Meta-dominance analysis – A tool for the assessment of the quality of digital behavioural data Article Swipe
Andreas Schneck
,
Wojtek Przepiorka
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.31235/osf.io/cy3wj
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.31235/osf.io/cy3wj
We propose a simple yet comprehensive conceptual framework for the identification of different sources of error in research with digital behavioural data. We use our framework to map potential sources of error in 25 years of research on reputation effects in peer-to-peer online market platforms. Using a meta-dataset comprising 346 effect sizes extracted from 109 articles, we apply meta-dominance analysis to quantify the relative importance of different error components. Our results indicate that 85% of explained effect size heterogeneity can be attributed to the measurement process, which comprises the choice of platform, data collection mode, construct operationalisation and variable transformation. Error components attributable to the sampling process or publication bias capture relatively small parts of the explained effect size heterogeneity. This approach reveals at which stages of the research process researcher decisions may affect data quality most. This approach can be used to identify potential sources of error in established strands of research beyond the literature of behavioural data from online platforms.
Related Topics
Concepts
Computer science
Dominance (genetics)
Process (computing)
Construct (python library)
Data quality
Reputation
Data mining
Data science
Quality (philosophy)
Econometrics
Data collection
Statistics
Mathematics
Marketing
Gene
Business
Sociology
Social science
Biochemistry
Epistemology
Philosophy
Chemistry
Operating system
Metric (unit)
Programming language
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31235/osf.io/cy3wj
- https://osf.io/cy3wj/download
- OA Status
- gold
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4323980358
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4323980358Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.31235/osf.io/cy3wjDigital Object Identifier
- Title
-
Meta-dominance analysis – A tool for the assessment of the quality of digital behavioural dataWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-11Full publication date if available
- Authors
-
Andreas Schneck, Wojtek PrzepiorkaList of authors in order
- Landing page
-
https://doi.org/10.31235/osf.io/cy3wjPublisher landing page
- PDF URL
-
https://osf.io/cy3wj/downloadDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://osf.io/cy3wj/downloadDirect OA link when available
- Concepts
-
Computer science, Dominance (genetics), Process (computing), Construct (python library), Data quality, Reputation, Data mining, Data science, Quality (philosophy), Econometrics, Data collection, Statistics, Mathematics, Marketing, Gene, Business, Sociology, Social science, Biochemistry, Epistemology, Philosophy, Chemistry, Operating system, Metric (unit), Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
70Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4323980358 |
|---|---|
| doi | https://doi.org/10.31235/osf.io/cy3wj |
| ids.doi | https://doi.org/10.31235/osf.io/cy3wj |
| ids.openalex | https://openalex.org/W4323980358 |
| fwci | |
| type | preprint |
| title | Meta-dominance analysis – A tool for the assessment of the quality of digital behavioural data |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10609 |
| topics[0].field.id | https://openalex.org/fields/33 |
| topics[0].field.display_name | Social Sciences |
| topics[0].score | 0.9904999732971191 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3312 |
| topics[0].subfield.display_name | Sociology and Political Science |
| topics[0].display_name | Digital Marketing and Social Media |
| topics[1].id | https://openalex.org/T10068 |
| topics[1].field.id | https://openalex.org/fields/18 |
| topics[1].field.display_name | Decision Sciences |
| topics[1].score | 0.9742000102996826 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1802 |
| topics[1].subfield.display_name | Information Systems and Management |
| topics[1].display_name | Technology Adoption and User Behaviour |
| topics[2].id | https://openalex.org/T11995 |
| topics[2].field.id | https://openalex.org/fields/14 |
| topics[2].field.display_name | Business, Management and Accounting |
| topics[2].score | 0.9656999707221985 |
| topics[2].domain.id | https://openalex.org/domains/2 |
| topics[2].domain.display_name | Social Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1404 |
| topics[2].subfield.display_name | Management Information Systems |
