View in EDS

Network of Categories: A Method to Aggregate Egocentric Network Survey Data into a Whole Network Structure

Saved in:
Bibliographic Details
Title: Network of Categories: A Method to Aggregate Egocentric Network Survey Data into a Whole Network Structure
Language: English
Authors: Mireia Bolíbar (ORCID 0000-0001-9525-0907), Julia Martínez-Ariño, Maria Schiller
Source: Field Methods. 2025 37(2):110-127.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 18
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Measurement Techniques, Data Analysis, Data Collection, Networks, Network Analysis, Surveys, Immigrants, Organizations (Groups), Governance, Foreign Countries
Geographic Terms: France, Germany
DOI: 10.1177/1525822X241262678
ISSN: 1525-822X
1552-3969
Abstract: We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g., "being immigrant organizations") and abstract attribute-based groups or types of alters (e.g., "any immigrant organization"). This method takes advantage of both whole networks and ego-centered networks analytical approaches since it gains insights into the context's whole network structure while generalizing the results to a wider population. The method can be applied to data obtained through modified versions of instruments such as position or resource generators, which are easy to collect within standard large-N representative surveys. We present a concrete application of the method to the analysis of immigrant organizations' position in local governance networks in 40 French and German cities.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1466740
Database: ERIC
FullText Text:
  Availability: 0
Header DbId: eric
DbLabel: ERIC
An: EJ1466740
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Network of Categories: A Method to Aggregate Egocentric Network Survey Data into a Whole Network Structure
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Mireia+Bolíbar%22">Mireia Bolíbar</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9525-0907">0000-0001-9525-0907</externalLink>)<br /><searchLink fieldCode="AR" term="%22Julia+Martínez-Ariño%22">Julia Martínez-Ariño</searchLink><br /><searchLink fieldCode="AR" term="%22Maria+Schiller%22">Maria Schiller</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Field+Methods%22"><i>Field Methods</i></searchLink>. 2025 37(2):110-127.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 18
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Collection%22">Data Collection</searchLink><br /><searchLink fieldCode="DE" term="%22Networks%22">Networks</searchLink><br /><searchLink fieldCode="DE" term="%22Network+Analysis%22">Network Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Surveys%22">Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Immigrants%22">Immigrants</searchLink><br /><searchLink fieldCode="DE" term="%22Organizations+%28Groups%29%22">Organizations (Groups)</searchLink><br /><searchLink fieldCode="DE" term="%22Governance%22">Governance</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22France%22">France</searchLink><br /><searchLink fieldCode="DE" term="%22Germany%22">Germany</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/1525822X241262678
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1525-822X<br />1552-3969
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g., "being immigrant organizations") and abstract attribute-based groups or types of alters (e.g., "any immigrant organization"). This method takes advantage of both whole networks and ego-centered networks analytical approaches since it gains insights into the context's whole network structure while generalizing the results to a wider population. The method can be applied to data obtained through modified versions of instruments such as position or resource generators, which are easy to collect within standard large-N representative surveys. We present a concrete application of the method to the analysis of immigrant organizations' position in local governance networks in 40 French and German cities.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1466740
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1466740
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/1525822X241262678
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 110
    Subjects:
      – SubjectFull: Measurement Techniques
        Type: general
      – SubjectFull: Data Analysis
        Type: general
      – SubjectFull: Data Collection
        Type: general
      – SubjectFull: Networks
        Type: general
      – SubjectFull: Network Analysis
        Type: general
      – SubjectFull: Surveys
        Type: general
      – SubjectFull: Immigrants
        Type: general
      – SubjectFull: Organizations (Groups)
        Type: general
      – SubjectFull: Governance
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: France
        Type: general
      – SubjectFull: Germany
        Type: general
    Titles:
      – TitleFull: Network of Categories: A Method to Aggregate Egocentric Network Survey Data into a Whole Network Structure
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Mireia Bolíbar
      – PersonEntity:
          Name:
            NameFull: Julia Martínez-Ariño
      – PersonEntity:
          Name:
            NameFull: Maria Schiller
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 1525-822X
            – Type: issn-electronic
              Value: 1552-3969
          Numbering:
            – Type: volume
              Value: 37
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Field Methods
              Type: main
ResultId 1