Skip to main content

Social Networks, Algebraic Models for

  • Reference work entry
  • 331 Accesses

Article Outline

Glossary

Definition of the Subject

Introduction

Algebras from Networks

Algebraic Structure

Algebraic Analysis

Algebraic and Network Mappings

Examples

Future Directions

Bibliography

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   1,500.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   1,399.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Abbreviations

Social network :

social network comprises a set of relationships among members of a set \( { N=\{1,2, \dots, n\} } \) of actors. It can be represented by an \( { n \times n } \) binary array X recording the presence or absence of a social relationship, or tie, between each pair (or orderedpair) of members of \( { N=\{1,2,\dots, n\} } \). If there isa relationship from actor k to actor l, we write \( { X(k,l)=1 } \);otherwise, \( { X(k,l)=0 } \). If the relationship is a property ofa pair of actors, the network is nondirected; if it isa property of an ordered pair, the network is termeddirected. The directed network X may also be regarded asa  binary relation R X on the set N with \( (k,l) \in R_X \) if and only if \( { X(k,l) = 1 } \); equivalently, it may beconstrued as a directed graph with node set N andarc set R X , with an arc from node k tonode l if and only if \( { (k,l) \in R_{X} } \).

Affiliation network :

An affiliation network isan \( { n\times g }\) binary array X recording the membership of each of a set N of actors in a prescribed set G of groups , with\( { X(k,l)=1 } \) if actor k is a member of group l, and \( { X(k,l)=0 } \) otherwise.

Multiple network :

multiple network is a collection ofnetworks for each of a set of r relations. We let \( { X_{m}(k,l)=1 } \)if the tie from k to l corresponding to the relation oftype m is present; and \( { X_{m}(k\:,l)=0 } \) if the tie isabsent. Nodes k and l are joined by a  labeled walk withlabel \(Y_{1}\, Y_{2}\, \dots Y_{j}\) if there is a sequenceof nodes \(k=k_{0}, k_{1}, \dots, k_{j}=l\), forwhich \(Y_{h}(k_{h-1}, k_{h})=1\) for \(h=1,2,\dots, j\).

Local network :

The (1-)neighborhood of a subset P of actors in a network is defined to be theset \( P \cup\{l\in N\colon X_{m}(k,l)=1 \) forsome \( { k\in P } \) and some relation m}. The q‑neighborhood of P is then definedrecursively as the 1‑neighborhood of the \( { (q-1) }\)‑neighborhood of P. The q‑localnetwork of the subset P of N is the network restricted toits q‑neighborhood.

Algebra :

A ( partially ordered) algebra isa triple [\( { S,F,\leq } \)], where S is a nonempty set ofelements (usually assumed to be finite), F is a specified set ofoperations, \( { f_{\alpha } } \), each mapping a power \( { S^{n(\alpha)} } \)of S into S, for some non‐negative finite integer\( { n(\alpha) } \), and \( { \leq } \) is a partial order on S. Eachoperation f α is assumed to be isotone in each ofits variables: that is, if \(x_{i} \leq y_{i}\, (x_{i}, y_{i} \in\ S;\,i = 1,2, \dots, n(\alpha))\), then \(f_{\alpha} (x_{1},x_{2}, \dots, x_{n(\alpha)})\leq f_{\alpha}(y_{1},y_{2},\dots, y_{n(\alpha)}) \).A  family of algebras is a collection of algebras each having the same set F ofoperations and satisfying a specified set of postulates. Two algebrasbelonging to the same family are termed similar.

Partial algebra :

partial algebra isa triple [\( { S,F,\leq } \)], where S is a nonempty set of elements(usually assumed to be finite), F is a specified set ofpartial operations, \( { f_{\alpha}} \), each mapping somesubset \( { T^{(\alpha)} } \) of \( { S^{n(\alpha)} } \) into S, for somenon‐negative finite integer \( { n(\alpha) } \), and \( { \leq } \) is a partialorder on S. Each partial operation f α is assumed to beisotone in each of its variables: that is, if \(x_{i} \leq y_{i}\,(x_{i}, y_{i}\in S;\,i = 1,2, \dots,n(\alpha))\), then \(f_\alpha (x_1 ,x_2 , \ldots ,x_{n(\alpha )} ) \le f_\alpha (y_1 ,y_2 , \ldots ,y_{n(\alpha )} )\) provided that both\((x_{1},x_{2}, \dots, x_{n(\alpha)})\:, (y_{1},y_{2}, \dots, y_{n(\alpha)})\in T^{(\alpha)}\).A  family of partial algebras is a collection of algebras each having the same set F of partialoperations defined on the same subsets \( { T^{(\alpha)}} \) of the powersets \( { S^{n(\alpha)} } \).

