Η παρουσίαση φορτώνεται. Παρακαλείστε να περιμένετε

Η παρουσίαση φορτώνεται. Παρακαλείστε να περιμένετε

Semantic Drift between the Testaments Using Collocation Analysis to Find Theological Significance Matt Munson.

Παρόμοιες παρουσιάσεις


Παρουσίαση με θέμα: "Semantic Drift between the Testaments Using Collocation Analysis to Find Theological Significance Matt Munson."— Μεταγράφημα παρουσίασης:

1 Semantic Drift between the Testaments Using Collocation Analysis to Find Theological Significance Matt Munson

2 Theological Background Use of Old Testament in the New – Similarities – Differences – Relative Meaning But re-use goes beyond quotations – What about the similarities, differences, and relative meanings of individual words – Can we detect theological significance even here?

3 Linguistic Background - Collocations Firth, “You shall know a word by the company it keeps!” Harris, “If we consider words or morphemes A and B to be more different in meaning than A and C, then we will often find that the distributions of A and B are more different than the distributions of A and C. In other words, difference of meaning correlates with difference of distribution.”

4 My Hypothesis Linguistic: – By comparing the collocation word fields of the same target word in the Septuagint and the New Testament, one can detect which words have changed in meaning the most from one Testament to the other. Theological: – Further investigation of how the collocation fields have changed will lead to insights concerning the theological changes from the LXX to the NT.

5 My Method Lemmatized Greek Texts Collocation span of 4L and 4R Co-occurrence counts Log likelihood significance Cosine similarity of log likelihood tables Comparison of log likelihood and cosine similarity tables for each lemma

6 Lemmatized Greek Texts Highly Inflected Language – Nouns: 8 distinct forms – Verbs: would you believe over 200 forms? Not lemmatizing would make each of these forms appear to the computer to be a unique word Could be interesting but not enough data to overcome atomization

7 Collocation Span of 4L and 4R Experiments have shown this to be the most effective span L4L3L2L1LemmaR1R2R3R4 ἐνἀρχήποιέωὁθεόςὁοὐρανόςκαίὁ ὁἄβυσσοςκαίπνεῦμαθεόςἐπιφέρωἐπάνωὁὕδωρ

8 Co-occurrence Counts Simple counts of how often a collocate occurs in the given span of the target Example: – 'ἔντιμος' 1, 'ἀπόδεκτος' 1, προευαγγελίζομαι' 1, 'γεννάω' 11, 'κιθάρα' 1, 'ὀλίγος' 1, 'πρό' 4, 'ἀνοίγω' 2, 'ἐπιποθέω' 2, 'ἀστεῖος' 1, 'ἔμπροσθεν' 6, 'μετάνοια' 7, 'ἐκπορεύομαι' 2, 'ὅτε' 9, 'οἰκτιρμός' 2, 'Ῥαιφάν' 1, 'ὅτι' 122…

9 Log Likelihood Significance I “Significant collocation is regular collocation between two items, such that they co-occur more often than their respective frequencies.” (Léon, 14) “log-likelihood measures the strength of association between words by comparing the occurrences of words respectively and their occurrences together.” also appropriate for sparse data This measures syntagmatic relationships More Information: TU Darmstadt LinguisticsWebTU Darmstadt LinguisticsWeb

10 Log Likelihood Significance II Tables θεός1317Lemma ἔντιμος10, ἀπόδεκτος10, προευαγγελίζομαι10, γεννάω110, κιθάρα10, ὀλίγος10, πρό40, ἀνοίγω20, ἐπιποθέω20, ἀστεῖος10, ἔμπροσθεν60, μετάνοια70, ἐκπορεύομαι20, ὅτε90, οἰκτιρμός20, Ῥαιφάν10, ὅτι1220,030284

11 Cosine Similarity of Log-Likelihood Tables Cosine similarity is often used to measure the similarity between word frequency lists I used it to compare log likelihood tables, which have the same form as frequency lists I compared all the tables in the LXX to each other and all in the NT to each other I also compared the same lemmata in each Testament to each other This measures paradigmatic relationships

12 Cosine Similarity Results Within each Testament 'θεός'Lemma 'εἰμί'0, 'πᾶς'0, 'καί'0, 'ἐν'0, 'πιστεύω'0, 'οὕτω'0, 'περί'0, 'γράφω'0, 'ὄνομα'0, 'λαλέω'0, 'χάρις'0, 'χείρ'0, 'πόλις'0, 'λαμβάνω'0, 'οὗτος'0, 'λόγος'0, Between the Testaments καί0, οὔτε0, ἐν0, πᾶς0, ὁ0, ὅς0, οὗτος0, αὐτός0, σύ0, ἐγώ0, εἰς0, εἰμί0, Σαλμών0, ἐπί0, ὅτι0, γάρ0, ἀπό0,

13 Compare Log Likelihood Tables This will show which collocates occur more significantly with the lemma in the LXX and the NT Positive means more significantly in the LXX, negative in the NT Syntagmatic comparison Will show change in usage but not change in meaning directly

14 Compare Log Likelihood Tables - Results 'θεόςEnglishLemma κύριοςLord75, ἐγώI21, σύYou20, λατρεύωTo serve9, εὐλογητόςBlessed9, ὅτιThat, which8, υἱόςSon8, ἸσραήλIsrael6, εὐλογέωTo bless6, ἕτεροςother5, … εἰρήνηPeace-1, ἐνώπιονBefore, in front of-2, θέλημαWill-2, εὐχαριστέωTo give thanks-2, δοξάζωTo magnify, extol-3, χάριςGift, grace-3, βασιλείαKingdom-7, αὐτόςHe, she, it, self-12, καίAnd-32, ὁthe-116,551495

15 Compare Cosine Similarity Tables This will show to which other lemmata each lemma in each Testament attracts The value will be positive if it they are more attracted in the LXX, negative if in the NT Paradigmatic comparison These comparisons should suggest meaning change

16 Compare Cosine Similarity Tables - Results 'θεόςEnglishLemma συνίημιTo come together, understand0, δοξάζωTo magnify, extol0, ταπεινόωTo lower, to abase0, φέρωTo carry0, σπέρμαSeed0, ἀρχήBeginning, power0, ἐπερωτάωTo consult0, ΔαυίδDavid0, πρεσβύτεροςElder0, γλῶσσαTongue0, … καιρόςPeace-0, ἕτεροςOther-0, οὖνAnd so-0, ἐμόςMine (possessive)-0, ἵναIn order to-0, βάλλωTo throw-0, ὥραPart of a day, hour-0, μᾶλλονmore-0, χάριςGift, grace-0, περιπατέωTo walk (about), to live-0,

17 Next Steps Finish comparison of LL and CS tables Include other information in analysis – POS Information – Semantic dependencies Could help to account for Greek sentence structure Remove information from the analysis – Stop words – Certain parts of speech (e.g., adverbs, particles) Close-reading analysis of the results


Κατέβασμα ppt "Semantic Drift between the Testaments Using Collocation Analysis to Find Theological Significance Matt Munson."

Παρόμοιες παρουσιάσεις


Διαφημίσεις Google