A Network Analysis of Figurative Topic Classification: The Case Study of Timon of Athens

Gilad Gutman · Digital Humanities Quarterly 18(3) · 2024 · digital-humanities · record gutman2024-figurative-topics
tag layer · index · concepts · authors · עברית

Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. Claim type is method rather than critique even though sections 3.1 and 4.1 argue against topic modeling and against particular readings of the play: the article's own framing is that it offers a computational method (topic classification plus network analysis). method is recorded as system-or-tool-building because the concrete output is a hand-built dataset (1,388 classified figurative instances from four tragedies), a fine-tuned DistilBERT topic classifier, and Gephi networks; there is no separate slot for the literary-critical close reading that occupies section 4, which is a humanistic interpretation rather than any of the listed methods. Replication status is untested: the article reports no replication of its own or of others' results, and the classifier's accuracy (72.94%) and F-score (71.12) are single self-reported figures. Some claim relations are drawn from footnote-bearing sentences, but only the sentence text itself is quoted. The Rhody and Finkelstein relations are typed contradicts because the paper disputes the adequacy of their positions rather than merely citing them; a relation to I. A. Richards and to Blumenberg is present in section 2 but was left out because the sentences that name them describe their positions rather than explicitly stating this paper's relation to them. 2026-08-14, 2026-08-15 and 2026-08-17 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at merge time; concept terms verified present; every edge endpoint an existing node.

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Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 9 concept tags on this paper, 4 are grounded in a quoted sentence.

figurative language topic classification network analysis close reading natural language processing tenor vehicle word intrusion topic modeling THE DIFFICULTY IS ATTRIBUTED TO THE STRUCTURE OF THE OBJECT, NOT TO THE METHOD: analysing figurative RATHER THAN LITERAL language POSES CERTAIN DIFFICULTIES DUE TO THE VERY STRUCTURE OF FIGURATIVE EXPRESSIONS - so the obstacle is located in what is being measured before any tool is named A PROHIBITION IS SHOWN VIOLATING ITSELF IN ITS OWN WORDING: the Areopagite judges CONDEMN the use of figurative language AS DECEPTIVE, and THEY THEMSELVES USE A METAPHOR OF A CARPENTER IN THEIR CONDEMNATION. The rule against a class of language is stated in that class of language AND THE SHARPER POINT IS THAT THE HOMONYMY DOES THE WORK, NOT THE METAPHOR: the influence is NOT ONLY evident through the carpenter - RATHER IT IS THE MORE SUBTLE HOMONYM SENSES OF THE WORDS UPRIGHT AND RULE THAT TRULY