A deviational approach to blockmodeling of valued networks

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

This article proposes a novel approach to blockmodeling of valued (one-mode) networks where the identification of (binary) block patterns in the valued relations differ from existing approaches. Rather than looking at the absolute values of relations, or examining valued ties on a per-actor basis (cf. Nordlund, 2007), the approach identifies prominent (binary) ties on the basis of deviations from expected values. By comparing the distribution of each actor's valued relations to its alters with the macro-level distributions of total in- and outdegrees, prominent (1) and non-prominent (0) ties are determined both on a per-actor-to-actor and a per-actor-from-actor basis. This allows for a direct interpretation of the underlying functional anatomy of a non-dichotomized valued network using the standard set of ideal blocks as found in generalized blockmodeling of binary networks. In addition to its applicability for direct blockmodeling, the article also suggests a novel indirect measure of deviational structural equivalence on the basis of such deviations from expected values. Exemplified with the note-sharing data in Žiberna (2007a), citations among social work journals (Baker, 1992), and total commodity trade among EU/EFTA countries as of 2010, both the direct and indirect approach produce results that are more sensitive to variations at the dyadic level than existing approaches. This is particularly evident in the case of the EU/EFTA trade network, where the indirect approach yields partitions and blockmodels in support of theories of regional trade, despite the significantly skewed valued degree distribution of the dataset.

Detaljer

Författare
Externa organisationer
  • Central European University
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Tvärvetenskapliga studier
  • Sannolikhetsteori och statistik

Nyckelord

Originalspråkengelska
Sidor (från-till)160-178
Antal sidor19
TidskriftSocial Networks
Volym44
StatusPublished - 2016 jan 1
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa