to construct a user profile of the users and further use it for personalisation (no: 1 and 2 in the list above), we would be only able to do it for the group of taggers, i.e. 33%. The benefits could only be reaped by that group too, since for the rest of them, we have no profiling information to be used for personalisation.
However, a social tagging system is more about creating "personalisation" for all the users of the system, regardless if we know anything about them and they are willing to put in the time to create a profile and feed it in. It's about making social navigation trails visible to every user of the system, instead of going for "personalisation".
What I think is really cool is that we've shown that we more than doubled the amount of ppl who took advantage of contributions, i.e. from 27% who tag and use tags for navigation to 59% (that is adding the group of 32% who use tags but don't tag).
My assumption is that the rest would not even care about recommendations, etc., as they seem to formulate their searches in a rather acknowledgble way (40% formulate advanced searches; 38% only browse categories and 30% do both).
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Some other thoughts about personalisation:
By personalisation it is meant that, for example on a learning resource portal, the offer is tailor made for one of the users of the system. There are three commonly known ways of doing this:
- Based on self-proclaimed profile (e.g. you say you teach math, so your services are personlised towards math)
- Based on collaborative filtering e.g. ratings (like-minded users, ppl who agree in the past tend to agree in the future) or content-based filtering
- Based on behaviour (e.g. other teachers who used this resource, also used xx)
Also, not all the users are always interested in doing the work of filling in a profile or rating resources. In one of my studies (Vuorikari, Sillaots, Panzavolta, Koper, 2009) we found very different types of users behaviour, in this case related to how ppl tag (which could be also used for collaborative filtering).
About 33% of ppl tagged content (the arrows going away from the user group in the image), 32% used tags for searching but did not tag themselves (the arrows going towards a user), whereas 35% of ppl did not tag nor used tags at all (in the image the arrow going from LOM towards the group indicating that they used LOM based search methods only).
In this case, I'm interested in the 32% group, who clearly got benefit from tagging that other folks did, but did not do any work themselves (kinda freeriders, if you wish, but I don't mean to be negative).
If we were to use the tagging and bookmarking information to construct a user profile of the users and further use it for personalisation (no: 1 and 2 in the list above), we would be only able to do it for the group of taggers, i.e. 33%. The benefits could only be reaped by that group too, since for the rest of them, we have no profiling information to be used for personalisation.
However, a social tagging system is more about creating "personalisation" for all the users of the system, regardless if we know anything about them and they are willing to put in the time to create a profile and feed it in. It's about making social navigation trails visible to every user of the system, instead of going for "personalisation".
What I think is really cool is that we've shown that we more than doubled the amount of ppl who took advantage of contributions, i.e. from 27% who tag and use tags for navigation to 59% (that is adding the group of 32% who use tags but don't tag).
My assumption is that the rest would not even care about recommendations, etc., as they seem to formulate their searches in a rather acknowledgble way (40% formulate advanced searches; 38% only browse categories and 30% do both).
---------------------------------------------------
Some other thoughts about personalisation:
- There are things that I dig, like Amazon, when it tells me "ppl who bought this book also bought xx". Thing thing is, though, that is the stuff that generally makes any user's life better on Amazon. It is not that they personalise the thing for me only, the unique Riina, the one and only, but it is something that makes any users experience on Amazon better.
- the problem with personalisation often is that there needs to be a detailed profile of you that is based on detailed user model that is based on some abstract model that some obscure committee came out with in the 70's. Ok, that's maybe a bit exaggerated, but you get the point - there is a model where you are fitted.
- What if I don't want to be personalised? What if I want to do the same thing as my buddies do; listen to same music as they do, study the same stuff as they do and go shopping with them? I want to share my life and experiences with other people around me because, guess what, through that type of sharing and doing stuff together, I feel related to them, I have things to talk with them and we form a community together. And it is really important for me to be part of that community, because it's part of who I am and helps me to reflect on what's out there.
- Is peronalisation really personalised? It's not actually. By making things personalised to me, what is actually happening is "un-personlisation" of me. My taste is guided to the direction of all the other users, so I am actually being socialised! My personal music recommendations are actually very similar to other listeners, and eventually, it's all going to be the same taste!! Of course, unless there is randomness which offers serendipity.
