Publicação
Quantifying Data-Driven Campaigning Across Sponsors and Platforms
| Resumo: | Although modern data-driven campaigning (DDC) is not entirely new, scholars have typically relied on reports and interviews of practitioners to understand its use. However, the advent of public ad libraries from Meta and Google provides an opportunity to measure the scope and variation in DDC practice in advertising across different types of sponsors and within sponsors across platforms. Using textual and audiovisual processing, we create a database of ads from the 2022 US elections. These data allow us to create an index that quantifies the extent of DDC at the level of the sponsor and platform. This index takes into account both the number of unique creatives placed and the similarity across those creatives. In addition, we explore the impact of sponsor resources, the office being sought, and the competitiveness of the race on the measure of DDC sophistication. Ultimately, our research establishes a measurement strategy for DDC that can be applied across ad sponsors, campaigns, parties, and even countries. Understanding the extent of DDC is vital for policy discussions surrounding the regulation of microtargeting and data privacy. |
|---|---|
| Autores principais: | Franz, Michael M. |
| Outros Autores: | Zhang, Meiqing; Ridout, Travis N.; Oleinikov, Pavel; Yao, Jielu; Cakmak, Furkan; Fowler, Erika Franklin |
| Assunto: | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | unknown |
| Instituição associada: | Cogitatio Press |
| Idioma: | inglês |
| Origem: | Media and Communication |
| _version_ | 1864888757495267328 |
|---|---|
| author | Franz, Michael M. |
| author2 | Zhang, Meiqing Ridout, Travis N. Oleinikov, Pavel Yao, Jielu Cakmak, Furkan Fowler, Erika Franklin |
| author2_role | author author author author author author |
| author_facet | Franz, Michael M. Zhang, Meiqing Ridout, Travis N. Oleinikov, Pavel Yao, Jielu Cakmak, Furkan Fowler, Erika Franklin |
| author_role | author |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Franz, Michael M.\"},{\"Person.name\":\"Zhang, Meiqing\"},{\"Person.name\":\"Ridout, Travis N.\"},{\"Person.name\":\"Oleinikov, Pavel\"},{\"Person.name\":\"Yao, Jielu\"},{\"Person.name\":\"Cakmak, Furkan\"},{\"Person.name\":\"Fowler, Erika Franklin\"}] |
| datacite.creators.creator.creatorName.fl_str_mv | Franz, Michael M. Zhang, Meiqing Ridout, Travis N. Oleinikov, Pavel Yao, Jielu Cakmak, Furkan Fowler, Erika Franklin |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| datacite.titles.title.fl_str_mv | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| dc.creator.none.fl_str_mv | Franz, Michael M. Zhang, Meiqing Ridout, Travis N. Oleinikov, Pavel Yao, Jielu Cakmak, Furkan Fowler, Erika Franklin |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://doi.org/10.17645/mac.8577 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Cogitatio Press |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.rights.rights.copyright.fl_str_mv | https://creativecommons.org/licenses/by/4.0 |
| dc.source.none.fl_str_mv | Media and Communication; Vol 12 (2024): Data-Driven Campaigning in a Comparative Context: Toward a 4th Era of Political Communication? 2183-2439 10.17645/mac.i457 |
| dc.subject.none.fl_str_mv | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| dc.title.fl_str_mv | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Although modern data-driven campaigning (DDC) is not entirely new, scholars have typically relied on reports and interviews of practitioners to understand its use. However, the advent of public ad libraries from Meta and Google provides an opportunity to measure the scope and variation in DDC practice in advertising across different types of sponsors and within sponsors across platforms. Using textual and audiovisual processing, we create a database of ads from the 2022 US elections. These data allow us to create an index that quantifies the extent of DDC at the level of the sponsor and platform. This index takes into account both the number of unique creatives placed and the similarity across those creatives. In addition, we explore the impact of sponsor resources, the office being sought, and the competitiveness of the race on the measure of DDC sophistication. Ultimately, our research establishes a measurement strategy for DDC that can be applied across ad sponsors, campaigns, parties, and even countries. Understanding the extent of DDC is vital for policy discussions surrounding the regulation of microtargeting and data privacy. |
