standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.| relation to other work | claim_relations | how this paper stands to another: agrees, contradicts, extends, qualifies |
| claim type | claim_type | the shape of the claim: existence, mechanism, method, critique, prediction, null |
| concept edge | concept_edges | an asserted relation between two concepts, with the sentence asserting it |
| concept | concepts | an idea the paper works with, quoted where the paper uses it |
| content tag | content_tags | a finding, definition, quantity, statistic or variable named in the paper |
| limitation | limitations | what the paper says its evidence cannot support |
| mechanism | mechanisms | how the reported effect is said to come about |
| method | method | how the paper produced its evidence |
| phenomenon | phenomenon | the effect or regularity under study |
| sense | senses | a distinct use of a term, quoted where the paper fixes it |
| transfer | transfers | a method or concept carried in from another field |
Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; none of 1 relation here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.
This record holds no controls. A layer is empty when the tagger recorded nothing in it — which is not the same as the paper having nothing to record.
| facet | tag | field | conf. | whose words |
|---|---|---|---|---|
| claim_type | method Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_type | the paper's words | |
| phenomenon | computational analysis of large visual cultural datasets Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | phenomenon | the paper's words | |
| method | review Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: review | method | the paper's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[0] | the tagger's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[1] | the tagger's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[2] | the tagger's words | |
| limitations | The chosen examples are deliberately biased toward the humanities rather than being a neutral survey of data science. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: the choice of examples, declared as a specification rather than confessed: SINCE MY ARTICLE IS WRITTEN FOR HUMANITIES AUDIENCE, IT IS ON PURPOSE BIASED - MY EXAMPLES COME FROM HUMANITIES AS OPPOSED TO ECONOMICS OR SOCIOLOGY | limitations[0] | the tagger's words | |
| limitations | A two-feature comparison of images ignores every other kind of difference between the works. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: the two-feature comparison: THIS EXAMPLE DISREGARDS ALL OTHER TYPES OF DIFFERENCE: SUBJECT MATTER, COMPOSITION, COLOR PALETTE, BRUSHWORK | limitations[1] | the tagger's words | |
| limitations | Even with many features there is no guarantee that the extracted features capture difference as humans perceive it. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any feature-based measure of similarity: EVEN IF WE USE MANY DIFFERENT FEATURES, WE CANNOT BE SURE THAT WE HAVE CAPTURED THE RIGHT INFORMATION TO QUANTIFY DIFFERENCE AS WE HUMANS SEE IT | limitations[2] | the tagger's words | |
| limitations | Dimension-reduced plots are hard to interpret because the axes no longer correspond to single features. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any reading of the reduced plots: IT CAN BE QUITE CHALLENGING TO INTERPRET THE MEANING OF EACH DIMENSION once dimension reduction has been applied | limitations[3] | the tagger's words | |
| limitations | Computational analysis has a precondition that the article says cannot be changed: the phenomenon must first be made into a finite set of objects and a finite set of features. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any computational result about a cultural phenomenon: the article states the phenomenon must first be represented as a finite set of individual objects and a finite set of their features | limitations[4] | 1.0 | the tagger's words |
| limitations | The comparison is confined to the chosen features, and everything else is set aside — which the article names as a limitation and then reframes as an advantage. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: a similarity computed over selected image features: the article states it disregards subject matter, composition, colour palette and brushwork, and treats that as both a limitation and an advantage | limitations[5] | 1.0 | the tagger's words |
| limitations | The demographic and facial variables in the featured project were produced by paid crowdworkers and a commercial face-analysis service. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: the age, gender and emotion variables in this project: the age and gender estimates came from Amazon Mechanical Turk and the facial features from a commercial recognition service | limitations[6] | 1.0 | the tagger's words |
| limitations | THE PAPER STATES THAT THE CENTRAL RISK CANNOT BE RETIRED BY ADDING MORE MEASUREMENT: 'even if we use many different features, we cannot be sure that we have captured the right information to quantify difference as we humans see it'. It then declines the obvious repair - 'producing a single correct map should not be our main goal' - so the limitation is accepted as a condition of the method rather than treated as a defect to fix. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | limitations[7] | 0.95 | the tagger's words |
| transfers | the core analytic concepts of data science (objects, features, feature space, distance, dimension reduction) are imported wholesale as a framework for art-historical and humanistic study Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | transfers[0] | the tagger's words | |
| transfers | the term "features" is adopted into digital art history in place of the sciences' "variable", and stretched to cover existing metadata as well as computed attributes Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | transfers[1] | the tagger's words | |
| concepts | data Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: data | concepts[0] | the paper's words | |
| concepts | phenomenon Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: phenomenon | concepts[1] | the paper's words | |
| concepts | features Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: features | concepts[2] | the paper's words | |
| concepts | objects Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: objects | concepts[3] | 0.85 | the paper's words |
| concepts | feature space Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: feature space | concepts[4] | 0.95 | the paper's words |
| senses | phenomenon - AS INDEPENDENT: something that objectively exists regardless of how we study it, irrespective of which objects and properties we choose Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[0] | 1.0 | the tagger's words |
| senses | phenomenon - AS CONSTITUTED: equal to the set of objects and properties used to study it, so that it is made by its representations and the conversations about it Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[1] | 1.0 | the tagger's words |
| senses | feature selection - stated as BOTH a limitation and an advantage, because isolating features is what makes comparison on chosen dimensions possible at all Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[2] | 1.0 | the tagger's words |
| senses | variable - used in opposite ways by the two fields the paper is joining: one isolated variable for understanding in statistics, many features for automation in data science Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[3] | 0.95 | the tagger's words |
| claim_relations | extends → Franco Moretti, 'Conjectures on World Literature' (2000) Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[0] | the tagger's words | |
| concept_edges | features —operationalised-as→ feature space Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. strength of the relation: 0.9 · note: The second constituting move, stated as a conceptualisation rather than a discovery: 'we will CONCEPTUALIZE our data table as a geometric space…' Similarity becomes distance because the table is read as a space.
Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span says each feature BECOMES A DIMENSION of the feature space; operationalised-as is loose - part-of is what is stated. also in: features · feature space | concept_edges[1] | 0.95 | the tagger's words |
| content_tags | principal component analysis Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: principal component analysis | content_tags.statistics[0] | the tagger's words | |
| content_tags | multidimensional scaling Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: multidimensional scaling | content_tags.statistics[1] | the tagger's words | |
| content_tags | mean Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: mean | content_tags.statistics[2] | the tagger's words | |
| content_tags | Classical statistics and data science use variables in opposite ways: statistics isolates one independent and one dependent variable in order to explain a phenomenon, while data science piles up many features in order to automate a cognitive task. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[0] | the tagger's words | |
| content_tags | The feature-space concept lets the humanities' oldest method, comparison, be scaled up to very large cultural datasets. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[1] | the tagger's words | |
| content_tags | Representing images in a feature space equates visual difference with distance in that space. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[2] | the tagger's words | |
| content_tags | Automatic classification, probably the most common data-science application, is in the author's view the least interesting one for the humanities. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[3] | the tagger's words | |
| content_tags | Dimension reduction makes the shape of a high-dimensional space visible but at the cost of interpretability, because each plotted axis stands for a combination of features rather than one feature. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[4] | the tagger's words | |
| content_tags | On average brightness and saturation, van Gogh's Paris paintings vary more than his Arles paintings. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[5] | the tagger's words | |
| content_tags | The images popularly associated with Impressionism make up only a smaller part of the artworks these artists created. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[6] | the tagger's words | |
| content_tags | The Instagram tags show little interaction between two types: one group of users used generic tags, another tagged local, specific events. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[7] | the tagger's words | |
| content_tags | data science Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: data science | content_tags.definitions[0] | the tagger's words | |
| content_tags | features Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: features | content_tags.definitions[1] | the tagger's words | |
| content_tags | data Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: data | content_tags.definitions[2] | the tagger's words | |
| content_tags | feature space Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: feature space | content_tags.definitions[3] | the tagger's words | |
| content_tags | dimension reduction Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: dimension reduction | content_tags.definitions[4] | the tagger's words | |
| content_tags | semantic gap Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: semantic gap | content_tags.definitions[5] | the tagger's words | |
| content_tags | coding Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: coding | content_tags.definitions[6] | the tagger's words | |
| content_tags | supervised learning Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: supervised learning | content_tags.definitions[7] | the tagger's words | |
| content_tags | average color saturation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: average color saturation | content_tags.variables[2] | the tagger's words | |
| content_tags | average hue Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: average hue | content_tags.variables[3] | the tagger's words | |
| content_tags | 10.5 million — number of publicly visible Instagram images collected across New York City over five months in 2014 for the On Broadway project Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[0] | the tagger's words | |
| content_tags | 6,165 / 13,208 / 21,465 (5845 unique) — Instagram users, images and tags (and unique tags) collected in central Kyiv over 17–22 February 2014 Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[1] | the tagger's words | |
| content_tags | 200 — number of visual features the lab extracted from each Impressionist painting image before reducing dimensions Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[2] | the tagger's words | |
| content_tags | approximately 6000 — size of the French Impressionist painting dataset visualised with PCA Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[3] | the tagger's words | |
| content_tags | 3200 — number of Instagram self-portraits assembled and made filterable in the Selfiecity interface Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[4] | the tagger's words | |
| content_tags | 50,000 — size of the random Instagram image sample taken from each of Bangkok and Tokyo for the Phototrails comparison Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[5] | the tagger's words |
Tags that could not be placed in the text:
What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.