Network AnalysisNetwork AnalysisData CollectionData Collection

Important Factors for ResearchImportant Factors for Researchin Network Analysisin Network Analysis

• Boundary SpecificationBoundary Specification

• SamplingSampling

• MeasurementMeasurement

Boundary SpecificationBoundary Specification

Social Networks usually don’t have Social Networks usually don’t have obvious boundariesobvious boundaries

““Snowball sampling”-Analyst begins with Snowball sampling”-Analyst begins with actors identified as a part of the network actors identified as a part of the network (first zone), then moves progressively (first zone), then moves progressively outward to other actors identified by first outward to other actors identified by first actors (second, third zones, etc.) actors (second, third zones, etc.)

Snowball SamplingSnowball Sampling

Number of “zones” to be included will vary Number of “zones” to be included will vary depending on type of phenomenon being depending on type of phenomenon being investigatedinvestigated

Must include all relevant levels of the Must include all relevant levels of the networknetwork

Using too few zones can distort dataUsing too few zones can distort data Better to include too many zones rather Better to include too many zones rather

than too fewthan too few

Two Approaches to Boundary Two Approaches to Boundary SpecificationSpecification

Realist approachRealist approach

Nominalist perspectiveNominalist perspective

Realist ApproachRealist Approach

Analyst adopts subjective perceptions of Analyst adopts subjective perceptions of the actors themselvesthe actors themselves Boundaries are defined as the limits Boundaries are defined as the limits

experienced by members of the entityexperienced by members of the entity

Mutual RelevanceMutual Relevance Only actors who are relevant to each other Only actors who are relevant to each other

are included in the social networkare included in the social network May not set precise, definite boundariesMay not set precise, definite boundaries

Mutual RelevanceMutual Relevance

Valuable for studying large-scale systemsValuable for studying large-scale systems Four types of empirical evidence for inclusionFour types of empirical evidence for inclusion

Positional-formal entities with direct functions or Positional-formal entities with direct functions or interests in the domaininterests in the domain

Decisional-entities with decision-making power in the Decisional-entities with decision-making power in the domaindomain

Reputational-entities recognized by others to be Reputational-entities recognized by others to be influential in the domaininfluential in the domain

Relational-entities recognized as a part of the domain Relational-entities recognized as a part of the domain due to connections with entities of the first three typesdue to connections with entities of the first three types

Nominalist PerspectiveNominalist Perspective

Boundaries are defined by the researcher Boundaries are defined by the researcher based on the conceptual framework based on the conceptual framework required for the studyrequired for the study Used for laboratory studies or formally Used for laboratory studies or formally

bounded natural groupsbounded natural groups Restricted to relatively small groupsRestricted to relatively small groups May omit effect of interactions outside the May omit effect of interactions outside the

observed areaobserved area

SamplingSampling

Sampling is difficult due to the potential number Sampling is difficult due to the potential number of entities in a networkof entities in a network Number of potential ties in a population of size N is Number of potential ties in a population of size N is

N(N-1)/2N(N-1)/2 Sampling in network analysis cannot be randomSampling in network analysis cannot be random

At this time, there is not an entirely satisfactory At this time, there is not an entirely satisfactory strategy for developing a sample for network strategy for developing a sample for network analysisanalysis Some advances have been made in this areaSome advances have been made in this area

Recent Methods of Sampling 1Recent Methods of Sampling 1

Analyst develops a list of respondentsAnalyst develops a list of respondents

Ask each respondent who s/he knows on Ask each respondent who s/he knows on that listthat list

The observed density of ties between The observed density of ties between respondents on the list will be an unbiased respondents on the list will be an unbiased estimate of the density of the entire estimate of the density of the entire networknetwork

Limitations of Sampling Method 1Limitations of Sampling Method 1

Can not be used at the level of the Can not be used at the level of the individualindividual

Mainly used to estimate the density of Mainly used to estimate the density of relations of the populationrelations of the population

Analyst must have specific names of Analyst must have specific names of individuals rather than general individuals rather than general identificationidentification

Recent Methods of Sampling 2Recent Methods of Sampling 2

The analyst identifies personal attributes The analyst identifies personal attributes that capture social stratificationthat capture social stratification

Attributes are combined so that individuals Attributes are combined so that individuals in each category have similar relations in each category have similar relations with otherswith others

Individuals with identical attributes are Individuals with identical attributes are assumed to have identical relationsassumed to have identical relations

MeasurementMeasurement

Strength of the link between pairs of actorsStrength of the link between pairs of actors

Level of mutual involvement in the same Level of mutual involvement in the same activitiesactivities

Strength of LinksStrength of Links

Simple dichotomy-present link vs. absent Simple dichotomy-present link vs. absent linklink

Detailed quantitative scale-number of Detailed quantitative scale-number of interactions between a pair of actors over interactions between a pair of actors over a specified period of timea specified period of time

Mutual InvolvementMutual Involvement

May be measured with varying degrees of May be measured with varying degrees of specificity-the number of times one actor specificity-the number of times one actor initiates a particular type of activity with initiates a particular type of activity with another actoranother actor

Methods of Data CollectionMethods of Data Collection

Direct observationDirect observation

Archival researchArchival research

Self-report surveysSelf-report surveys

Direct ObservationDirect Observation

PlusesPluses Data is known to be validData is known to be valid Researcher has better understanding of dataResearcher has better understanding of data

MinusesMinuses Observed network must be smallObserved network must be small May require a great deal of time if behavior May require a great deal of time if behavior

being analyzed is infrequentbeing analyzed is infrequent Presence of researcher may affect behavior Presence of researcher may affect behavior

of subjectsof subjects

Archival ResearchArchival Research

Can provide data on entities no longer Can provide data on entities no longer available due to death or dissolutionavailable due to death or dissolution

Can provide data that spans long periods Can provide data that spans long periods of timeof time

Self-Report SurveysSelf-Report Surveys

Most common source of data on social Most common source of data on social networksnetworks

Several potential problemsSeveral potential problems Subjects may not have accurate recall of Subjects may not have accurate recall of

interactionsinteractions Interviewee fatigueInterviewee fatigue

Self-Report Surveys:Self-Report Surveys:Subject RecallSubject Recall

Methods to improve accuracy of Methods to improve accuracy of responsesresponses

Use specific, detailed questionsUse specific, detailed questions Provide cues to respondentsProvide cues to respondents Don’t provide options that are too closely Don’t provide options that are too closely

interpretedinterpreted

Self-Report SurveysSelf-Report SurveysInterviewee FatigueInterviewee Fatigue

If a person has a great number of contacts If a person has a great number of contacts for the relation under investigation, a great for the relation under investigation, a great deal of time may be required to provide all deal of time may be required to provide all necessary names and detailsnecessary names and details

Dividing data collection surveys into steps Dividing data collection surveys into steps may help alleviate fatiguemay help alleviate fatigue

Missing DataMissing Data

Missing data is more crucial in network Missing data is more crucial in network analysis than in other types of social analysis than in other types of social researchresearch

A small number of missing entities can A small number of missing entities can also lead to exclusion of their linked also lead to exclusion of their linked entitiesentities

No good solution, researcher must use No good solution, researcher must use great care in data collectiongreat care in data collection