The locomotion behavior of Caenorhabditis elegans has been studied extensively to understand the respective roles of neural control and biomechanics as well as the interaction between them. In the present study, we suggest a new approach to characterize the temporal patterns in the swimming behavior of the organism. The approach is based on the branching length similarity (BLS) entropy defined on a simple branching network consisting of a single node and branches. The organism’s swimming activity is recorded using a charge-coupled device (CCD) camera for 3 h at a rate of 4 frames per second. In each frame, we place 13 points as nodes, those points being distributed at equal intervals along the organism’s length. Thus, the organism is represented by 13 nodes and 12 edges between nodes. By using the nodes and edges, we construct two simple networks. One is formed by connecting the center point to all other points, and the other is generated from the angles between edges. The BLS entropy values are calculated as S _L for the former network and S _θ for the latter. We investigate the distributions of the S _L and the S _θ values in the phase space of S _L — S _θ and compare those with the values obtained from a simulated C. elegans generated by using randomly-moving chained particles along a certain angle. The comparison revealed distinctive features of the ment patterns of C. elegans during swimming activity. In addition, we briefly discuss the application of our method to bio-monitoring systems to capture behavioral changes of test organisms before and after chemical treatment at low concentrations.