Print

Print


*****  To join INSNA, visit http://www.insna.org  *****

I'd agree that costly behaviour should certainly make for be a better index
- but (and maybe I've missed something here) doesn't our awareness of this
suggest that Amazon's publishing of the 'people who bought this also bought'
links must bias the data we're seeing? After all, if it didn't, why would
Amazon use it?

Much as I love the diagrams at OrgNet, I wonder if the sub-groups would be
so clearly delineated if Amazon didn't encourage us to follow the behaviour
of others. I wonder just how much of the structure could be predicted from
the presence of feedback alone. Somebody must have modelled this?

Mark Round
QinetiQ


-----Original Message-----
From: Social Networks Discussion Forum [mailto:[log in to unmask]] On
Behalf Of Valdis Krebs
Sent: 03 January 2007 15:29
To: [log in to unmask]
Subject: Re: Recommender systems

*****  To join INSNA, visit http://www.insna.org  *****

That paper appears to look at...

> user practices in online product reviews at several leading  
> ecommerce sites

Yes, written reviews are easy to spin... release a book, get all of  
your friends/bots to write a good review on Amazon.  Most books [non- 
bestsellers] have < 10 written reviews -- not hard to get a + majority.

What matters is the actual buying behavior -- putting your money  
where your mouth/keyboard is.  Actual purchase patterns are hard to  
spin unless you have a lot of money and a strong agenda.  ;-)

Valdis


On Jan 3, 2007, at 1:26 AM, Lisa Stampnitzky wrote:

> *****  To join INSNA, visit http://www.insna.org  *****
>
> Trevor Pinch has also been doing work on recommender/reviewer  
> systems- see
> e.g.
> Shay David and Trevor Pinch "Six degrees of reputation: The use and  
> abuse of
> online review and recommendation systems"
> http://papers.ssrn.com/sol3/papers.cfm?abstract_id=857505

_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.

The information contained in this E-Mail and any subsequent
correspondence is private and is intended solely for the intended
recipient(s).  The information in this communication may be confidential
and/or legally privileged.  Nothing in this e-mail is intended to
conclude a contract on behalf of QinetiQ or make QinetiQ subject to any
other legally binding commitments, unless the e-mail contains an express
statement to the contrary or incorporates a formal Purchase Order.

For those other than the recipient any disclosure, copying,
distribution, or any action taken or omitted to be taken in reliance on
such information is prohibited and may be unlawful.

Emails and other electronic communication with QinetiQ may be monitored
and recorded for business purposes including security, audit and
archival purposes.  Any response to this email indicates consent to
this.

Telephone calls to QinetiQ may be monitored or recorded for quality
control, security and other business purposes.

_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.