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Understanding cross-site linking in online social networks
Gong Q., Chen Y., Hu J., Cao Q., Hui P., Wang X. ACM Transactions on the Web12 (4):1-29,2018.Type:Article
Date Reviewed: Mar 22 2019

This paper is a data-driven analysis of cross-site linking in online social networks, including Foursquare, Facebook, and Twitter. It describes the user behavior behind cross-site linking and why users do cross-site linking. It is one of the first works to analyze such a large number of social network users (61.39 million Foursquare users).

The authors do a great job of performing a thorough analysis of the demographics, engagement, and user behavior of different groups of users that interact with online social networks (for example, zombies, loners, watchers, and ordinary users). Even though the overall results are not new or surprising, it is good to see this quantified and to verify the expected results. Moreover, the authors do a good job of analyzing cross-site information consistency, that is, how consistent the user profile is among other cross-linked online social networks.

An interesting finding relates to non-early users with a higher probability of enabling cross-site linking. This is probably true because Foursquare did not initially have cross-site linking and only added this capability later. In addition, non-early users are more well versed and familiar with online social networks; they want to enable cross-site linking so that they don’t have to post separately to other online social networks like Facebook and Twitter, thus saving time and resources (that is, having to copy the text and get the image/video, and then paste it in the Facebook app or the Twitter app).

Another finding relates to the profile picture as “an indicator for the adoption of cross-site linking.” The authors do not offer an explanation as to why this is the case. Most likely it is because users want to be more active and more social, and want others to notice them and follow them; therefore, in order to get other people’s attention, they post a profile picture.

The authors also conduct a survey to investigate why users enable cross-site linking, which cannot be obtained from a quantitative data analysis of user profiles. It would be nice if the authors could correlate the type of user (zombie, loner, watcher, and ordinary user) with the survey results. For example, if a user does not enable cross-site linking because of privacy concerns, is this evident in the cross-linked user profile as well?

Future work should investigate how to create a holistic user profile that combines all user profile fields from each online social network.

Reviewer:  Alvin Chin Review #: CR146485 (1906-0246)
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Social Networking (H.3.4 ... )
 
 
Collaborative Computing (H.5.3 ... )
 
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