Title: Testing for Balance in Social Networks,
Abstract: Friendship and antipathy exist in concert with one another in real social
networks. Despite the role they play in social interactions, antagonistic ties
are poorly understood and infrequently measured. One important theory of
negative ties that has received relatively little empirical evaluation is
balance theory, the codification of the adage `the enemy of my enemy is my
friend' and similar sayings. Unbalanced triangles are those with an odd number
of negative ties, and the theory posits that such triangles are rare. To test
for balance, previous works have utilized a permutation test on the edge signs.
The flaw in this method, however, is that it assumes that negative and positive
edges are interchangeable. In reality, they could not be more different. Here,
we propose a novel test of balance that accounts for this discrepancy and show
that our test is more accurate at detecting balance. Along the way, we prove
asymptotic normality of the test statistic under our null model, which is of
independent interest. Our case study is a novel dataset of signed networks we
collected from 32 isolated, rural villages in Honduras. Contrary to previous
results, we find that there is only marginal evidence for balance in social tie
formation in this setting.