Monday, November 24, 2003

More of interest with social networks

Via iaslash, here are a couple of articles by Stowe Boyd on social networks: The Promise and Pitfalls of Social Networking and Cracking the Social Code. I especially appreciate this opinion in the light of my previous thoughts:

"It is perhaps true that the enemy of my enemy is my friend, but it is not clear that the friend of my friend is a friend of mine. Trust and regard attenuates rapidly in human relationships: a friend of a friend of a friend is unlikely to bring much social juice to bear. Except in narrowly defined and strongly affiliated groups (like religious sects, fraternities or within corporations), this transitivity of social capital does not really work."
I think I'll have to think this through in a more socio-mathematical way - what aspects of online trust that are of value can be tracked and transmitted and how can these be usefullly exploited?

Wednesday, November 19, 2003

It's not who you know in social networks

Via the New Scientist (15 November 2003) some detail of research by Cornell University into algorithms to track the most influential members of a network (as opposed to the best connected). Interesting...hmmm.

Making stuff useful...again

I've already ranted about this multiple times. Here's a back up quote via an interesting article called Design by or for the people? (via Infodesign) from Robert Brunner:

“it really doesn’t matter if something is usable. What matters is that it is in fact, useful. And even better if it is desirable."
. Let's make stuff useful - usability is a part, not the whole of this equation.

Wednesday, November 12, 2003

Blogging, memes, value

Was reading Knows and Memes from Many to Many - reminded me of the piece I was writing a while ago called Weblogs: dynamics and value. Strikes me that the transmission of memes "themes" could usefully expand some of my thoughts...

Wallop - Microsoft and the social network

Maybe this is the sort of hook that trust-based search could leverage: Microsoft is apparently developing wallop, which leverages Instant Messaging groups and contacts for "social software" purposes. Not much detail available yet.
Read the following:

Peter M's opinions about epinions have sparked my interest, I must check it out a bit.

Tuesday, November 11, 2003

Photographs of me (and others, natch)!

In entirely solipsistic and self-absorbed fashion, here are links to photos of me, my beautiful girlfriend Severine (to whom I'm getting married in a fortnight!) and Eric who came to pay us a visit in Glasgow a couple of weeks back

Just a bunch of interesting stuff: information visualisation, search...

Shirky, the Semantic Web, and even more on recommendations

I was reading Clay Shirky's The Semantic Web, Syllogism and Worldview, and found it a very interesting and challenging article. I do have a couple of thoughts on his ideas, however, and am not in total agreement.

  1. The semantic web is (initially) probably likely to be most useful for simple logic statements as opposed to more complex combinations.

  2. Examples of syllogisms are syllogistic in their nature: if insufficient or contrary information is given, then wrong conclusions will always be jumped to - garbage in, garbage out. The Brooklyn accent example, for instance, could be resolved by removing the generalisation.

  3. I agree that deductive reasoning alone is unlikely to create artificial intelligence, but a basic set of rules about the nature of things could form the basis for more complex probablilistic reasoning, I reckon. (Not that I'm claiming to know much about AI)

  4. Of course ontology creation is political and has a social context: all ordering and classification is. We comprehend the world through arbitrary symbols - why write an article if you don't trust the arbitrary rules of words and grammar? This is why I reckon that the semantic web isn't going to bea coherent whole (if it happens), but a series of smaller, overlapping (rather than co-incident) ontologies.

Anyway, I'd recommend the scepticism of the article: healthy, intelligent stuff. On another note, I noticed the following with interest toward the article's close:

"Social networking services [...] assume that people will treat links to one another as external signals of deep association, so that the social mesh as represented by the software will be an accurate model of the real world [...] and as a result, links between people on Friendster have been drained of much of their intended meaning. Trying to express implicit and fuzzy relationships in ways that are explicit and sharp doesn't clarify the meaning, it destroys it."
my italics
I don't 100 per cent agree with this. Yes, you cannot express the "true" value of a social network in this way, but if you are honest about precisely what you are attempting to achieve and the fact that the attempt is not going to be a perfect representation, then what's the problem? In my trust model, saying I trust B's opinion on everything is far from close to saying I really trust B's opinion on ice cream, trust him slightly less on sorbet, and don't trust him at all on frozen yoghurt, but I can gain value from expressing this relationship of "general" trust, and it is a far more maintainable (and therefore valuable) network for this.

