Category Archives: Online Privacy

An Empirical Look at “Creeping” on Social Networks

Disclaimer: no personally identifiable data was used for this research. We had anonymous clickstream data. Also, this is not a scathing expose. Let’s have a sense of humor.

Watch this video:

(courtesy of my college a Capella group)

Tawanda Sibanda and I set out to understand how non-friends interact on a major social network. Our hypothesis was simple: “creeping”

What is “Creeping”? From Urban Dictionary: Following what is going on in someone’s life by watching their status messages on Instant Messengers such as MSN, and their updates to their social networking profiles on websites like Facebook or MySpace.

We were hoping our hypothesis was wrong. False. In short, the vast majority of non-friend interactions are anonymous viewing of photos and profiles. The culprits? Men aged 23-50 viewing women aged 18-30.

How do people interact when they are not friends?

Non-friends use Social Networks for “creeping”
Out of our dataset of 7,152 interactions, 2,219 (31%) are between users who are not friends. Of those, 2,169 (98%) are Info Views, i.e., actions that allow the viewer to collect information about another user without their knowledge, such as viewing photos or profiles. Those Info Views include 1,436 photo views (65% of non-friend interactions), 632 profile views (28%) and 101 views of the target’s social network (5%). In short, there is a lot of passive “creeping” behavior.

Who are the Creepers?

By gender: 2:1 odds it’s a male
Out of 2,186 non-friend interactions where gender is known, men initiated 1,463, or 67%. In short, in our data set, men are 2X more likely to ping strangers than women.Interestingly, overt gestures like messaging or poking are 6X more likely to be initiated by men than women – men initiated 36 such gestures, vs. only 6 for women. Obviously there could sampling error with such small numbers.

By age: Men aged between 31-50 are most likely to engage in “creeping” (specifically of women age 30 years or younger)
“Creeper” behavior here is defined as actions that allow a user to gather information about another user (who is NOT a friend), usually without the target’s explicit knowledge. This includes viewing the target’s friend list, photos or profile, and searching for the target’s profile. The data shows that men aged 23-30 contribute the most “creeping” interactions (32%).

We also computed the percentage of interactions from each age group that involved “creeping”.

Essentially men aged 31-50 are more likely to “creep” than men of other ages (48% of interactions for that age group vs. 40% for the next highest age group, men aged 23-30). In contrast, and perhaps surprisingly, women over 50 are most likely to engage in such behavior (and even more likely than men in the same age group).

To better understand the most active creepers (men aged 31-50 and women over 50), we looked at the gender of their targets.

So men aged 31-50 are predominantly viewing women they do not know, whereas women over 50 are viewing both men and women in relatively equal proportions. The behavior of the women over 50 seems benign. Perhaps they are truly looking to meet new friends, or searching for old friends.

We drilled further into the characteristics of the women being viewed by men aged 31-50. The answer: they look at women aged 23-30. Slightly creepier finding: 30% of their interactions are with women 22 years old and younger!

Does any of this behavior lead to new friendships?
Both genders rarely add people they are “creeping” to their networks.
193 of 3,960 male interactions (4.87%) correspond to adding of friends vs. 116 out of 3,103 female interactions (3.7%). Men are slightly more likely to engage in adding people to their network than women, but the differences are small and, in fact, women have a higher average number of friends (301) vs. men (256).

Interestingly, when you look at the composition of people being added by men vs. women the difference is startling. 79.8% of the time men are adding women to their friends network. In contrast, women only add men to their friends network 40.5% of the time.

Some Good News: “Creeping” behavior is by a small subset of men
We were a little disturbed by our findings, so we started looking for a silver lining. One hypothesis was that a power law / 80:20 rule might be behind the “creeping” clicks. So we checked. It turns out about 39% of the men in the dataset account for 100% of male interactions with non-friends, and 20% account for 87% of the behavior.

So what does it all mean?

  1. Not much—this sounds like real life
  2. Women should probably spend a little time going through their privacy settings (particularly for pictures)
  3. A major social network is not an environment where people go to genuinely look for new friends / find dates. Start-up dating sites rejoice!

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