Semigroup :

(partially ordered) semigroup isan algebra [\( { S,F,\leq } \)] in which F comprises a singlebinary operation f satisfying the associativity condition:

$$f(f(x,y),z)=f(x,f(y,z)) \:.$$
Lattice :

lattice L is an algebra[\( { S,F,\leq } \)] in which F comprises two associative andcommutative binary operations, ∧ and ∨ (termedmeet and join, respectively) satisfying theidentities:

$$ \begin{aligned}& x \wedge x =x \:, \\ & x \vee x =x\end{aligned}$$

and

$$x \wedge (x \vee y)=x \vee (x \wedge y)=x\:.$$

The operations are isotone, so that \( { x \leq y } \) is equivalent tothe pair of conditions:

$$x \wedge y=x \quad \text{and} \quad x \vee y=y \:,$$

and the operations of meet and join may be interpreted as the greatestlower bound and least upper bound, respectively. A lattice  L is distributive if the identity

$$x \wedge (y \vee z)=(x \wedge y) \vee (x \wedge z)$$

holds. A lattice L is modular if, whenever \( { x \leq z } \), then

$$x \vee (y \wedge z)=(x \vee y) \wedge z\:.$$
Role algebra :

role algebra is an algebra[\( { S,F,\leq } \)] in which F comprises a single binarycomposition operation satisfying the condition: \( { s \leq t } \) in Simplies \( { su \leq tu \text{ in }S } \), for any \( { u \in W } \).

Homomorphism :

An (isotone) homomorphism froman algebra \( { A = [S,F,\leq] } \) onto a similar algebra \(B =[T,F,\leq]\) is a mapping \( { \phi\colon S \to T } \) such that,

  1. (i)

    for all \( f_\alpha \in F \) and \( { x_{i}\in S } \),

    $$\phi(f_{\alpha}(x_{1},x_{2}, \dots,x_{n(\alpha)})) \\ =f_{\alpha}(\phi(x_{1})\:,\phi (x_{2}), \dots, \phi(x_{n(\alpha)})) \:; \quad \text{ and}$$
  2. (ii)

    \( { x \leq y \text{ in } S } \) implies \( { \phi (x) \leq \phi (y) \text{ in } T } \).

The algebra B is termed a (homomorphic) imageof A, and we write \( { B=\phi (A) } \). Each homomorphism ϕ from \( { A =[S,F,\leq] } \) onto \( { B=[T,F,\leq] } \) hasa corresponding binary relation  π on S (termed herea π‑relation) in which \( { (x,y) \in \pi} \) ifand only if \( { \phi (y) \leq \phi (x) } \). Theequivalence relation \( { \sigma_{\pi} } \) defined by \( { (x,y) \in \sigma_{\pi} } \) if and only if \( { (x,y) \in \pi } \) and \( { (y,x) \in \pi } \) istermed a congruence relation.

Homomorphism lattice :

The homomorphism lattice L(A)of the algebra \( { A =[S,F,\leq] } \) is the collection of allhomomorphisms of A partially ordered by the relation: \( { \phi_{1}\leq \phi_{2} } \) if, for all \( { x, y \in S,\, \phi_{2}(x) \leq\phi_{2}(y) } \) implies \( { \phi_{1}(x) \leq \phi_{1}(y) } \). Thelattice \( { L_{\pi} (A) } \) of π‑relations on A,dual to L(A), has the partial ordering: \( { \pi_{1} \leq \pi_{2} } \)if \( { (x,y) \in \pi_{1} } \) implies \( { (x,y) \in \pi_{2} } \), for any \( { x, y \in S } \).