| topics[2].display_name | FinTech, Crowdfunding, Digital Finance |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.6245059967041016 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C151913843 |
| concepts[1].level | 3 |
| concepts[1].score | 0.5758311748504639 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q3454555 |
| concepts[1].display_name | Dominance (genetics) |
| concepts[2].id | https://openalex.org/C98045186 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5196658372879028 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[2].display_name | Process (computing) |
| concepts[3].id | https://openalex.org/C2780801425 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5069125294685364 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q5164392 |
| concepts[3].display_name | Construct (python library) |
| concepts[4].id | https://openalex.org/C24756922 |
| concepts[4].level | 3 |
| concepts[4].score | 0.49619609117507935 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1757694 |
| concepts[4].display_name | Data quality |
| concepts[5].id | https://openalex.org/C48798503 |
| concepts[5].level | 2 |
| concepts[5].score | 0.44979146122932434 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q877546 |
| concepts[5].display_name | Reputation |
| concepts[6].id | https://openalex.org/C124101348 |
| concepts[6].level | 1 |
| concepts[6].score | 0.4479413628578186 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[6].display_name | Data mining |
| concepts[7].id | https://openalex.org/C2522767166 |
| concepts[7].level | 1 |
| concepts[7].score | 0.44149544835090637 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[7].display_name | Data science |
| concepts[8].id | https://openalex.org/C2779530757 |
| concepts[8].level | 2 |
| concepts[8].score | 0.43159377574920654 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1207505 |
| concepts[8].display_name | Quality (philosophy) |
| concepts[9].id | https://openalex.org/C149782125 |
| concepts[9].level | 1 |
| concepts[9].score | 0.41671645641326904 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q160039 |
| concepts[9].display_name | Econometrics |
| concepts[10].id | https://openalex.org/C133462117 |
| concepts[10].level | 2 |
| concepts[10].score | 0.41585949063301086 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q4929239 |
| concepts[10].display_name | Data collection |
| concepts[11].id | https://openalex.org/C105795698 |
| concepts[11].level | 1 |
| concepts[11].score | 0.3542923331260681 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[11].display_name | Statistics |
| concepts[12].id | https://openalex.org/C33923547 |
| concepts[12].level | 0 |
| concepts[12].score | 0.12862613797187805 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[12].display_name | Mathematics |
| concepts[13].id | https://openalex.org/C162853370 |
| concepts[13].level | 1 |
| concepts[13].score | 0.10104906558990479 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q39809 |
| concepts[13].display_name | Marketing |
| concepts[14].id | https://openalex.org/C104317684 |
| concepts[14].level | 2 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[14].display_name | Gene |
| concepts[15].id | https://openalex.org/C144133560 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q4830453 |
| concepts[15].display_name | Business |
| concepts[16].id | https://openalex.org/C144024400 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q21201 |
| concepts[16].display_name | Sociology |
| concepts[17].id | https://openalex.org/C36289849 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q34749 |
| concepts[17].display_name | Social science |
| concepts[18].id | https://openalex.org/C55493867 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[18].display_name | Biochemistry |
| concepts[19].id | https://openalex.org/C111472728 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q9471 |
| concepts[19].display_name | Epistemology |
| concepts[20].id | https://openalex.org/C138885662 |
| concepts[20].level | 0 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[20].display_name | Philosophy |
| concepts[21].id | https://openalex.org/C185592680 |
| concepts[21].level | 0 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[21].display_name | Chemistry |
| concepts[22].id | https://openalex.org/C111919701 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[22].display_name | Operating system |
| concepts[23].id | https://openalex.org/C176217482 |
| concepts[23].level | 2 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q860554 |
| concepts[23].display_name | Metric (unit) |
| concepts[24].id | https://openalex.org/C199360897 |
