a toolkit for social network analysis

7/28/2019 A Toolkit for Social Network Analysis

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http://asj.sagepub.comActa Sociologica

DOI: 10.1177/0001699396039002051996; 39; 211Acta Sociologica

John ScottSoftware Review : A Toolkit for Social Network Analysis

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SOFTWARE REVIEW

AToolkit for Social NetworkAnalysis

John Scott

University of Essex

The general principles of social network analysis have recently beenreviewed in a special issue of Acta Sociologica, and an excellent article byMark Mizruchi (1994) introduces some of the basic themes and ideas. Manypeople, however, find this a daunting area to consider, being put off by themathematics and not knowing quite how to begin to learn the ideas that theyneed for their applications. My aim in this paper is to indicate the basic toolkit that might be needed for undertaking a piece of social network analysis.

Considered as a method, rather than as a substantive theory, socialnetwork analysis comprises a collection of techniques for the analysis ofrelational data. These relations may be interpersonal, economic, or political,and so on. Social network analysis provides a mathematical method for

describing the structures of these relations as they are formed into socialnetworks.At its simplest, points (perhaps representing people) are thoughtof as being connected by lines (representing their social relationships). Themathematical approach called graph theory is a way of analysing the formal

properties of such graphs, and so the use of this mathematics allowsresearchers to construct formal models of social networks. It is through theuse of graph theory that such ideas as the distance between two people,their relative centrality, the formation of cliques and the densities of

whole networks can be measured.With the greater availability of computers, social network analysis has

grown as an area, and a number of software packages are now available.With these, it is possible to compute, with great ease, things that a few yearsago were impossible or very time-consuming. It is, however, difficult fornewcomers to navigate through these packages, and most of the availablebooks are of little help in guiding them.Anyone who seeks to undertakesocial network analysis will need the appropriate tool kit of handbooks and

computer software. My purpose in this review is to indicate the main suchtools available, for both novices and more advanced researchers.

The major handbooks for social network analysis, that is, Scott (1992)and Wasserman & Faust (1994), were recently reviewed in the special issue

John Scott, University of Essex, Wivenhoe Park, Colchester C04 3SQ, UK. @ Scandinavian

SociologicalAssociation 1996


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of Acta Sociologica (Plotts 1994), and I will not consider them in detail again.It is, however, worth pointing out the difference of focus in the two books. Ihave to declare an immediate interest as the author, but I see Scott (1992) asparticularly intended as a beginners guide that avoids too many mathema-tical technicalities. It introduces the basic ideas and

principlesof this area

and gives an overview of procedures for handling social network analysis.Wasserman & Fausts book (1994), on the other hand, is a reference sourcefor more advanced practitioners. It is written at an advanced level and isdemanding reading.Anyone who has begun with Scott (1992), however,should be able to handle the book. There are other useful compendiums oftechniques and conceptualizations, such as Freeman et al. (1992), Wasser-man & Galaskiewicz (1994), Burt & Minor (1983), and Knoke & Kuklinski(1982), but none has the introductory aims or the broad sweep of the twohandbooks that I have discussed.

1. Software for network analysisThere are three major packagesavailable for social network analysis on PCs:GRADAP, STRUCTURE and UCINET.1

1

GRADAP

GRADAP has not changed since I last reviewed the program (Scott 1992:

appendix),but both of the other programs have

undergone majorrevisions.

GRADAP remains a major package with powerful applications for manynetwork purposes.Although I do not intend to repeat my original reviewhere, it is worth summarising some of its principal features. GRADAP (theGraph Definition andAnalysis Package) was converted for use on PCs fromits original mainframe version, and still works in a batch mode. It will run onany IBM compatible computer with a mathematical co-processor, but isfastest on a 486 or Pentium machine. It is a fairly fast program, although it isfirst necessary to convert the data files into system files. Its files are set up inSPSS format, and it uses a command language that is based on that of SPSS.

GRADAP operates with files in the form of point sets and line sets; thesedata files contain the basic information on the nodes and their connections.Amajor limitation of GRADAP is that the line set must be produced manually orfrom some other program, as it cannot accept direct sociometric input. Oncecreated, however, the data set can be used for the analyses of subgraphs,centrality, adjacency and distance procedures, each being set up in an inputfile for batch processing. Thus, it is possible to explore cliques, components,and blocks, in directed and in undirected graphs, the relative centralities ofthe points, the density and overall centralization of the network, and, indirected graphs, the indegrees and outdegrees of the various points.

For all its power, however, GRADAP is somewhat cumbersome and is notespecially user-friendly. It has all the disadvantages of a pioneer, and it isunfortunate that its developers have been unable to produce a newer versionof the program. Both STRUCTURE and UCINET, on the other hand, have gonethrough major revamps to produce versions that are more flexible and easierto use.