Bibliography

  1. BarnesG, Cerrito P, Levi I (1998) A mathematical model for interpersonalrelationships in social networks. Soc Netw 20:179–196

    Google Scholar 

  2. Birkhoff G (1963) Lattice theory, 3rd edn. American Mathematical Society, Providence

    Google Scholar 

  3. Bonacich P (1980) The common structure semigroup, a replacement for the Boorman and White joint reduction. Am J Soc 86:159–166

    Article  Google Scholar 

  4. Bonacich P (1983) Representations for homomorphisms. Soc Netw 5:173–192

    Article  Google Scholar 

  5. Boorman SA, White HC (1976) Social structures from multiple networks II. Role structures. Am J Soc 81:1384–1446

    Article  Google Scholar 

  6. Boyd JP (1969) The algebra of group kinship. J Math Psychol 6:139–167

    Article  MATH  Google Scholar 

  7. Boyd JP (1989) Social semigroups and Green relations. In: Freeman LC, White DR, Romney AK (eds) Research methods in social network analysis. George Mason University Press, Fairfax, pp 215–254

    Google Scholar 

  8. Boyd JP (1990) Social semigroups: A unified theory of scaling and blockmodelling as applied to social networks. George Mason University Press, Fairfax

    Google Scholar 

  9. Boyd JP, Haehl JH, Sailer LD (1989) Kinship systems and inverse semigroups. J Math Soc 2:37–61

    Article  Google Scholar 

  10. Breiger RL (1974) The duality of persons and groups. Soc Forces 53:181–190

    Google Scholar 

  11. Breiger RL, Pattison PE (1986) Cumulated social roles: the duality of persons and their algebras. Soc Netw 8:215–256

    Article  Google Scholar 

  12. Davis A, Gardner B, Gardner M (1941) Deep south. Chicago University Press, Chicago

    Google Scholar 

  13. Doreian P (1981) Polyhedral dynamics and conflict mobilization in social networks. Soc Netw 3:107–116

    Article  MathSciNet  Google Scholar 

  14. Duquenne V (1996) On lattice approximations: syntactic aspects. Soc Netw 18:189–200

    Article  Google Scholar 

  15. Freeman LC (1996) Cliques, Galois lattices, and the structure of human social groups. Soc Netw 18:173–87

    Article  Google Scholar 

  16. Freeman LC, White DR (1993) Using Galois lattices to represent network data. In: Marsden P (ed) Sociological methodology. American Sociological Association, Washington, pp 127–146

    Google Scholar 

  17. Friedell M (1967) Organizations as semilattices. Am Soc Rev 32:46–54

    Article  Google Scholar 

  18. Fuchs L (1963) Partially ordered algebraic systems. Pergamon, Oxford

    MATH  Google Scholar 

  19. Ganter B, Wille R (1989) Conceptual scaling. In: Roberts F (ed) Applications of combinatorics and graph theory in the biological and social sciences. Springer, New York, pp 139–167

    Chapter  Google Scholar 

  20. Ganter B, Wille R (1999) Formal concept analysis: mathematical foundations. Springer, New York

    Book  MATH  Google Scholar 

  21. Grenander U (1993) General pattern theory. Oxford University Press, Oxford

    Google Scholar 

  22. HandcockMS (2003) Statistical models for social networks. In: Breiger RL,Carley KM, Pattison PE (eds) Dynamic social network modeling andanalysis. National Academies Press, Washington

    Google Scholar 

  23. Homans G (1951) The human group. Routledge & Kegan Paul, London

    Google Scholar 

  24. Kim KH (1982) Boolean matrix theory and applications. Dekker, New York

    MATH  Google Scholar 

  25. KimKH, Roush FW (1984) Group relationships and homomorphisms of Booleanmatrix semigroups. J Math Psychol 28:448–452

    Google Scholar 

  26. Lorrain F (1975) Reseaux sociaux et classifications sociales. Hermann, Paris

    MATH  Google Scholar 

  27. Lorrain F, White HC (1971) Structural equivalence of individuals in social networks. J Math Soc 1:49–80

    Article  Google Scholar 

  28. Luce RD (1956) A note on Boolean matrix theory. Proc Am Math Soc 3:382–388

    Article  MathSciNet  Google Scholar 

  29. Mandel M (1983) Local roles and social networks. Am Soc Rev 48:376–386

    Article  Google Scholar 

  30. Martin JL (2002) Some algebraic structures for diffusionin social networks. J Math Soc 26:123–146

    Article  MATH  Google Scholar 

  31. Martin JL (2006) Jointness and duality in algebraic approaches to dichotomous data. Soc Method Res 35:159–192

    Article  Google Scholar 

  32. McConaghy M (1981) The common role structure: improved blockmodelling methods applied to two communities' elites. Soc Method Res 9:267–285