REVEAL THE PERVASIVE POWER OF THE FIGURATIVE. Two words carrying two senses each, unnoticed by the speakers, are what the argument turns on A CLASS OF METAPHOR IS DEFINED BY WHAT WOULD BE IMPOSSIBLE WITHOUT IT: the word is catalogued as part of the ORIENTATIONAL class of metaphors, which RELY ON OUR MOST BASIC SENSE OF SPACE AND PHYSICAL CONCEPTS, so much so that WITHOUT WHICH WE COULD NOT FUNCTION IN THE WORLD - COULD NOT REASON OR COMMUNICATE. The category's members are identified by the cost of their absence A METHOD'S OUTPUT AND THE CONCEPT IT IS MEANT TO MEASURE ARE REPORTED NOT TO CORRESPOND: after comparing a computational reading with a thematic one, the conclusion quoted is WE CANNOT FIND A CLEAR OR CONSTANT RELATIONSHIP BETWEEN AN LDA-TOPIC AND A THEME. The instrument produces something, and it is not the thing the word names THE METHOD IS SAID TO WORK ON ONE TEXT TYPE AND FAIL ON ANOTHER, AND THE REASON GIVEN IS CONTEXT-EXCLUSIVITY OF VOCABULARY: topic modelling applied to poetry DOES NOT EXTRACT CLEAR AND DEFINED THEMES AS IT DOES WHEN APPLIED TO SCIENTIFIC TEXTS, because IN SCIENTIFIC TEXTS THERE ARE WORDS THAT ARE USED EXCLUSIVELY IN VERY SPECIFIC CONTEXTS - and THE LINGUISTIC USES IN POETRY WORK IN THE EXACT OPPOSITE WAY. The property that makes the method work is a property of the vocabulary, not of the algorithm THE NAMING STEP IS IDENTIFIED AS THE MANUAL AND SUBJECTIVE ONE: in topic modelling, DISCERNING THE TITLES of the groups of words REMAINS A MANUAL TASK THAT REQUIRES ACTIVE AND OFTEN SUBJECTIVE INTERPRETATION. The algorithm delivers groups; a person supplies the words that say what the groups are A NAMED DEFECT OF AUTOMATIC GROUPING IS CITED, AND IT IS A DISAGREEMENT BETWEEN MACHINE AND HUMAN CATEGORIES: a list of words treated as one topic MAY INCLUDE WORDS THAT HUMAN INTERPRETERS RECOGNIZE AS BELONGING TO DISTINCT TOPICS - a problem with its own name, WORD INTRUSION. The defect is defined by the mismatch, and the mismatch is what the name records THE RIGHT RELIABILITY MEASURE IS NAMED, ITS PURPOSE STATED, AND IT IS EXPLICITLY NOT DONE, WITH THE REASON: given the SAME set of topics and instances, TWO INTERPRETERS MIGHT STILL CHOOSE DIFFERENT TOPICS for a word - INTER-ANNOTATORS AGREEMENT is the method by which that agreement can be measured, PROVIDING A STATUS OF CONSENSUS, and the procedure REQUIRES CERTAIN RESOURCES AND HENCE WILL BE IMPLEMENTED later. The measure that would qualify the result is named and deferred in the same breath THE IMPROVEMENTS PROPOSED ARE PROPERTIES OF THE SETUP RATHER THAN OF THE ANALYSIS: the recommendations begin with REDUCING THE NUMBER OF TOPICS AND ENLARGING THE DATASET, which will allow the algorithm to have MORE DATA AND LESS AMBIGUITY REGARDING TOPICS - so the ambiguity is treated as a quantity the design can lower rather than a feature of the object metaphor literary criticism system-or-tool-building