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STRUCTURE

STRUCTURE, version 4.2, is the latest release of a program that first appearedin 1975. Ronald Burt produced it for his own work on structural autonomyand has since expanded the original program into a powerful suite of

programs.It is currently available in two different forms: a Basic Edition, which

runs on any PC with 425KRAM and a Virtual Memory Edition, which

requires a 386 or better computer with 1 Mb RAM and 5 Mb free disk space.The Basic Edition of the program is limited in the size of network (85 actors)that it can handle because it works exclusively in RAM, whereas the Virtual

memory Edition swaps data back and forth to the hard disk and so can deal

with larger networks (300 actors, or 999 actors with 53 Mb free on your hard

disk). Users of the Virtual Memory Edition will have to exercise good

housekeeping on their hard disks to keep enough space free. I have regularlyupgraded my hard disk, but with the growing requirements of current

programs I never seem to have more than a few Mb free. I have not tested the

compatibility of STRUCTURE with disk compression software.2 Both versionsare supplied with manuals and with anASSISTANT program for preparingcommand files and a JEDIT program for handling data files.

Like GRADAP, STRUCTURE runs in batch mode rather than interactively,and so it is necessary to set up an input command file, a data file, and an

output file. The Basic program is loaded by typing sTRUC at the DOS prompt(there is no Windows version yet) and then, when prompted, entering thename of the input command file. This file tells STRUCTURE which data file touse, the particular analyses to perform, and the name of the output file inwhich the results are to be stored. To run the Virtual Memory edition, youtype vsTRUC, and you are presented with a menu system that allows a degreeof interactive use.

The command file is simply a text file, produced on any text editor orwithASSISTANT, that comprises a number of separate command lines. Thecore lines are those that contain the DATA, NETWORK, andANALYZE commands.

These name the data file, describe the data and set out the particular

procedures to use in the analysis.At its simplest, then,a

command filecontains just these three lines. More complex analyses can be undertaken bybuilding sequences of these three lines, eachANALYZE command telling the

program to carry out the analysis requested.AnANALYZE command on its

own, however, simply performs default calculations, and the line will

normally be preceded by specific commands and options. The program offersCLIQUES, POWER, POSITIONS,AUTONOMY, and other procedures, and the optionsinclude those for calculating density and other graph parameters. Data filesare simple matrices and can be produced in any text editor, spreadsheet, ordatabase package that is capable of writing an output matrix, or by usingGRADAP to produce matrices for direct input to STRUCTURE. The provided JEDITprogram, however, is a useful alternative. TheASSISTANT program compilescommand files, but has in-built procedures for help in testing equivalencehypotheses and undertaking Monte Carlo analyses.

The program itself is based around Burts ideas on cohesion, structural

equivalence, prominence, range, and brokerage. This departs somewhat fromdistribution.

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the assumptions of graph theory that underpin GRADAP and UCINET. ThePOSITIONS command, for example, is used to undertake analyses of structuralequivalence, whileAUTONOMY performs analyses of structural autonomy andconstraint.3 Most of the procedures are unchanged from the earlier version,though they work more rapidly and more smoothly. The program can also berun in an error-checking mode that checks the syntax of commands and theformat of the data files. This saves the program going into a lengthy run, onlyto crash because of a syntax error deep in the command file. I have not testedthe program for speed on varying networks, but Burt claims that a fairlycomplex set of procedures on a 59-person network will load and run in 34seconds in the BASIC Edition and in 47 seconds in the Virtual Memoryedition. This difference is largely because of the time taken up in setting-upthe virtual memory files. There is, then, a slight time penalty in using theVirtual Memory edition on small data sets, but this is outweighed by the

possibilities that it offers for analysing large data sets.

UCINET

UCINET originated at the University of California, Irvine (UCI), and is nowmarketed byAnalytical Technologies. Its authors, Stephen Borgatti, MartinEverett and Linton Freeman, are to be congratulated for producing what is,to my mind, the best of the three programs under review and the one that ismost accessible for the novice. Version 3 consisted of a set of modules that

operated as a cluster of independent programs on the same data files.Version 4 has dispensed with this approach and is now a completelyintegrated interactive package. It now operates through a menu interface,and it is simply necessary to load a data set and then choose analyticalprocedures from the menu bar. The basic version, like its predecessor, runson virtually any PC, the advanced variant of Version 4 requires a 386 orbetter and at least 1.5 Mb of RAM. The program operates with virtual

memory wherever appropriate, trading off speed against size of matrix. Thebasic version claims to handle 500 points for basic clique procedures and 180points for multidimensional scaling.