| concepts[24].level | 1 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[24].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.6245059967041016 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/dominance |
| keywords[1].score | 0.5758311748504639 |
| keywords[1].display_name | Dominance (genetics) |
| keywords[2].id | https://openalex.org/keywords/process |
| keywords[2].score | 0.5196658372879028 |
| keywords[2].display_name | Process (computing) |
| keywords[3].id | https://openalex.org/keywords/construct |
| keywords[3].score | 0.5069125294685364 |
| keywords[3].display_name | Construct (python library) |
| keywords[4].id | https://openalex.org/keywords/data-quality |
| keywords[4].score | 0.49619609117507935 |
| keywords[4].display_name | Data quality |
| keywords[5].id | https://openalex.org/keywords/reputation |
| keywords[5].score | 0.44979146122932434 |
| keywords[5].display_name | Reputation |
| keywords[6].id | https://openalex.org/keywords/data-mining |
| keywords[6].score | 0.4479413628578186 |
| keywords[6].display_name | Data mining |
| keywords[7].id | https://openalex.org/keywords/data-science |
| keywords[7].score | 0.44149544835090637 |
| keywords[7].display_name | Data science |
| keywords[8].id | https://openalex.org/keywords/quality |
| keywords[8].score | 0.43159377574920654 |
| keywords[8].display_name | Quality (philosophy) |
| keywords[9].id | https://openalex.org/keywords/econometrics |
| keywords[9].score | 0.41671645641326904 |
| keywords[9].display_name | Econometrics |
| keywords[10].id | https://openalex.org/keywords/data-collection |
| keywords[10].score | 0.41585949063301086 |
| keywords[10].display_name | Data collection |
| keywords[11].id | https://openalex.org/keywords/statistics |
| keywords[11].score | 0.3542923331260681 |
| keywords[11].display_name | Statistics |
| keywords[12].id | https://openalex.org/keywords/mathematics |
| keywords[12].score | 0.12862613797187805 |
| keywords[12].display_name | Mathematics |
| keywords[13].id | https://openalex.org/keywords/marketing |
| keywords[13].score | 0.10104906558990479 |
| keywords[13].display_name | Marketing |
| language | en |
| locations[0].id | doi:10.31235/osf.io/cy3wj |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | https://osf.io/cy3wj/download |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.31235/osf.io/cy3wj |
| locations[1].id | pmh:oai:share.osf.io:d4f15595-f939-4bb3-a2ab-5ec2fa9a52ad |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306400047 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | Arabixiv (OSF Preprints) |
| locations[1].source.host_organization | https://openalex.org/I2799848540 |
| locations[1].source.host_organization_name | Center for Open Science |
| locations[1].source.host_organization_lineage | https://openalex.org/I2799848540 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Preprint |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://osf.io/cy3wj |
| locations[2].id | pmh:oai:share.osf.io:E0054-C27-11C |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306400047 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | Arabixiv (OSF Preprints) |
| locations[2].source.host_organization | https://openalex.org/I2799848540 |
| locations[2].source.host_organization_name | Center for Open Science |
| locations[2].source.host_organization_lineage | https://openalex.org/I2799848540 |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | preprint |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | |
| locations[2].landing_page_url | http://doi.org/10.31235/OSF.IO/CY3WJ |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5068280022 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7035-0346 |
| authorships[0].author.display_name | Andreas Schneck |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I8204097 |
| authorships[0].affiliations[0].raw_affiliation_string | Ludwig Maximilian University of Munich, Department of Sociology, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I8204097 |
| authorships[0].institutions[0].ror | https://ror.org/05591te55 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I8204097 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | Ludwig-Maximilians-Universität München |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Andreas Schneck |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Ludwig Maximilian University of Munich, Department of Sociology, Germany |
| authorships[1].author.id | https://openalex.org/A5042566717 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9432-8696 |
| authorships[1].author.display_name | Wojtek Przepiorka |
| authorships[1].countries | NL |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I193662353 |
| authorships[1].affiliations[0].raw_affiliation_string | Utrecht University, Department of Sociology / ICS, Netherlands |
