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Interesting article in today’s WSJ about Ebay and computer scientists who track fraud through algori

LongacreLongacre Posts: 16,717 ✭✭✭
I don’t have a link to the article in today's Wall Street Journal, but it is pretty interesting. I am no math geek, so bear with me as I try to explain the article. A group of computer scientists from Carnegie Mellon developed a theory called “bipartite core” in order to predict fraud on Ebay. A bipartite core is a term from math and computer science that describes a situation where members of Group A will deal with members of Group B, but never with each other; the pattern become apparent when the interactions of the two groups are plotted on a graph.

To my simple mind, an example of this is a fraudster creating multiple Ebay accounts and creating multiple accomplice accounts and generating positive feedback with related party transactions and a few outside people. The article explains this a lot better than I can, but supposedly these computer scientists created an algorithm that can analyze a large amount of data on Ebay and predict which accounts engage in fraud (or are more likely to engage in a future fraudulent transaction).

If anyone has today’s paper, the article in on page B3.
Always took candy from strangers
Didn't wanna get me no trade
Never want to be like papa
Working for the boss every night and day
--"Happy", by the Rolling Stones (1972)

Comments

  • dbldie55dbldie55 Posts: 7,741 ✭✭✭✭✭
    Sounds pretty clear to me.
    Collector and Researcher of Liberty Head Nickels. ANA LM-6053
  • BearBear Posts: 18,953 ✭✭✭
    "TRUST NO ONE.........SUSPECT, EVERYONE"
    There once was a place called
    Camelotimage
  • BigDaddyzBigDaddyz Posts: 1,306 ✭✭✭
    That's exactly what I have been complaining to ebay about when I send in fraud alerts. With the information they have at hand, they should be able to spot a huge amount of fraud without it going so far that they get recognized and reported by other users.


    It should be very simple for them to do with programs what we do with simple observation.

    Great BST experiences: abitofthisabitofthat, silvercoinsdude, gerard, coinfame, mikescoins, wondercoin
  • From the article:

    "We ran the algorithm over a large set of data from eBay, and we were able to locate some obvious cases of fraud that hadn't been spotted before."

    I have seen forum members here team up and accomplish the same thing during a Sunday halftime. The fact remains that Ebay should be at the forefront of this work, not Carnegie Mellon grad students or coin collectors.

    Very interesting link-- thanks!
  • mr1931Smr1931S Posts: 6,385 ✭✭✭✭✭
    tried to find article online and was unsuccessful...math nerds unite!

    Whoever is careless with the truth in small matters cannot be trusted with important matters.

  • flaminioflaminio Posts: 5,664 ✭✭✭
    Couldn't find the article online, but here's a link to the original paper. Sounds very complicated...
  • MillertimeMillertime Posts: 2,048 ✭✭
    Sounds like a NUMB3RS episode.

    Millertime
  • PetescornerPetescorner Posts: 1,220 ✭✭
    Great! Now if anyone at eBay only cared about doing anything about it...
  • mr1931Smr1931S Posts: 6,385 ✭✭✭✭✭
    Indeed, "deep hole" data mines will reveal their "nuggets of truth" when subjected to sophisticated mathematical analysis...thanks, flaminio

    Whoever is careless with the truth in small matters cannot be trusted with important matters.

  • LanLordLanLord Posts: 11,723 ✭✭✭✭✭
    Two things come to mind:

    1 - Ebay needs to get control of their world
    B - It shouldn't be up to people that are losing money to prove they've been wronged, Ebay should have be held to the same controls that CEOs and CFOs are with the SOX requirements
    4 - It's just sad that some students did this and Ebay couldn't
  • ttt
  • LongacreLongacre Posts: 16,717 ✭✭✭
    I tried to read the paper that Flamino linked. Man, I better stick to tax law. That paper was Greek to me and I had to stop reading.
    Always took candy from strangers
    Didn't wanna get me no trade
    Never want to be like papa
    Working for the boss every night and day
    --"Happy", by the Rolling Stones (1972)
  • ziggy29ziggy29 Posts: 18,668 ✭✭✭


    << <i>"We ran the algorithm over a large set of data from eBay, and we were able to locate some obvious cases of fraud that hadn't been spotted before." >>

    If Category = "Coins" and Seller_Location = "China" then Fraud = "Yes" image
  • sonofagunksonofagunk Posts: 1,349 ✭✭
    This is nothing new. I use to do it for a job. We use similar algorthms to make sure that our traders are not doing anything illegal. There are a TON of simple tests that you could do and catch ebay people (I do it all of the time and report them, but 75% of the time, nothing happens). If I had acccess to IP addresses of where bids were placed, I could catch a ton more.

    They just do not want to catch people
  • DentuckDentuck Posts: 3,820 ✭✭✭
    There are three kinds of people on eBay: those who can count, and those who can't.

    Longacre, I owe you an email on an unrelated topic. Could you PM me your address?
  • ziggy29ziggy29 Posts: 18,668 ✭✭✭


    << <i>This is nothing new. I use to do it for a job. We use similar algorthms to make sure that our traders are not doing anything illegal. There are a TON of simple tests that you could do and catch ebay people (I do it all of the time and report them, but 75% of the time, nothing happens). If I had acccess to IP addresses of where bids were placed, I could catch a ton more. >>

    This reminds me of some of the discussions we had on heuristics when I was taking some CS graduate courses. This would have been an interesting case study to talk about in the lectures.
  • itsnotjustmeitsnotjustme Posts: 8,779 ✭✭✭
    With a group size in the millions, and possible fraud networks of 5-10-15-20 accounts, I suspect it is hard to specify a group that doesn't deal with another group, as most e-bay accounts only deal with a very small percentage of the exsting e-bay accounts.

    Regarding 3 types of people on e-bay...

    There are 10 types of nerds in the world. Those that know binary and those that don't.
    Give Blood (Red Bags) & Platelets (Yellow Bags)!

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