The main menu offers DATASETS, NETWORKS and MATRICES options, as well

as various disk housekeeping procedures. UCINET 4 data files differ from theirVersion 3 counterparts, though they are still in simple matrix format andstill consist of simple alphanumeric files. Each of the main lines in a filerepresents a row in an incidence or adjacency matrix, but the first linescontain codes for the number of rows and columns and their labels. The

program contains in-built procedures for converting earlier UCINET data filesinto an appropriate format. It will also convert STRUCTURE files.

New data files can be created with the spreadsheet-style data entrysystem, using the linked list format. In this format, it is simply necessary to

enter, for each point, all other points to which it is connected. This procedureis found in the SPREADSHEET option of the NETWORKentry on the menu bar.The file can be edited after data entry and various permutations andtransformations can be performed on the data file in order to identify subsetsfor further analysis. The rows and the columns can be permutated, for

example, or the weightings of lines can be altered by dichotomizing thematrix.




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Once a satisfactory data set has been produced, it can then be subjectedto the basic UCINET procedures. Cliques, for example, are analysed throughusing the SUBGRAPHS option, which is found in the TRANSFORM section of theNETWORKmenu. This procedure allows, for example, the search for n-cliquesand sends a summary ofthe output to the screen. The full output is written toa log file and can be read on screen or printed out. Options available withinUCINET allow measures of adjacency, centrality, distance, and so on, as well asclique and cluster procedures, and a number of variant measures are

generally available for each of these procedures.Very limited plotting of data is possible from within UCINET, although it

had originally been intended to include Borgattis useful little GROUP

program as a component of UCINET. Fortunately,Analytic Technologieshave also made available a separate program called KRACKPLOT, produced byDavid Krackhardt, Mark Lundberg and Laura ORourke. This is an excellent

program with an add-on that converts UCINET files, and it will plot them onthe screen using multidimensional scaling procedures. Once plotted, theycan be labelled and altered in various ways and can be printed using a laseror dot matrix printer. The next step in network analysis packages must,surely, be to incorporate some of the plotting and transformation proceduresavailable in wire-frame graphics programs. Until then, KRACKPLOT is anessential adjunct to UCINET.

2. Conclusion

Any choice of tool kit will be a matter of personal preference, but someguidelines can be given. The starter kit for newcomers and those interestedin basic applications of network analysis, with the emphasis on ease of use,might be the Scott (1992) handbook and the UCINET software. Both areconstructed around ideas from graph theory, though both also range morewidely, and almost any network tasks can be undertaken with the UCINET

program. Those who mainly handle small data sets and who find visual

representation useful should consider adding KRACKPLOT to the tool kit.Amore advanced tool kit would need the Wasserman & Faust (1994) reference

handbook and STRUCTURE, in addition.Although GRADAP is now a little dated,it still has much to offer for those pursuing conventional graph theoreticalanalyses, and would also be a good addition to the advanced tool kit.

First version received September 1995Final version accepted November 1995

Notes

1So far as I am aware, there are no social network analysis

programs available forApple Macs. The three packages consideredhere run on IBM and compatible machines.Availability is as follows:GRADAP, Release 2.1, disks and manual, distributed by iec Pro-GAMMA, Kraneweg 8, 9718 JP, Grningen, The Netherlands;STRUCTURE, Basic Edition, Release 4.2, disks and manuals, distrib-uted by Professor R. Burt, Department of Sociology, University ofChicago, 1126 East 59th Street, Chicago, Illinois 60637, USA, $50


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($125 for Virtual Memory Edition); UCINET, Release 4.0, disks andmanual, distributed byAnalytic Technologies, 306 S. Walker Street,Columbia, SC29205, USA.2The earlier version of STRUCTURE had difficulties running on

some hard disks, but these problems have now been overcome.3

These ideas are discussed in Burt (1982).

References

Burt, R. 1982. Toward a Structural Theory ofAction. New York:Academic Press.

Burt, R. & Minor 1983.Applied NetworkAnalysis:A MethodologicalIntroduction. Beverly Hills: Sage.

Freeman, L. C., White, D. R. & Romney,A. K. (eds) 1992. ResearchMethods in Social NetworkAnalysis. New Brunswick: Transaction.

Knoke,D. &

Kuklinski,J. H. 1982. Network

Analysis. BeverlyHills:

Sage.Mizruchi, M. 1994. Social NetworkAnalysis: RecentAchievementsand Current Controversies.Acta Sociologica 37, 329-343.

Plotts, B. P. 1994. Review of Scott (1992) and Wasserman and Faust(1994).Acta Sociologica 37, 419-423.

Scott, J. 1992. Social NetworkAnalysis:AHandbook. London: Sage.Wasserman, S. & Faust, K. 1994. Social NetworkAnalysis: MethodsandApplications. Cambridge: Cambridge University Press.

Wasserman, S. & Galaskiewicz, J. (eds) 1994.Advances in SocialNetworkAnalysis. Beverly Hills: Sage.



a toolkit for social network analysis

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