- Lately with all these micro-messaging things where ppl post their "mood" or what they are doing online ( e.g. I should be tweeting right now: "I'm writing a blog post" and simultaneously have it up on my Facebook), it's kinda funny that they feel this urge to yell out to all what they are doing in their über-personlised world.
Wednesday, July 15, 2009
Palm Pre - I wonder when it might come to Europe?
Already for a long time I've been ready to say goodbye for Nokia. This is a big statement from someone from Finland whose grown up with Nokia. Mind you, when you kid/growing up you wear Nokia rubber boots. Your bike tires are Nokia. I bet at one point there was also toilet paper that they produced, among other things like cable and TVs. And then - the first kännys, the mobile phones in early 90' (Btw, they were not called gsms back in the day, as we used anotehr standard called NMT with much better coverage in vaste areas like in Lapland).
So, my whole active mobile phone user time (which in my case started already in early 80's, dad had a mobile phone in the car which we used to tell mom to turn on sauna when returning from summer house. You actually had to go by a dispatcher and push to talk!) I've stayed fidel to Nokia, and mostly Communicator, which I have had since '03 or something (when they came up with the 2 model).
Anyway, everything turned sour with the last Communicator that I had (E something). They've cut down the awsome shortcuts that used to be there and everything became too heavey and hard to use. Also, the size did not get any smaller. But I did not want to buy an iPhone either, I think no cool kids use iPhone. All the other phones are infested with all Microsoft this and that from which I prefer to shun away. So when I heard about Pre Palm, I took a look at it with no presumptions of the past (I used to hate palms and despite ppl who choose to use such an inferior technology - go and figure)
I so want it, this review is really good. I wonder if I have to wait until they come to Europe or can I buy it from the US? Well, actually just checked on it, by Christmas - geee, that's some waiting.
So, my whole active mobile phone user time (which in my case started already in early 80's, dad had a mobile phone in the car which we used to tell mom to turn on sauna when returning from summer house. You actually had to go by a dispatcher and push to talk!) I've stayed fidel to Nokia, and mostly Communicator, which I have had since '03 or something (when they came up with the 2 model).
Anyway, everything turned sour with the last Communicator that I had (E something). They've cut down the awsome shortcuts that used to be there and everything became too heavey and hard to use. Also, the size did not get any smaller. But I did not want to buy an iPhone either, I think no cool kids use iPhone. All the other phones are infested with all Microsoft this and that from which I prefer to shun away. So when I heard about Pre Palm, I took a look at it with no presumptions of the past (I used to hate palms and despite ppl who choose to use such an inferior technology - go and figure)
I so want it, this review is really good. I wonder if I have to wait until they come to Europe or can I buy it from the US? Well, actually just checked on it, by Christmas - geee, that's some waiting.
Google parsing microformat, e.g. ratings
In May Google announced that they will start parsing microformats (on a small scale first), similar stuff came out from Yahoo! last year, but even on a smaller scale.
This is pretty huge for the end-user generated ratings! I must say that I did not see it coming in this way, which makes it even more exiting :)
So, since a long time it's been problematic to get enough ratings on items, this is a known problem especially in the field of Recommender systems. They talk about "sparse data". An example, you want to make a recommendation on music, but the item x has 3 ratings, item y 2 ratings, etc. This is way too little to be used to create recommendations using the algorithms that are out there. Take another example, a camera shop, they let users rate their cameras, but they get very little reviews from users.
Now, however, there are other camera shops who are struggling with the same problem. Essentially, they all are selling the same camera brands, and they all have only a few ratings on it, and at the end, non of them can do much fun with this small amount of rather anecdotal information.
There has been talk about a unique identifier set by industry, for example, so that all camera sellers could use them and thus aggregate all the reviews and ratings together. Yep, you guessed it, there's maybe that one shop down the blog who does not want to use it. I think a couple of years back Yahoo! came up with a very compelling paper reiterating the idea and trying to muster up enough consensus among industry and other players. Not much happened - and then, here is Google and microformats... beautiful :)
Why I'm interested in this is that with the idea of federating learning resource metadata across repositories, we face the same problem. As a result of sharing metadata, the same resource might end up used in many different repositories, where users might be allowed to rate them. But that metadata on ratings or evaluations is VERY seldom shipped back to the mother board.
