HOUSTON — More and more friendships these days are forming online. The internet has made it easier than ever to find like-minded people to connect with, regardless of distance. But, what is the best way to find a digital companion? A study by researchers at Rice University finds that forming online friendships comes down to the number of groups and organizations one joins. Surprisingly, the actual topics and subjects these groups are focused on just doesn’t matter as much as simply joining as many as possible.
“If a person is looking for friends, they should basically be active in as many communities as possible,” says co-author Anshumali Shrivastava, assistant professor of computer science at Rice University, in a statement. “And if they want to become friends with a specific person, they should try to be a part of all the groups that person is a part of.”
The researchers analyzed six different social networks, encompassing millions of users. Their findings were surprising, mainly because of how drastically the results differed from previous research on friendship formation and the role communities play in that process.
“There’s an old saying that ‘birds of a feather flock together,’” Shrivastava continues. “And that idea — that people who are more similar are more likely to become friends — is embodied in a principal called homophily, which is a widely studied concept in friendship formation.”
In the past, research on this subject has accounted for homophily by assigning online groups an “affinity” score based on how alike the group members are. The higher the affinity score is, the greater chance group members will become friends.
“A community, for our purposes, is any affiliated group of people within the network,” Shrivastava explains. “Communities can be very large, like everyone who identifies with a particular country or state, and they can be very small, like a handful of old friends who meet once a year.”
However, this study’s authors discovered a major problem regarding the affinity score approach: the overlap between communities and smaller sub-committees. For example:
“Let’s say Adam, Bob and Charlie are members of the same four communities, but in addition, Adam is a member of 16 other communities,” Shrivastava says. “The existing affiliation model says the likelihood of Adam and Charlie being friends only depends on the affinity measures of the four communities they have in common. It doesn’t matter that each of them are friends with Bob or that Adam’s being pulled in 16 other directions.”
To correct for this, Shrivastava and his team borrowed a concept still in use today by internet search engines that was developed in the 1990s. This approach, called the Jaccard overlap, accounts for similarities among web pages across the internet.
“We used this to measure overlap between communities and then checked to see if there was a relationship between overlap and friendship probability, or friendship affiliation, on six well-studied social networks,” Shrivastava explains. “We found that on all six, the relationship more or less looked like a straight line.”
So, after finishing their analysis, the research team came to a relatively simple conclusion regarding how friendships form.
“It seems that the most effective way is to encourage people to form more sub-communities,” Shrivastava concludes. “The more sub-communities you have, the more they overlap, and the more likely it is that individual members will have more close friendships throughout the organization. People have long thought that this would be one factor, but what we’ve shown is this is probably the only one you have to pay attention to.”
The peer-reviewed study was presented at the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining in Barcelona, Spain.