Legend

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
control	`controls`	an experiment run to eliminate a rival explanation
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

The paper

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at its publisher. The reading view exists for the papers whose licence permits it.

Every tag on this page

claim_relations 4 · claim_type 1 · concept_edges 1 · concepts 4 · content_tags 4 · controls 1 · limitations 8 · mechanisms 10 · method 1 · phenomenon 1 · senses 3 · transfers 1

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.

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	figurative language as a network of topics 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	system-or-tool-building Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: system-or-tool-building	`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. about this quote: The span contains the author's typo "in this articles" for "in this article". Not extraction damage - it is in the published DHQ text - and quoted verbatim. also in: THE DIFFICULTY IS ATTRIBUTED TO THE STRUCTURE OF THE OBJECT, NOT TO THE METHOD: analysing figurative RATHER THAN LITERAL language POSES CERTAIN DIFFICULTIES DUE TO THE VERY STRUCTURE OF FIGURATIVE EXPRESSIONS - so the obstacle is located in what is being measured before any tool is named	`mechanisms[0]`	0.95	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. also in: A PROHIBITION IS SHOWN VIOLATING ITSELF IN ITS OWN WORDING: the Areopagite judges CONDEMN the use of figurative language AS DECEPTIVE, and THEY THEMSELVES USE A METAPHOR OF A CARPENTER IN THEIR CONDEMNATION. The rule against a class of language is stated in that class of language	`mechanisms[1]`	0.95	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. also in: AND THE SHARPER POINT IS THAT THE HOMONYMY DOES THE WORK, NOT THE METAPHOR: the influence is NOT ONLY evident through the carpenter - RATHER IT IS THE MORE SUBTLE HOMONYM SENSES OF THE WORDS UPRIGHT AND RULE THAT TRULY REVEAL THE PERVASIVE POWER OF THE FIGURATIVE. Two words carrying two senses each, unnoticed by the speakers, are what the argument turns on	`mechanisms[2]`	0.95	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. also in: A CLASS OF METAPHOR IS DEFINED BY WHAT WOULD BE IMPOSSIBLE WITHOUT IT: the word is catalogued as part of the ORIENTATIONAL class of metaphors, which RELY ON OUR MOST BASIC SENSE OF SPACE AND PHYSICAL CONCEPTS, so much so that WITHOUT WHICH WE COULD NOT FUNCTION IN THE WORLD - COULD NOT REASON OR COMMUNICATE. The category's members are identified by the cost of their absence	`mechanisms[3]`	0.95	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. also in: A METHOD'S OUTPUT AND THE CONCEPT IT IS MEANT TO MEASURE ARE REPORTED NOT TO CORRESPOND: after comparing a computational reading with a thematic one, the conclusion quoted is WE CANNOT FIND A CLEAR OR CONSTANT RELATIONSHIP BETWEEN AN LDA-TOPIC AND A THEME. The instrument produces something, and it is not the thing the word names	`mechanisms[4]`	0.85	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. also in: THE METHOD IS SAID TO WORK ON ONE TEXT TYPE AND FAIL ON ANOTHER, AND THE REASON GIVEN IS CONTEXT-EXCLUSIVITY OF VOCABULARY: topic modelling applied to poetry DOES NOT EXTRACT CLEAR AND DEFINED THEMES AS IT DOES WHEN APPLIED TO SCIENTIFIC TEXTS, because IN SCIENTIFIC TEXTS THERE ARE WORDS THAT ARE USED EXCLUSIVELY IN VERY SPECIFIC CONTEXTS - and THE LINGUISTIC USES IN POETRY WORK IN THE EXACT OPPOSITE WAY. The property that makes the method work is a property of the vocabulary, not of the algorithm	`mechanisms[5]`	0.95	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. also in: THE NAMING STEP IS IDENTIFIED AS THE MANUAL AND SUBJECTIVE ONE: in topic modelling, DISCERNING THE TITLES of the groups of words REMAINS A MANUAL TASK THAT REQUIRES ACTIVE AND OFTEN SUBJECTIVE INTERPRETATION. The algorithm delivers groups; a person supplies the words that say what the groups are	`mechanisms[6]`	0.95	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. also in: A NAMED DEFECT OF AUTOMATIC GROUPING IS CITED, AND IT IS A DISAGREEMENT BETWEEN MACHINE AND HUMAN CATEGORIES: a list of words treated as one topic MAY INCLUDE WORDS THAT HUMAN INTERPRETERS RECOGNIZE AS BELONGING TO DISTINCT TOPICS - a problem with its own name, WORD INTRUSION. The defect is defined by the mismatch, and the mismatch is what the name records	`mechanisms[7]`	0.85	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. about this quote: EXTENDED to the full stop, and the span contains the author's typo "Tthis procedure" with a doubled T. Not extraction damage; it is in the published text. The extension matters because "will be implemented in a future study" is what dates the deferral - the reliability measure is named, its purpose stated, and its absence scheduled, all in one passage. also in: THE RIGHT RELIABILITY MEASURE IS NAMED, ITS PURPOSE STATED, AND IT IS EXPLICITLY NOT DONE, WITH THE REASON: given the SAME set of topics and instances, TWO INTERPRETERS MIGHT STILL CHOOSE DIFFERENT TOPICS for a word - INTER-ANNOTATORS AGREEMENT is the method by which that agreement can be measured, PROVIDING A STATUS OF CONSENSUS, and the procedure REQUIRES CERTAIN RESOURCES AND HENCE WILL BE IMPLEMENTED later. The measure that would qualify the result is named and deferred in the same breath	`mechanisms[8]`	0.85	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. also in: THE IMPROVEMENTS PROPOSED ARE PROPERTIES OF THE SETUP RATHER THAN OF THE ANALYSIS: the recommendations begin with REDUCING THE NUMBER OF TOPICS AND ENLARGING THE DATASET, which will allow the algorithm to have MORE DATA AND LESS AMBIGUITY REGARDING TOPICS - so the ambiguity is treated as a quantity the design can lower rather than a feature of the object	`mechanisms[9]`	0.95	the tagger's words
limitations	Figurative instances still have to be extracted from the plays by hand; no automatic procedure isolates them. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[0]`		the tagger's words
