GAYATRI SWAMYNATHAN, CHRISTO WILSON, BRYCE BOE, KEVIN ALMEROTH AND BEN Y. ZHAO UC SANTA BARBARA Do...
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![Page 1: GAYATRI SWAMYNATHAN, CHRISTO WILSON, BRYCE BOE, KEVIN ALMEROTH AND BEN Y. ZHAO UC SANTA BARBARA Do Social Networks Improve e-Commerce? A Study on Social.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649da75503460f94a93c7b/html5/thumbnails/1.jpg)
GAYATRI SWAMYNATHAN, CHRISTO WILSON, BRYCE BOE,
KEVIN ALMEROTH AND BEN Y. ZHAO
UC SANTA BARBARA
Do Social Networks Improvee-Commerce?
A Study on Social Marketplaces
1
Current Lab @ UCSB
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Leveraging Online Social Networks
Online communities in the Web 2.0 era Facebook – ~90 million users Myspace – ~110 million users Orkut – ~60 million users
Question: can friends-of-friends networks be leveraged outside social networks?
Examples Internet Search Spam Filtering Online marketplaces…?
Enhanced reputation systems Sybil Protection
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Current Lab @ UCSB
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What’s Wrong With Online Marketplaces?
Man arrested in huge eBay fraud – MSNBC 2003 http://www.msnbc.msn.com/id/3078461/
eBay urged to tackle fraud better – BBC 2006 http://news.bbc.co.uk/1/hi/uk/4749806.stm
Fraud abroad remains 'uphill battle' for eBay – CNET 2008 http://news.cnet.com/Fraud-abroad-remains-uphill-battle-for-eBay/2100-7348_3-6233893.html
Tacoma woman’s house emptied after Craigslist hoax – The Seattle Times 2007 http://seattletimes.nwsource.com/html/localnews/2003652872_webhouse05m.html
Escrow fraud ruining Craigslist? – ZDNet 2008 http://blogs.zdnet.com/threatchaos/?p=519
Bottom Line – Online markets plagued by fraud Feedback-based reputation systems ineffective
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Current Lab @ UCSB
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Social Marketplaces and Overstock.com
Online marketplaces that incorporate social networks
Hypothesis: transactions with social friends will have higher satisfaction. Are people actually using this capability?
Measure transaction volume vs. path length Do social networks actually improve satisfaction?
Measure satisfaction vs. path lengthOverstock Auctions
Started in 2004 Similar to eBay
Buyers leave feedback after each transaction Incorporates social components
Comment and leave ratings on friend’s profiles Message boards “How am I connected?” button
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Current Lab @ UCSB
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Methodology
Analyze overall network structure of Overstock Connectivity of all 431,705 users provided by Overstock Two networks:
“Personal” – connecting friends “Business” – automatically connects users who transact
Correlating structure with transactions Two questions:
1. What correlates transactions: Business or Social connectivity?2. What is the impact of path length on transaction satisfaction?
Crawled transaction history of ~10,000 users ~18,000 total transactions
Overall feedback for each user Feedback for individual transactions
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Current Lab @ UCSB
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Do Social Networks Improve e-Commerce?
Outline
1. Connectivity graph analysis2. What correlates transactions?
Social vs. Business path lengths
3. Impact of path lengths on transaction satisfaction
6
Current Lab @ UCSB
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Connectivity Graph Analysis
Business Network Social Network
Total Nodes 398,989 85,200
Total Links 1,926,553 1,895,100
Avg. Node Degree 4.82 22.24
Socialnetwork
32,716 nodes(8%)
Business network346,505 nodes
(80%)
52,484nodes(12%)
82% of users have < 1% overlap
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Current Lab @ UCSB
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Connectivity is Heterogeneous 8
Current Lab @ UCSB
50% of users have less than 10
friends and/or transaction partners.
Business network has lesser degree
overall.
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Do Social Networks Improve e-Commerce?