    Article  Google Scholar 

  33. Mische A, Pattison PE (2000) Composing a civic arena:Publics, projects and social settings. Poetics 27:163–194

    Article  Google Scholar 

  34. Pattison PE (1982) The analysis of semigroups of multirelational systems. J Math Psychol 25:87–118

    Article  MathSciNet  MATH  Google Scholar 

  35. Pattison PE (1989) Mathematical models for local socialnetworks. In: Keats J, Taft R, Heath R, Lovibond S (eds) Mathematicaland theoretical systems. North Holland, Amsterdam

    Google Scholar 

  36. Pattison PE (1993) Algebraic models for socialnetworks. Cambridge University Press, New York

    Book  Google Scholar 

  37. Pattison PE, Bartlett WK (1982) A factorization procedurefor finite algebras. J Math Psychol 25:51–81

    Article  MathSciNet  MATH  Google Scholar 

  38. Pattison PE, Breiger RL (2002) Lattices and dimensionalrepresentations: matrix decompositions and ordering structures. SocNetw 24:423–444

    Article  Google Scholar 

  39. Pattison PE, Wasserman S (1995) Constructing algebraic models for local social networks using statistical methods. J Math Psychol 39:57–72

    Article  MATH  Google Scholar 

  40. Pattison PE, Wasserman S, Robins G, Kanfer A (2000) Statistical evaluation of algebraic constraints for social networks. J Math Psychol 44:536–568

    Article  MATH  Google Scholar 

  41. Robins G, Woolcock J, Pattison P (2005) Small and other worlds: Global network structures from local processes. Am J Sociol 110:894–936

    Article  Google Scholar 

  42. Rutherford D (1963) Inverses of Boolean matrices. Proc Glasgow Math Assoc 6:49–53

    Article  MathSciNet  MATH  Google Scholar 

  43. Schein B (1970) A construction for idempotent binary relations. Proc Jpn Acad 46:246–247

    Article  MathSciNet  MATH  Google Scholar 

  44. Schein B (1976) Regular elements of the semigroup of all binary relations. Semigr Forum 13:95–102

    Article  MathSciNet  Google Scholar 

  45. Schweizer T (1993) The dual ordering of actors and possessions. Curr Anthropol 34:469–483

    Article  Google Scholar 

  46. Vickers M (1981) Relational analysis: an appliedevaluation. MSc Thesis, University of Melbourne, Melbourne

    Google Scholar 

  47. White DR, Duquenne V (1996) Special issue on socialnetworks and discrete structure analysis. Soc Netw 18:169–318

    Article  Google Scholar 

  48. White HC (1963) An anatomy of kinship. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  49. White HC (1992) Identity and control. University ofChicago Press, Chicago

    Google Scholar 

  50. White HC, Boorman SA, Breiger RL (1976) Social structure from multiple networks: I. Blockmodels of roles and positions. Am J Sociol 81:730–780

    Article  Google Scholar 

  51. Wille R (1984) Line diagrams of hierarchical concept systems. Intern Classif 11:77–86

    Google Scholar 

  52. Wilson S, Bladin P, Saling M, Pattison P (2005) Characterizing psychosocial outcome trajectories following seizure surgery. Epilepsy Behav 6:570–580

    Article  Google Scholar 

  53. WinshipC, Mandel M (1983) Roles and positions: a critique and extensionof the blockmodelling approach. In: Leinhardt S (ed) Sociologicalmethodology. Jossey-Bass, San Francisco, pp 314–344

    Google Scholar 

  54. Wu L (1983) Local blockmodel algebras for analyzing social networks. In: Leinhardt S (ed) Sociological methodology. Jossey-Bass, San Francisco, pp 272–313

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag

About this entry

Cite this entry

Pattison, P. (2012). Social Networks, Algebraic Models for. In: Meyers, R. (eds) Computational Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1800-9_180

Download citation

Publish with us

Policies and ethics