Zobrazit v EDS

The Re-mediation of Legacy and New Media on Twitter: A Six-Language Comparison of the European Social Media Discourse on Migration

Uloženo v:
Podrobná bibliografie
Název: The Re-mediation of Legacy and New Media on Twitter: A Six-Language Comparison of the European Social Media Discourse on Migration
Autoři: Farjam, Mike, Dutceac Segesten, Anamaria
Přispěvatelé: Lund University, Lunds universitet, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator
Zdroj: Social Science Computer Review. 42(5):1136-1159
Témata: Social Sciences, Political Science, Samhällsvetenskap, Statsvetenskap, Media and Communications, Medie, kommunikations, och informationsvetenskaper, Natural Sciences, Computer and Information Sciences, Natural Language Processing, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Språkbehandling och datorlingvistik
Popis: Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across languages but clearly different when remediating legacy and new media. Trust in legacy media is correlated with higher proportion of shared links from legacy media and reversely related to the proportion of shared links from new media sources. Considering the volume and timingof the remediated content, we conclude that legacy media retains its agenda setting power. New media linked content tends to cover migration in association to subjects such as Islam or terrorism and to express strong critical opinions against migrants/refugees. The language used is more toxic than in legacy media linked content. The tweets remediating legacy media articles covered topics like domestic or European politics, causes of refugee arrivals and procedures to give them protection. Thus, legacy and new media remediated content differs in both tone and function: toxicity is low and factuality high for content linking to legacy media, with the reverse being true for new media remediations.
Přístupová URL adresa: https://doi.org/10.1177/08944393241246101
Databáze: SwePub
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.1177/08944393241246101#
    Name: EDS - SwePub (s4221598)
    Category: fullText
    Text: View record in SwePub
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Farjam%20M
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsswe
DbLabel: SwePub
An: edsswe.oai.portal.research.lu.se.publications.02773e9f.8a7c.4bb0.80a8.96a5a85a83eb
RelevancyScore: 979
AccessLevel: 6
PubType: Review
PubTypeId: review
PreciseRelevancyScore: 979.415405273438
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Re-mediation of Legacy and New Media on Twitter: A Six-Language Comparison of the European Social Media Discourse on Migration
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Farjam%2C+Mike%22">Farjam, Mike</searchLink><br /><searchLink fieldCode="AR" term="%22Dutceac+Segesten%2C+Anamaria%22">Dutceac Segesten, Anamaria</searchLink>
– Name: Author
  Label: Contributors
  Group: Au
  Data: Lund University, Lunds universitet, Originator<br />Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>Social Science Computer Review</i>. 42(5):1136-1159
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Social+Sciences%22">Social Sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Political+Science%22">Political Science</searchLink><br /><searchLink fieldCode="DE" term="%22Samhällsvetenskap%22">Samhällsvetenskap</searchLink><br /><searchLink fieldCode="DE" term="%22Statsvetenskap%22">Statsvetenskap</searchLink><br /><searchLink fieldCode="DE" term="%22Media+and+Communications%22">Media and Communications</searchLink><br /><searchLink fieldCode="DE" term="%22Medie%22">Medie</searchLink><br /><searchLink fieldCode="DE" term="%22kommunikations%22">kommunikations</searchLink><br /><searchLink fieldCode="DE" term="%22och+informationsvetenskaper%22">och informationsvetenskaper</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+Sciences%22">Natural Sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+and+Information+Sciences%22">Computer and Information Sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+Language+Processing%22">Natural Language Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Naturvetenskap%22">Naturvetenskap</searchLink><br /><searchLink fieldCode="DE" term="%22Data-+och+informationsvetenskap+%28Datateknik%29%22">Data- och informationsvetenskap (Datateknik)</searchLink><br /><searchLink fieldCode="DE" term="%22Språkbehandling+och+datorlingvistik%22">Språkbehandling och datorlingvistik</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across languages but clearly different when remediating legacy and new media. Trust in legacy media is correlated with higher proportion of shared links from legacy media and reversely related to the proportion of shared links from new media sources. Considering the volume and timingof the remediated content, we conclude that legacy media retains its agenda setting power. New media linked content tends to cover migration in association to subjects such as Islam or terrorism and to express strong critical opinions against migrants/refugees. The language used is more toxic than in legacy media linked content. The tweets remediating legacy media articles covered topics like domestic or European politics, causes of refugee arrivals and procedures to give them protection. Thus, legacy and new media remediated content differs in both tone and function: toxicity is low and factuality high for content linking to legacy media, with the reverse being true for new media remediations.
– Name: URL
  Label: Access URL
  Group: URL
  Data: <link linkTarget="URL" linkTerm="https://doi.org/10.1177/08944393241246101" linkWindow="_blank">https://doi.org/10.1177/08944393241246101</link>
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsswe&AN=edsswe.oai.portal.research.lu.se.publications.02773e9f.8a7c.4bb0.80a8.96a5a85a83eb
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/08944393241246101
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 1136
    Subjects:
      – SubjectFull: Social Sciences
        Type: general
      – SubjectFull: Political Science
        Type: general
      – SubjectFull: Samhällsvetenskap
        Type: general
      – SubjectFull: Statsvetenskap
        Type: general
      – SubjectFull: Media and Communications
        Type: general
      – SubjectFull: Medie
        Type: general
      – SubjectFull: kommunikations
        Type: general
      – SubjectFull: och informationsvetenskaper
        Type: general
      – SubjectFull: Natural Sciences
        Type: general
      – SubjectFull: Computer and Information Sciences
        Type: general
      – SubjectFull: Natural Language Processing
        Type: general
      – SubjectFull: Naturvetenskap
        Type: general
      – SubjectFull: Data- och informationsvetenskap (Datateknik)
        Type: general
      – SubjectFull: Språkbehandling och datorlingvistik
        Type: general
    Titles:
      – TitleFull: The Re-mediation of Legacy and New Media on Twitter: A Six-Language Comparison of the European Social Media Discourse on Migration
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Farjam, Mike
      – PersonEntity:
          Name:
            NameFull: Dutceac Segesten, Anamaria
      – PersonEntity:
          Name:
            NameFull: Lund University, Lunds universitet, Originator
      – PersonEntity:
          Name:
            NameFull: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 08944393
            – Type: issn-locals
              Value: SWEPUB_FREE
            – Type: issn-locals
              Value: LU_SWEPUB
          Numbering:
            – Type: volume
              Value: 42
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Social Science Computer Review
              Type: main
ResultId 1