New research from Dr. Tara Marshall at Brunel University has found that Facebook surveillance of ex-romantic partners may disrupt post-breakup recovery and personal growth.
That’s bad news, because earlier this year Veronika Lukacs found that almost 90% of people keep tabs on their exes using Facebook.
In the Brunel study, bad breakups were linked to a greater likelihood of Facebook stalking. That, in turn, contributed to current distress, negative feelings, desire and longing for the ex.
Remaining Facebook friends but not “offline friends” after a breakup was associated with less personal growth and poorer post-breakup functioning, given Facebook could be a source of emotionally damaging news (such as an ex’s involvement in a new relationship).
But remaining both online and offline friends led to lower levels of negative feelings, sexual desire and longing for an ex-partner, perhaps because exposure to the ex’s banal Facebook posts destroyed any remaining attraction.
Is stalking endemic to networked publics?
Facebook stalking is so common that when the Break-up Notifier service opened in 2011, to provide notifications when a contact’s relationship status changed, 3.6m users signed up in one week, Facebook slowed to a crawl and the service was banned.
We should not be suprised that stalking is so integral to Facebook. University of California researcher Danah Boyd argued in 2007 that networked publics have four properties:
- Persistence: digital objects are infinitely transferable and storable
- Searchability: digital objects are easily found
- Replicability: digital objects are infinitely and perfectly reproducible
- Invisible audiences: digital objects are seen by an unknowably large audience
The last of these, invisible audiences, is crucial to stalking. It also seems to be a necessary evil for Social Network Service (SNS) popularity. For many years Japanese SNS Mixi showed the “footprints” of those who had viewed a user’s profile.
While this led to initial growth, it was turned off in 2011 because of social problems concerning being seen and reciprocality.
Indirectly, both Marshall’s and Kuvacs’ research points to new ways of thinking about personal insight.
Facebook collects information about “people and the connections they have to everything they care about”. The data is imperfect, but as Forbes describes, this “social graph” is as exploitable a resource as crude oil.
Until recently, the exploitability of this data was rather asymmetrical. Specifically, Facebook and marketers could dig into it but users were more or less limited to browsing it.
Now, however, a growing number of services are allowing individuals to dig into their own Facebook data. Jeremy Keeshin’s Facebook Friends Rankings bookmarklet reveals how much you are viewing the pages of contacts, and perhaps insight into whether your habits are helpful or harmful.
The Facebook search bar autocompletes search queries. Keeshin’s bookmarklet reveals the numbers used to the order of autocomplete options. The more negative the number, the more Facebook thinks you are looking for that individual.
The general consensus of six undergraduates I work with, who used the bookmarklet last night, was that the ranking was fairly accurate but had some discrepancies.
Firstly, the numerical difference between “first ranked” and others ranged from -1.7 to -8, but the difference between second through tenth ranked was much more gradual, usually varying by about 0.2.
Facebook, it seems, weights first place very highly but other places not so much.
Secondly, for reasons unknown there was usually at least one person on the list who the students’ claimed was not a regular interactant. This may have been because of stated relationships (i.e. family relationships recorded and acknowledged on the site).
In three instances boyfriends/girlfriends appeared first in the list but in two other instances family members or relatives showed up in the top ten, despite low levels of interactivity.
The ranking reflects changes in activites very rapidly, but only public activities (likes, comments, and wall posts). People with whom the students had been intensively private messaging recently did not show up near the top of the list.
Wolfram Alpha and Gabi: details, details, details
While Keeshin’s bookmarklet is a single-purpose measure, many more detailed tools are also available.
Wolfram Alpha’s Personal Analytics for Facebook allows you to see the demographics of your contacts – names, relationships, places, jobs, purchases, likes.
It also provides you with details on how you use Facebook and all associated apps. So you can find out when and how often you post, from what app, when you post photographs and who and where you tag, the average length of your status updates, and much, much more.
If you own an iPhone, Gabi represents a new way to think about Facebook. Gabi provides structured ways of asking questions about you and your friends on Facebook.
Such as: how many of your local contacts are single versus in a relationship, and which of your photographs is the most liked or commented on.
These services do not provide fully symmetrical access to the full social graph, as some developers advocate given that it is, indeed, our data.
But while we work for that, along with fighting to protect the privacy of that data, it is certainly valuable to have more objective personal insight into one’s social media presence and that of one’s contacts.