Title
On the bias of BFS (Breadth First Search)
Abstract
Breadth First Search (BFS) and other graph traversal techniques are widely used for measuring large unknown graphs, such as online social networks. It has been empirically observed that incomplete BFS is biased toward high degree nodes. In contrast to more studied sampling techniques, such as random walks, the bias of BFS has not been characterized to date. In this paper, we quantify the degree bias of BFS sampling. In particular, we calculate the node degree distribution expected to be observed by BFS as a function of the fraction of covered nodes, in a random graph RG(pk) with a given (and arbitrary) degree distribution pk. Furthermore, we also show that, for RG(pk), all commonly used graph traversal techniques (BFS, DFS, Forest Fire, and Snowball Sampling) lead to the same bias, and we show how to correct for this bias. To give a broader perspective, we compare this class of exploration techniques to random walks that are well-studied and easier to analyze. Next, we study by simulation the effect of graph properties not captured directly by our model. We find that the bias gets amplified in graphs with strong positive assortativity. Finally, we demonstrate the above results by sampling the Facebook social network, and we provide some practical guidelines for graph sampling in practice.
Year
DOI
Venue
2010
10.1109/ITC.2010.5608727
International Teletraffic Congress
Keywords
Field
DocType
graph theory,signal sampling,social networking (online),tree searching,BFS sampling,Facebook social network,breadth first search,forest fire,graph traversal technique,node degree distribution,online social networks,random graph,random walks,snowball sampling,BFS,Breadth First Search,Facebook,OSN,Online Social Networks,bias,graph sampling
Graph theory,Random graph,Graph traversal,Graph property,Computer science,Random walk,Algorithm,Real-time computing,Theoretical computer science,Degree distribution,Sampling (statistics),Snowball sampling
Conference
ISBN
Citations 
PageRank 
978-1-4244-8835-3
55
2.35
References 
Authors
15
3
Name
Order
Citations
PageRank
Maciej Kurant1552.35
Athina Markopoulou22084121.94
Patrick Thiran32712217.24