limitations	The trained topic classifier reaches only 72.94% accuracy and is presented as needing further fine-tuning. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[1]`		the tagger's words
limitations	The number of topics and their titles are partly subjective researcher decisions. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[2]`		the tagger's words
limitations	Inter-annotator agreement on the manual classification was not measured; it is deferred to a future study. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[3]`		the tagger's words
limitations	The automatic classification is described as still needing improvement (fewer topics, larger dataset, other language models). Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[4]`		the tagger's words
limitations	Extending the network to a directed one (tenor to vehicle) is blocked by cases where the tenor is only implied. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[5]`		the tagger's words
limitations	Low centrality in the network does not establish that a topic is unimportant, so the method cannot by itself dismiss an interpretation. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`limitations[6]`		the tagger's words
limitations	A modelled topic may group words that human readers see as belonging to different topics. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any topic produced by the modelling step here: the authors note that discerning the titles is a manual task requiring subjective interpretation, and that a topic's word list may include words human interpreters recognise as belonging to distinct topics, a problem named word intrusion	`limitations[7]`	1.0	the tagger's words
transfers	the computational apparatus of natural language processing - tokenisation, distributional similarity, network construction - applied to figurative language in a corpus of liturgical poetry Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`transfers[0]`	0.85	the tagger's words
controls	randomly splitting the dataset into a 66% training set and a 33% test set Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: that the classifier's apparent accuracy comes from memorising the data it was trained on · outcome: held	`controls[0]`	0.85	the tagger's words
concepts	tenor Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: tenor	`concepts[5]`		the paper's words
concepts	vehicle Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: vehicle	`concepts[6]`		the paper's words
concepts	word intrusion Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: word intrusion	`concepts[7]`		the paper's words
concepts	topic modeling Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: topic modeling	`concepts[8]`		the paper's words
senses	a topic title - SUPPLIED BY A READER, AND DEFENDED AS SUCH: the paper states that titling the groups of words is a manual task requiring active and often subjective interpretation, and then argues that this subjectivity does not undermine the method but shows that various classifications are possible depending on the researcher's orientation - a position, not an oversight 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	tenor and vehicle - GLOSSED IN ONE PARENTHESIS: the underlying subject and the transported meaning, taken from I. A. Richards; the paper states the connection between them is not a necessary one but rests on substitution, which is why the network it builds is undirected 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	word intrusion - THE NAMED FAILURE MODE, ATTRIBUTED: a list of words the model calls one topic may contain words that human interpreters place in distinct topics, which the paper attributes to Chang et al. rather than presenting as its own discovery 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
claim_relations	builds-on → Moretti's notion of "operationalization" (Moretti 2013), after Bridgman's The Logic of Modern Physics 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
claim_relations	builds-on → Lakoff and Johnson (2003), Metaphors We Live By — metaphorical entailment Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`claim_relations[1]`		the tagger's words
claim_relations	contradicts → Rhody (2012), topic modeling of figurative language Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. differs in: BYPASSING AGAINST SOLVING. 'Quotation withheld' The method is granted as usable; what is contested is whether it addresses the problem.	`claim_relations[2]`		the tagger's words
claim_relations	contradicts → Finkelstein (2020), "Amicitia and beneficia in Timon of Athens" Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.	`claim_relations[3]`		the tagger's words
concept_edges	tenor —distinct-from→ vehicle Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. differs in: which side of the metaphor each names: the underlying subject, or the transported meaning · strength of the relation: 1 also in: tenor · vehicle	`concept_edges[0]`		the tagger's words
content_tags	Figurative language is harder to analyse than literal language because of the very structure of figurative expressions. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.	`content_tags.findings[0]`		the tagger's words
content_tags	The method combines two techniques rather than one: topic classification to label the figures, network analysis to relate them. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.	`content_tags.findings[1]`		the tagger's words
content_tags	Figurative analysis is not confined to literary criticism; it matters wherever the object of study is text. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.	`content_tags.findings[2]`		the tagger's words
content_tags	The method is judged by whether it can support a close reading, not only by whether it runs. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.	`content_tags.findings[3]`		the tagger's words

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