network analysis data collection. important factors for research in network analysis boundary...
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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