Direct blockmodeling of valued and binary networks: a dichotomization-free approach

TL;DR

This paper introduces a novel direct blockmodeling method for valued and binary networks that avoids data dichotomization, using an adaptive weighted correlation criterion, enhancing interpretability and applicability.

Contribution

It presents a new approach that bypasses the need for dichotomizing valued networks, allowing direct analysis with conventional ideal blocks without data transformation.

Findings

Effective application to both binary and valued networks

Produces feasible and intuitive solutions in diverse examples

Offers a practical alternative to traditional dichotomization methods

Abstract

A long-standing open problem with direct blockmodeling is that it is explicitly intended for binary, not valued, networks. The underlying dilemma is how empirical valued blocks can be compared with ideal binary blocks, an intrinsic problem in the direct approach where partitions are solely determined through such comparisons. Addressing this dilemma, valued networks have either been dichotomized into binary versions, or novel types of ideal valued blocks have been introduced. Both these workarounds are problematic in terms of interpretability, unwanted data reduction, and the often arbitrary setting of model parameters. This paper proposes a direct blockmodeling approach that effectively bypasses the dilemma with blockmodeling of valued networks. By introducing an adaptive weighted correlation-based criteria function, the proposed approach is directly applicable to both binary and valued networks, without any form of dichotomization or transformation of the valued (or binary) data at any point in the analysis, while still using the conventional set of ideal binary blocks from structural, regular and generalized blockmodeling. The approach is demonstrated by structural, regular and generalized blockmodeling applications of six classical binary and valued networks. Finding feasible and intuitive optimal solutions in both the binary and valued examples, the approach is proposed not only as a practical, dichotomization-free heuristic for blockmodeling of valued networks but also, through its additional benefits, as an alternative to the conventional direct approach to blockmodeling.