| authorships[1].institutions[0].id | https://openalex.org/I193662353 |
| authorships[1].institutions[0].ror | https://ror.org/04pp8hn57 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I193662353 |
| authorships[1].institutions[0].country_code | NL |
| authorships[1].institutions[0].display_name | Utrecht University |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Wojtek Przepiorka |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Utrecht University, Department of Sociology / ICS, Netherlands |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://osf.io/cy3wj/download |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2023-03-13T00:00:00 |
| display_name | Meta-dominance analysis – A tool for the assessment of the quality of digital behavioural data |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10609 |
| primary_topic.field.id | https://openalex.org/fields/33 |
| primary_topic.field.display_name | Social Sciences |
| primary_topic.score | 0.9904999732971191 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3312 |
| primary_topic.subfield.display_name | Sociology and Political Science |
| primary_topic.display_name | Digital Marketing and Social Media |
| related_works | https://openalex.org/W2358492783, https://openalex.org/W2604197785, https://openalex.org/W2105753174, https://openalex.org/W3122634986, https://openalex.org/W3152615410, https://openalex.org/W2898088173, https://openalex.org/W2891830216, https://openalex.org/W4226104445, https://openalex.org/W3167556887, https://openalex.org/W156784362 |
| cited_by_count | 0 |
| locations_count | 3 |
| best_oa_location.id | doi:10.31235/osf.io/cy3wj |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://osf.io/cy3wj/download |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.31235/osf.io/cy3wj |
| primary_location.id | doi:10.31235/osf.io/cy3wj |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | https://osf.io/cy3wj/download |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.31235/osf.io/cy3wj |
| publication_date | 2023-03-11 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3005044129, https://openalex.org/W2030032507, https://openalex.org/W1604910656, https://openalex.org/W6807461284, https://openalex.org/W3181093751, https://openalex.org/W2085175893, https://openalex.org/W6669497751, https://openalex.org/W3048172503, https://openalex.org/W6843057111, https://openalex.org/W2055202133, https://openalex.org/W2885312348, https://openalex.org/W6678868527, https://openalex.org/W6748504418, https://openalex.org/W4212935523, https://openalex.org/W2483961605, https://openalex.org/W3119547519, https://openalex.org/W4221033115, https://openalex.org/W6804731459, https://openalex.org/W6640380037, https://openalex.org/W2776961836, https://openalex.org/W2991191531, https://openalex.org/W6737937180, https://openalex.org/W6643224472, https://openalex.org/W4367676239, https://openalex.org/W3175886682, https://openalex.org/W2915451364, https://openalex.org/W2157931132, https://openalex.org/W2030464458, https://openalex.org/W4292202342, https://openalex.org/W2006546769, https://openalex.org/W6838123388, https://openalex.org/W2732477374, https://openalex.org/W3196504734, https://openalex.org/W1730782591, https://openalex.org/W6722226382, https://openalex.org/W2762364541, https://openalex.org/W3163506346, https://openalex.org/W2067141886, https://openalex.org/W1572903765, https://openalex.org/W2517839752, https://openalex.org/W4285024927, https://openalex.org/W4253455620, https://openalex.org/W2057525748, https://openalex.org/W2162949058, https://openalex.org/W3215367316, https://openalex.org/W1594616337, https://openalex.org/W4241063988, https://openalex.org/W4361201026, https://openalex.org/W3110243129, https://openalex.org/W4280542232, https://openalex.org/W4361201095, https://openalex.org/W2616446878, https://openalex.org/W4390260306, https://openalex.org/W4280582797, https://openalex.org/W1971916086, https://openalex.org/W204900244, https://openalex.org/W3157514924, https://openalex.org/W4210786371, https://openalex.org/W2126930838, https://openalex.org/W1941783251, https://openalex.org/W1845748792, https://openalex.org/W4365516066, https://openalex.org/W4294553991, https://openalex.org/W4307475647, https://openalex.org/W4238599281, https://openalex.org/W3122799521, https://openalex.org/W4282832862, https://openalex.org/W4312451159, https://openalex.org/W2102581597, https://openalex.org/W2890593043 |
| referenced_works_count | 70 |
| abstract_inverted_index.a | 2, 46 |
| abstract_inverted_index.25 | 33 |
| abstract_inverted_index.We | 0, 22 |
| abstract_inverted_index.at | 123 |
| abstract_inverted_index.be | 80, 140 |
