The paper presents several approaches to generalized blockmodeling of valued networks,
where values of the ties are assumed to be measured on at least interval scale. The first …

Discerning the essential structure of social networks is a major task. Yet, social network data
usually contain different types of errors, including missing data that can wreak havoc during …

The article presents several approaches to the blockmodeling of multilevel network data.
Multilevel network data consist of networks that are measured on at least two levels (eg …

The paper presents a k-means-based algorithm for blockmodeling linked networks where
linked networks are defined as a collection of one-mode and two-mode networks in which …

Social network data usually contain different types of errors. One of them is missing data due
to actor non-response. This can seriously jeopardize the results of analyses if not …

The aim of this article is to compare methods for detecting and/or measuring regular
equivalence in valued networks. The methods compared can be divided into direct and …

Social network data are prone to errors regardless their source. This paper focuses on
missing data due to actor non-response in valued networks. If actors refuse to provide …

This paper addresses the question of whether one can generate networks with a given
global structure (defined by selected blockmodels, ie, cohesive, core-periphery, hierarchical …

The aim of the paper is to compare and evaluate different approaches to detecting regular
equivalence classes of valued networks. The evaluated approaches include different …

The paper starts with an observation that the blockmodeling of relatively sparse binary
networks (where we also expect sparse non-null blocks) is problematic. The use of regular …