Here are some comments from others more worthy of commenting than myself (care of Blogdex):

Monday, November 10, 2003

Yet more recommendations

The paper from Macedo et al isn’t a million miles away from my idea. Essentially, it appears that their WebMemex system (apologies to Mr V. Bush? He’s in the references!) is made up of a tool to track a users web activity (ie. a record of page requests), a tool to link documents together by commonality of terminology (using Latent Semantic Indexing theory), and a system to recommend documents via the web activity of other people in an identified group.

There are a few things I found interesting and useful in this approach (other than Latent Semantic Indexing, which I read about, but didn’t understand, in another paper on a different issue):

  1. no recommendations are made per se – this is a tool that shares browsing activity;

  2. the yahoo chat buddies system is used to identify the social networks;

  3. trust is considered to be a reciprocated buddy, and you must have two or more reciprocated buddies for the system to work in order to protect the privacy of an individuals browsing path (with recommendations from only one buddy, you would know exactly which pages your buddy had visited).

I really like the fact that the social network is established outside of the application itself. The ties of trust should be able to work for other non-overlapping applications (in the same way that Sainsbury’s, BP, Barclaycard and Debenhams and share the Nectar Loyalty card): say for instance that Google, Amazon and Lastminute all used the same outsourced “trust” recommender system. This would reduce the burden on the user of duplicating information (single sign-on and then opting in to which companies can use your information), make it easier to maintain and much more likely that people would sign up to it (I reckon).

Equally, I appreciate the touch of protecting privacy through the use of a trust network only being valuable with anonymised input. I trust my friends’ opinions, but I don’t necessarily want to know which friend has made the recommendation (online trust being different in many ways to face-to-face trust).

It’s also made me think a little bit more about the trust network: where does the value come into play? I don’t really agree that reciprocation is necessary for trust – it’s more a case of mutual trust, so I don’t think it should affect any “trust values”. Additionally, I feel that mutual trust networks are more likely to be closed: closed networks in being less expansionist are less likely to be of use in covering a large dataset. I think that stronger and weaker trust links may overcome this: if I trust person A who in turn trusts person B, I may have some implicit trust in person B’s opinion, albeit at a lower level than that which I have with person A. As a rule of thumb, I would have thought that the small world six degrees of separation could express the outer boundary of trust value.

On another point, the principle of “it can be assumed that friends have common understandings and interests” expressed in the paper is an important one for trust. We cannot be 100% sure that I always trust A’s opinion on every matter, but it will be too time-consuming a task to filter out the unnecessary information. However, if the above assumption is true, value should come from the fact that A makes his recommendations in generally similar spheres to your interests, and that you are likely to be searching for recommendations within these spheres – which is the whole principle behind the pattern-matching side of recommendation engines anyway.

Overall, I have returned to my original idea, that, rather than seek to augment the quality of overall search results with a “trust weighting”, which I have been informed may be mathematically muddled in principle, a “search trusted sources” advanced option is the best bet. Essentially this could mean that a search engine could use keyword matching and popularity for a general trawl search where you’re just looking for as much information as you can find on a particular subject, and offer a “trusted sources” search where you really need to believe in the quality of the found artefacts (and then other searches for particular, known items etc.)

Anyway, this all bears a lot more structured thought than 15 minutes bashing it all out on a keyboard – I might return to this subject later. All comments appreciated, particularly those that may point out the errors in my logic!

Friday, November 07, 2003

Recommendations again

I haven't had a chance to read the full study yet, but the following from Automatically sharing web experiences through a hyperdocument recommender system
sounds very close to my idea:

"As an approach that applies not only to support user navigation on the Web, recommender systems have been built to assist and augment the natural social process of asking for recommendations from other people. In a typical recommender system, people provide suggestions as inputs, which the system aggregates and directs to appropriate recipients. In some cases, the primary computation is in the aggregation; in others, the value of the system lies in its ability to make good matches between the recommenders and those seeking recommendations.In this paper, we discuss the architectural and design features of WebMemex, a system that (a) provides recommended information based on the captured history of navigation from a list of people well-known to the users --- including the users themselves, (b) allows users to have access from any networked machine, (c) demands user authentication to access the repository of recommendations and (d) allows users to specify when the capture of their history should be performed. "

More once I've read it.

Tuesday, November 04, 2003

Recommendations updated

If it's worth saying...then someone's already said most of it in a better fashion already! Check out this detail on search from Autonomy (obviously). Although it doesn't touch on my trust issue, it does cover the pros and cons of the other bits and bobs, and talk about Bayes much more authoritatively.