The same with tags and bookmarking (other other tools that allow users to create collections or playlists). That could be valuable information for the repository who first federated the resource metadata out. By collecting back the varied annotations from different repositories, they could gain interesting information, and eventually overpass the sparse data problem. Moreover, they would gain data about what works and in which context, which makes me think of "travel well" resources.
In action
Here is an example of a search for Palm's new phone that I'm contemplating on. I search for reviews only and the result list shows the ratings, but I cannot yet make a query saying "palm pre" ratings grater than 3. Nice in any case.
I've had a few ideas on this with some colleagues and I really look forward to seeing what Google comes up with that. And how are they going to solve the issue of different rating scales used, and multi-attribute ratings.
This is pretty huge for the end-user generated ratings! I must say that I did not see it coming in this way, which makes it even more exiting :)
Holy smokes! This is cool, can't wait to see when it will first pop up in my search :)..Google is releasing support for parsing and display of microformat data in their search results. .. anyone who marks their pages up with the appropriate microformat data will be able to make their information understandable by Google. This technology would allow you to explicitly search, for example, for only printers that had an average customer review of 3 stars or higher.
So, since a long time it's been problematic to get enough ratings on items, this is a known problem especially in the field of Recommender systems. They talk about "sparse data". An example, you want to make a recommendation on music, but the item x has 3 ratings, item y 2 ratings, etc. This is way too little to be used to create recommendations using the algorithms that are out there. Take another example, a camera shop, they let users rate their cameras, but they get very little reviews from users.
Now, however, there are other camera shops who are struggling with the same problem. Essentially, they all are selling the same camera brands, and they all have only a few ratings on it, and at the end, non of them can do much fun with this small amount of rather anecdotal information.
There has been talk about a unique identifier set by industry, for example, so that all camera sellers could use them and thus aggregate all the reviews and ratings together. Yep, you guessed it, there's maybe that one shop down the blog who does not want to use it. I think a couple of years back Yahoo! came up with a very compelling paper reiterating the idea and trying to muster up enough consensus among industry and other players. Not much happened - and then, here is Google and microformats... beautiful :)
Why I'm interested in this is that with the idea of federating learning resource metadata across repositories, we face the same problem. As a result of sharing metadata, the same resource might end up used in many different repositories, where users might be allowed to rate them. But that metadata on ratings or evaluations is VERY seldom shipped back to the mother board.
The same with tags and bookmarking (other other tools that allow users to create collections or playlists). That could be valuable information for the repository who first federated the resource metadata out. By collecting back the varied annotations from different repositories, they could gain interesting information, and eventually overpass the sparse data problem. Moreover, they would gain data about what works and in which context, which makes me think of "travel well" resources.
In action
Here is an example of a search for Palm's new phone that I'm contemplating on. I search for reviews only and the result list shows the ratings, but I cannot yet make a query saying "palm pre" ratings grater than 3. Nice in any case.
I've had a few ideas on this with some colleagues and I really look forward to seeing what Google comes up with that. And how are they going to solve the issue of different rating scales used, and multi-attribute ratings.
Vuorikari, R., Manouselis, N., & Duval, E. (2007). Metadata for social recommendations: storing, sharing and reusing evaluations of learning resources. In D. H. Goh & S. Foo (Eds.), Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively (pp. 87-107). Hershey, PA: Idea Group Inc. Retrieved from http://elgg.ou.nl/rvu/files/20/144/SIR_vuorikari_manouselis_duval_web.pdf.
Manouselis, N., & Vuorikari, R. (2009). What if annotations were reusable: a preliminary discussion. In M. Spaniol (Ed.), Advances in Web-Based Learning - ICWL 2009, Lecture Notes in Computer Science (Vol. 5686, pp. 255–264). Berlin Heidelberg: Springer-Verlag.
Friday, July 10, 2009
Tags and self-organisation: a metadata ecology for learning resources in a multilingual context
I think I finally came up with a title for my PhD. You know, the type of title that says it all. It's a bit long, but "correct and descriptive", like Matt said. So here it goes: Tags and self-organisation: a metadata ecology for learning resources in a multilingual context.
Here is a wordle, it was extracted from a paper that summaries the research. Looks pretty accurate :)
Here is a wordle, it was extracted from a paper that summaries the research. Looks pretty accurate :)
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