Understanding Cross-site Linking in Online Social Networks Yang Chen 1, Chenfan Zhuang 2, Qiang Cao 1, Pan Hui 3 1 Duke University 2 Tsinghua University 3 Hong Kong University of Science and Technology

Motivation A number of OSN sites with different functionality It is quite common for an individual user to have multiple accounts on different OSN sites. – How to efficiently manage accounts on different OSNs? 2 Interact with friendsShare breaking news Job search Location-centric social interactions

The Cross-site Linking Function The cross-site linking function allows a user to link her account on one OSN site to her accounts on other OSN sites 3

Cross-site Linking: Advantages Make cross-site content posting easy – Help Foursquare users automatically post tips to Facebook and Twitter Avoid repeated efforts in social connection establishment – Import the contact list from other OSNs Provide more information of a user – Visit the linked profiles on other OSNs 4

Why Foursquare? A representative LBSN service, one of the most popular OSN sites – Foursquare app: customized discovery and recommendation engine – Swarm app: real-time location sharing with friends Supports the cross-site linking function – A user can link his profile to Facebook/Twitter Every Foursquare user has a public profile page ( 5

Data Collection Goal: analyze the entire Foursquare user base – To avoid the disadvantages of biased sampling Challenge: IP-based rate limiting – Crowd crawling:100 crawlers around the United States, each crawls one chunk of IDs Data – Collected between Jul. 22 th, 2014 and Jul. 29 th, 2014 – Public profiles of million Foursquare users Almost all (if not all) Foursquare users 6 IDGenderTipsCheckins FriendsFacebookTwitter… 123male eric_c…

Linking Options About 60% Foursquare users have enabled the cross-site linking function 56.15% users have added their Facebook accounts 15.78% users have added their Twitter accounts The cross-site linking function is widely used among Foursquare users 7 Percentage Distribution of Linking Options

Group-based Analysis: Gender Very little difference between male users and female users in terms of the distribution of linking options Gender options:  51.52% Male  42.92% Female  5.56% Rather not say 8

Group-based Analysis: Country Top four countries:  USA (27.61%)  Turkey (9.49%)  Indonesia (8.17%)  Brazil (7.04%) 9 Percentage of users that have enabled cross-site linking

Group-based Analysis: Activity Two factors: social connections and location- centric activities (leaving tips, check-ins) 10

Group-based Analysis: Activity (cont.)  Most zombies/loners have not enabled cross-site linking, as they are socially isolated.  Watchers v.s. Orindary users  Watchers are less motivated to link to Twitter, as they don’t publish  73% watchers and 71% ordinary users have linked to Facebook (users from both groups are connected with other Foursquare users) 11

Behavioral Difference among Users with Different Linking Options Users who have enabled the cross-site linking function are more “active” – Cross-site linking will deliver published contents to more prospective audience “TW only” > “FB only” – Publicly viewable tweets can be quickly spread through the Twitter network – FB user status is only visible to friends by default (fewer possible audiences) 12

User Privacy Concerns & Cross-site Linking In Foursquare, users can customize their profiles according to privacy concerns (a user can choose whether to enable an optional field) 13 Alice’s Foursquare Profile Alice’s Facebook Profile Alice’s Twitter Profile More information about Alice!! Intuitively, cross-site linking might cause concerns for users who care a lot about their privacy.

User Privacy Concerns & Cross-site Linking (cont.)  Whether or not uploading personalized profile photo is an indicator for the adoption of cross-site linking  Enabling any of the five optional field indicates a higher probability of using the cross-site linking function 14

Cross-site Information Consistency Cross-site Information Consistency (“Foursquare-Facebook”) Users have a high probability to manifest cross-site information consistency 15 A user might choose to expose the same or different personal information on different sites

Cross-site Information Aggregation Aggregate the information of the same user from different OSN sites (learn more about a user) Applications: friend suggestion, point-of-interest recommendation, personalized advertising, … Example: gender-based analysis of Twitter 16

Gender-based Analysis of Twitter 17 Female users publish more tweets Male users are involved in more lists

Gender-based Analysis of Twitter (cont.) URLDescriptionLocation Male32.07%62.82%56.87% Female25.02%64.73%57.35% The Use of Optional Fields (%)  Male users have a higher probability to add a URL  Both male and female users have a nearly 63% probability of adding a description, and a nearly 57% probability to add the location information. 18

Related Work Cross-OSN linking papers – Ottoni et al. [ICWSM 2014] : Pinterest-Twitter linking – Chen et al. [WOSN 2012] : Google+ – Both of them used biased sampling methods, while our study is based on the entire Foursquare user population Wang et al. [IEEE Internet Computing, 2014] compared a series of user activities across Foursquare, Facebook, and Twitter – We focus on the cross-site linking function Goga et al. [WWW 2013], Liu et al. [SIGMOD 2014] investigated how to identify accounts on different OSNs that all are owned by the same user – Useful for the OSN sites which do not support the cross-site linking function 19

Conclusion About 60% of Foursquare users have enabled the cross- site linking function, and these users are more active than other users Adding contents to an optional field indicates a higher probability of activating the cross-site linking function If a Foursquare user has linked his account to Facebook, he will have a high chance to provide consistent information to both Foursquare and Facebook The use of cross-site information aggregation helps us investigate the gender difference in using Twitter 20

Future Work Investigate cross-site links among more mainstream OSN sites – Discover general patterns to characterize cross-OSN links A volunteer-based study – Access the non-publicly viewable data (e.g.: check-in history)  a deeper investigation into cross-site information aggregation Build practical services/applications based on cross-site links – Malicious account detection 21