Optimizing Content with A/B Headline Testing: Changing Newsroom Practices
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.17645/mac.v7i1.1801 |
Resumo: | Audience analytics are an increasingly essential part of the modern newsroom as publishers seek to maximize the reach and commercial potential of their content. On top of a wealth of audience data collected, algorithmic approaches can then be applied with an eye towards predicting and optimizing the performance of content based on historical patterns. This work focuses specifically on content optimization practices surrounding the use of A/B headline testing in newsrooms. Using such approaches, digital newsrooms might audience-test as many as a dozen headlines per article, collecting data that allows an optimization algorithm to converge on the headline that is best with respect to some metric, such as the click-through rate. This article presents the results of an interview study which illuminate the ways in which A/B testing algorithms are changing workflow and headline writing practices, as well as the social dynamics shaping this process and its implementation within US newsrooms. |
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Optimizing Content with A/B Headline Testing: Changing Newsroom Practicesaudience metrics; content optimization; digital media; headline testing; headlinesAudience analytics are an increasingly essential part of the modern newsroom as publishers seek to maximize the reach and commercial potential of their content. On top of a wealth of audience data collected, algorithmic approaches can then be applied with an eye towards predicting and optimizing the performance of content based on historical patterns. This work focuses specifically on content optimization practices surrounding the use of A/B headline testing in newsrooms. Using such approaches, digital newsrooms might audience-test as many as a dozen headlines per article, collecting data that allows an optimization algorithm to converge on the headline that is best with respect to some metric, such as the click-through rate. This article presents the results of an interview study which illuminate the ways in which A/B testing algorithms are changing workflow and headline writing practices, as well as the social dynamics shaping this process and its implementation within US newsrooms.Cogitatio2019-02-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.17645/mac.v7i1.1801oai:ojs.cogitatiopress.com:article/1801Media and Communication; Vol 7, No 1 (2019): Emerging Technologies in Journalism and Media: International Perspectives on Their Nature and Impact; 117-1272183-2439reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://www.cogitatiopress.com/mediaandcommunication/article/view/1801https://doi.org/10.17645/mac.v7i1.1801https://www.cogitatiopress.com/mediaandcommunication/article/view/1801/1801Copyright (c) 2019 Nick Hagar, Nicholas Diakopouloshttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessHagar, NickDiakopoulos, Nicholas2022-12-20T10:57:51Zoai:ojs.cogitatiopress.com:article/1801Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:20:34.049527Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
title |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
spellingShingle |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices Hagar, Nick audience metrics; content optimization; digital media; headline testing; headlines |
title_short |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
title_full |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
title_fullStr |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
title_full_unstemmed |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
title_sort |
Optimizing Content with A/B Headline Testing: Changing Newsroom Practices |
author |
Hagar, Nick |
author_facet |
Hagar, Nick Diakopoulos, Nicholas |
author_role |
author |
author2 |
Diakopoulos, Nicholas |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Hagar, Nick Diakopoulos, Nicholas |
dc.subject.por.fl_str_mv |
audience metrics; content optimization; digital media; headline testing; headlines |
topic |
audience metrics; content optimization; digital media; headline testing; headlines |
description |
Audience analytics are an increasingly essential part of the modern newsroom as publishers seek to maximize the reach and commercial potential of their content. On top of a wealth of audience data collected, algorithmic approaches can then be applied with an eye towards predicting and optimizing the performance of content based on historical patterns. This work focuses specifically on content optimization practices surrounding the use of A/B headline testing in newsrooms. Using such approaches, digital newsrooms might audience-test as many as a dozen headlines per article, collecting data that allows an optimization algorithm to converge on the headline that is best with respect to some metric, such as the click-through rate. This article presents the results of an interview study which illuminate the ways in which A/B testing algorithms are changing workflow and headline writing practices, as well as the social dynamics shaping this process and its implementation within US newsrooms. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-02-19 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.17645/mac.v7i1.1801 oai:ojs.cogitatiopress.com:article/1801 |
url |
https://doi.org/10.17645/mac.v7i1.1801 |
identifier_str_mv |
oai:ojs.cogitatiopress.com:article/1801 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.cogitatiopress.com/mediaandcommunication/article/view/1801 https://doi.org/10.17645/mac.v7i1.1801 https://www.cogitatiopress.com/mediaandcommunication/article/view/1801/1801 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 Nick Hagar, Nicholas Diakopoulos http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 Nick Hagar, Nicholas Diakopoulos http://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Cogitatio |
publisher.none.fl_str_mv |
Cogitatio |
dc.source.none.fl_str_mv |
Media and Communication; Vol 7, No 1 (2019): Emerging Technologies in Journalism and Media: International Perspectives on Their Nature and Impact; 117-127 2183-2439 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799130654111170560 |