View in EDS PDF Full Text

Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?

Saved in:
Bibliographic Details
Title: Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?
Authors: Le Mens, Gaël1,2,3 gael.le-mens@upf.edu, Kovács, Balázs4 balazs.kovacs@yale.edu, Hannan, Michael T.5 hannan@stanford.edu, Pros, Guillem1 guillem.pros@upf.edu
Source: Sociological Science. Mar2023, Vol. 10, p82-117. 36p.
Database: Sociology Source Ultimate
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: sxi
DbLabel: Sociology Source Ultimate
An: 162340230
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Le+Mens%2C+Gaël%22">Le Mens, Gaël</searchLink><relatesTo>1,2,3</relatesTo><i> gael.le-mens@upf.edu</i><br /><searchLink fieldCode="AR" term="%22Kovács%2C+Balázs%22">Kovács, Balázs</searchLink><relatesTo>4</relatesTo><i> balazs.kovacs@yale.edu</i><br /><searchLink fieldCode="AR" term="%22Hannan%2C+Michael+T%2E%22">Hannan, Michael T.</searchLink><relatesTo>5</relatesTo><i> hannan@stanford.edu</i><br /><searchLink fieldCode="AR" term="%22Pros%2C+Guillem%22">Pros, Guillem</searchLink><relatesTo>1</relatesTo><i> guillem.pros@upf.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Sociological+Science%22">Sociological Science</searchLink>. Mar2023, Vol. 10, p82-117. 36p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=sxi&AN=162340230
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.15195/v10.a3
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 36
        StartPage: 82
    Titles:
      – TitleFull: Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Le Mens, Gaël
      – PersonEntity:
          Name:
            NameFull: Kovács, Balázs
      – PersonEntity:
          Name:
            NameFull: Hannan, Michael T.
      – PersonEntity:
          Name:
            NameFull: Pros, Guillem
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 03
              Text: Mar2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 23306696
          Numbering:
            – Type: volume
              Value: 10
          Titles:
            – TitleFull: Sociological Science
              Type: main
ResultId 1