| dirty | 0 |
| eu_rights_str_mv | unknown |
| format | article |
| id | mc_d63d007a80927dbfad5d009a3dfd357a |
| identifier.doi.fl_str_mv | https://doi.org/10.17645/mac.8577 |
| instacron_str | cp |
| institution | Cogitatio Press |
| instname_str | Cogitatio Press |
| language | eng |
| network_acronym_str | mc |
| network_name_str | Media and Communication |
| oai_identifier_str | oai:ojs.cogitatiopress.com:article/8577 |
| organization_str_mv | urn:organizationAcronym:cp |
| person_str_mv | Franz, Michael M. Zhang, Meiqing Ridout, Travis N. Oleinikov, Pavel Yao, Jielu Cakmak, Furkan Fowler, Erika Franklin |
| publishDate | 2024 |
| publisher.none.fl_str_mv | Cogitatio Press |
| reponame_str | Media and Communication |
| repository_id_str | urn:repositoryAcronym:mc |
| service_str_mv | urn:repositoryAcronym:mc |
| spelling | en-USQuantifying Data-Driven Campaigning Across Sponsors and PlatformsFranz, Michael M.Zhang, MeiqingRidout, Travis N.Oleinikov, PavelYao, JieluCakmak, FurkanFowler, Erika Franklindata-driven campaigning; digital campaigning; election campaigns; political advertisingCopyright (c) 2024 Michael M. Franz, Meiqing Zhang, Travis N. Ridout, Pavel Oleinikov, Jielu Yao, Furkan Cakmak, Erika Franklin Fowlerhttp://purl.org/coar/access_right/c_abf2https://doi.org/10.17645/mac.8577DOIhttps://www.cogitatiopress.com/mediaandcommunication/article/view/8577URLHasVersionhttps://www.cogitatiopress.com/mediaandcommunication/article/view/8577/4022URLHasVersionhttps://www.cogitatiopress.com/mediaandcommunication/article/downloadSuppFile/8577/4054URLHasVersionhttps://doi.org/10.17645/mac.8577DOI2024-10-31en-USAlthough modern data-driven campaigning (DDC) is not entirely new, scholars have typically relied on reports and interviews of practitioners to understand its use. However, the advent of public ad libraries from Meta and Google provides an opportunity to measure the scope and variation in DDC practice in advertising across different types of sponsors and within sponsors across platforms. Using textual and audiovisual processing, we create a database of ads from the 2022 US elections. These data allow us to create an index that quantifies the extent of DDC at the level of the sponsor and platform. This index takes into account both the number of unique creatives placed and the similarity across those creatives. In addition, we explore the impact of sponsor resources, the office being sought, and the competitiveness of the race on the measure of DDC sophistication. Ultimately, our research establishes a measurement strategy for DDC that can be applied across ad sponsors, campaigns, parties, and even countries. Understanding the extent of DDC is vital for policy discussions surrounding the regulation of microtargeting and data privacy.Cogitatio Pressapplication/pdfen-USMedia and Communication; Vol 12 (2024): Data-Driven Campaigning in a Comparative Context: Toward a 4th Era of Political Communication?2183-243910.17645/mac.i457engjournal articlehttp://purl.org/coar/resource_type/c_6501literatureVoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85https://creativecommons.org/licenses/by/4.0 |
| spellingShingle | Quantifying Data-Driven Campaigning Across Sponsors and Platforms Franz, Michael M. data-driven campaigning; digital campaigning; election campaigns; political advertising |
| status_str | VoR |
| subject.fl_str_mv | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| title | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| title_full | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| title_fullStr | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| title_full_unstemmed | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| title_short | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| title_sort | Quantifying Data-Driven Campaigning Across Sponsors and Platforms |
| topic | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| topic_facet | data-driven campaigning; digital campaigning; election campaigns; political advertising |
| url | https://doi.org/10.17645/mac.8577 |
| visible | 1 |