Outline
1. Connectivity graph analysis2. What correlates transactions?
Social vs. Business path lengths
3. Impact of path lengths on transaction satisfaction
9
Current Lab @ UCSB
![Page 10: GAYATRI SWAMYNATHAN, CHRISTO WILSON, BRYCE BOE, KEVIN ALMEROTH AND BEN Y. ZHAO UC SANTA BARBARA Do Social Networks Improve e-Commerce? A Study on Social.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649da75503460f94a93c7b/html5/thumbnails/10.jpg)
Transaction Volume vs. Path Length
Question: is there a correlation between social distance and buying decisions?
Compare transaction volume to network path length For each transaction, compute hops between buyer
and seller Business network – Connectivity is almost guaranteed
For partners with multiple transactions, path length = 1 Otherwise, remove 1-hop edge and calculate distance
Social network – Connectivity is NOT guaranteed! Not all users are present in the Social Network
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Current Lab @ UCSB
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Observations on Transaction Volume
Volume vs. path lengths for 17,376 transactions
11
Current Lab @ UCSB
20% of transactions
occur between repeat buyers.
At most, 20% of transactions can be accounted for on the
Social network.
Most transactions occur between close
Business network neighbors.Almost no
transactions occur between
friends.
Social network is smaller; is underutilized for making transaction
decisions.
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Do Social Networks Improve e-Commerce?
Outline
1. Connectivity graph analysis2. What correlates transactions?
Social vs. Business path lengths
3. Impact of path lengths on transaction satisfaction
12
Current Lab @ UCSB
![Page 13: GAYATRI SWAMYNATHAN, CHRISTO WILSON, BRYCE BOE, KEVIN ALMEROTH AND BEN Y. ZHAO UC SANTA BARBARA Do Social Networks Improve e-Commerce? A Study on Social.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649da75503460f94a93c7b/html5/thumbnails/13.jpg)
Question: does social distance influence transaction satisfaction?o Transaction success percentage vs. path
lengths for 17,376 transactionsExample transactions:
Satisfied = [+1, +2]
Impact of Path Lengths on Satisfaction
Seller Buyer Transaction ID Date Rating (-2 to +2)
A B 123 2/19/2005 +2
A B 234 12/17/2004 +2
A C 345 12/15/2004 0
B D 456 12/2/2004 -1
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Current Lab @ UCSB
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Observations on Personal Network14
Current Lab @ UCSB
Friendship is a choice!
Bad sellers/fraudsters are naturally excluded from Social network. Chain
of satisfaction holds at long social distances.
Near 100% satisfaction rate between friends.
90% average satisfaction for distances <= 5.
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Observations on Business Network15
Current Lab @ UCSB
Near 100% satisfaction rate
for repeat buyers.
Close to 0% satisfaction at larger
distances!
Business connections are automatic!
Business networks includes all transaction partners ever. This includes partners who you were unsatisfied with!
Chain of satisfaction does not hold at long distances.
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Conclusions
Social links underutilized for making transaction decisions Most users do not participate in the social
marketplace 8% of users are purely social 80% users not present in the Social network
Those who do separate business from friends Very few transactions between friends Little overlap of between Social and Business networks
Room for growth!
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Current Lab @ UCSB
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Conclusions, cont.
Current Lab @ UCSB
17
Social networks increase user satisfaction Success rates at long distances are higher on
Social network Social linkage is a choice, cheaters are quickly
excluded Fraudsters necessarily must use many fake accounts These accounts rarely become well connected in Social
network
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Conclusions, cont.
Current Lab @ UCSB
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Social networks are an excellent way to avoid bad sellers User education is needed
Get more people involved socially Encourage businesses to interact socially
Better advertising, more features for existing services Ebay: Favorite sellers and Neighborhoods Amazon Profiles Facebook Marketplace
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Thanks for Listening!
Questions?19
Current Lab @ UCSB