| abstract_inverted_index.in | 16, 32, 40, 148 |
| abstract_inverted_index.of | 11, 14, 30, 35, 65, 74, 90, 114, 126, 146, 151, 156 |
| abstract_inverted_index.on | 37 |
| abstract_inverted_index.or | 107 |
| abstract_inverted_index.to | 26, 60, 82, 103, 142 |
| abstract_inverted_index.we | 56 |
| abstract_inverted_index.109 | 54 |
| abstract_inverted_index.346 | 49 |
| abstract_inverted_index.85% | 73 |
| abstract_inverted_index.Our | 69 |
| abstract_inverted_index.and | 97 |
| abstract_inverted_index.can | 79, 139 |
| abstract_inverted_index.for | 8 |
| abstract_inverted_index.map | 27 |
| abstract_inverted_index.may | 132 |
| abstract_inverted_index.our | 24 |
| abstract_inverted_index.the | 9, 62, 83, 88, 104, 115, 127, 154 |
| abstract_inverted_index.use | 23 |
| abstract_inverted_index.yet | 4 |
| abstract_inverted_index.This | 120, 137 |
| abstract_inverted_index.bias | 109 |
| abstract_inverted_index.data | 92, 134, 158 |
| abstract_inverted_index.from | 53, 159 |
| abstract_inverted_index.size | 77, 118 |
| abstract_inverted_index.that | 72 |
| abstract_inverted_index.used | 141 |
| abstract_inverted_index.with | 18 |
| abstract_inverted_index.Error | 100 |
| abstract_inverted_index.Using | 45 |
| abstract_inverted_index.apply | 57 |
| abstract_inverted_index.data. | 21 |
| abstract_inverted_index.error | 15, 31, 67, 147 |
| abstract_inverted_index.mode, | 94 |
| abstract_inverted_index.most. | 136 |
| abstract_inverted_index.parts | 113 |
| abstract_inverted_index.sizes | 51 |
| abstract_inverted_index.small | 112 |
| abstract_inverted_index.which | 86, 124 |
| abstract_inverted_index.years | 34 |
| abstract_inverted_index.affect | 133 |
| abstract_inverted_index.beyond | 153 |
| abstract_inverted_index.choice | 89 |
| abstract_inverted_index.effect | 50, 76, 117 |
| abstract_inverted_index.market | 43 |
| abstract_inverted_index.online | 42, 160 |
| abstract_inverted_index.simple | 3 |
| abstract_inverted_index.stages | 125 |
| abstract_inverted_index.capture | 110 |
| abstract_inverted_index.digital | 19 |
| abstract_inverted_index.effects | 39 |
| abstract_inverted_index.process | 106, 129 |
| abstract_inverted_index.propose | 1 |
| abstract_inverted_index.quality | 135 |
| abstract_inverted_index.results | 70 |
| abstract_inverted_index.reveals | 122 |
| abstract_inverted_index.sources | 13, 29, 145 |
| abstract_inverted_index.strands | 150 |
| abstract_inverted_index.analysis | 59 |
| abstract_inverted_index.approach | 121, 138 |
| abstract_inverted_index.identify | 143 |
| abstract_inverted_index.indicate | 71 |
| abstract_inverted_index.process, | 85 |
| abstract_inverted_index.quantify | 61 |
| abstract_inverted_index.relative | 63 |
| abstract_inverted_index.research | 17, 36, 128, 152 |
| abstract_inverted_index.sampling | 105 |
| abstract_inverted_index.variable | 98 |
| abstract_inverted_index.articles, | 55 |
| abstract_inverted_index.comprises | 87 |
| abstract_inverted_index.construct | 95 |
| abstract_inverted_index.decisions | 131 |
| abstract_inverted_index.different | 12, 66 |
| abstract_inverted_index.explained | 75, 116 |
| abstract_inverted_index.extracted | 52 |
| abstract_inverted_index.framework | 7, 25 |
| abstract_inverted_index.platform, | 91 |
| abstract_inverted_index.potential | 28, 144 |
| abstract_inverted_index.attributed | 81 |
| abstract_inverted_index.collection | 93 |
| abstract_inverted_index.components | 101 |
| abstract_inverted_index.comprising | 48 |
| abstract_inverted_index.conceptual | 6 |
| abstract_inverted_index.importance | 64 |
| abstract_inverted_index.literature | 155 |
| abstract_inverted_index.platforms. | 44, 161 |
| abstract_inverted_index.relatively | 111 |
| abstract_inverted_index.reputation | 38 |
| abstract_inverted_index.researcher | 130 |
| abstract_inverted_index.behavioural | 20, 157 |
| abstract_inverted_index.components. | 68 |
| abstract_inverted_index.established | 149 |
| abstract_inverted_index.measurement | 84 |
| abstract_inverted_index.publication | 108 |
| abstract_inverted_index.attributable | 102 |
| abstract_inverted_index.meta-dataset | 47 |
| abstract_inverted_index.peer-to-peer | 41 |
| abstract_inverted_index.comprehensive | 5 |
| abstract_inverted_index.heterogeneity | 78 |
| abstract_inverted_index.heterogeneity. | 119 |
| abstract_inverted_index.identification | 10 |
| abstract_inverted_index.meta-dominance | 58 |
| abstract_inverted_index.transformation. | 99 |
| abstract_inverted_index.operationalisation | 96 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5042566717 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I193662353 |
| citation_normalized_percentile.value | 0.0425742 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |