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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Panta rei: Tracking Semantic Change with Distributional Semantics in Ancient Greek</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Martina A. Rodda</string-name>
          <email>martina.rodda@sns.it</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Marco S.G. Senaldi</string-name>
          <email>marco.senaldi@sns.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Alessandro Lenci</string-name>
          <email>alessandro.lenci@unipi.it</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>CoLing Lab, Università di Pisa</institution>
          ,
          <addr-line>via S. Maria 36</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Scuola Normale Superiore</institution>
          ,
          <addr-line>Piazza dei Cavalieri, 7, 56126 Pisa -</addr-line>
          <country country="IT">ITALY</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Scuola Normale Superiore</institution>
          ,
          <addr-line>Piazza dei Cavalieri, 7, 56126 Pisa -</addr-line>
          <country country="IT">ITALY</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>English. We present a method to explore semantic change as a function of variation in distributional semantic spaces. In this paper we apply this approach to automatically identify the areas of semantic change in the lexicon of Ancient Greek between the pre-Christian and Christian era. Distributional Semantic Models are used to identify meaningful clusters and patterns of semantic shift within a set of target words, defined through a purely data-driven approach. The results emphasize the role played by the diffusion of Christianity and by technical languages in determining semantic change in Ancient Greek and show the potentialities of distributional models in diachronic semantics.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Italiano. Si presenta un metodo per
indagare il cambiamento semantico come
funzione della variazione all’interno di
spazi semantici. Questo approccio è
applicato per identificare automaticamente
aree di cambiamento semantico nel
lessico greco antico tra età pre-cristiana e
cristiana. Modelli della Semantica
Distribuzionale sono usati per identificare
cluster e pattern di cambiamento
semantico in una lista di parole target, definita
con un approccio puramente data-driven.
I risultati mostrano il ruolo della
diffusione del Cristianesimo e dei linguaggi
tecnici nel determinare cambiamenti
semantici in greco antico, nonché le
potenzialità dei modelli distribuzionali nella
semantica diacronica.
1</p>
    </sec>
    <sec id="sec-2">
      <title>Introduction and Related Work</title>
      <p>
        Distributional Semantics is grounded on the
assumption that the meaning of a word can be
described as a function of its collocates in a corpus.
This suggests that diachronic meaning shifts can
be traced through changes in the distribution of
these collocates over time
        <xref ref-type="bibr" rid="ref12">(Sagi et al., 2011)</xref>
        .
While some studies focused on testing the
explanatory power of this method over
frequencyand syntax-based approaches
        <xref ref-type="bibr" rid="ref12 ref13 ref8">(Wijaya and
Yeniterzi, 2011; Kulkarni et al., 2015)</xref>
        , more
advanced contributions to the field explored how
distributional models can be used to test
competing hypotheses about semantic change
        <xref ref-type="bibr" rid="ref14">(Xu and
Kemp, 2015)</xref>
        , or to investigate the productivity
of constructions in diachrony
        <xref ref-type="bibr" rid="ref11">(Perek, 2016)</xref>
        . The
results attest the explanatory power of
distributional methods in modeling diachronic shifts in
meaning.
      </p>
      <p>
        In this paper, we propose a method to identify
semantic change through the Representational
Similarity Analysis
        <xref ref-type="bibr" rid="ref3 ref7">(RSA; Kriegeskorte and
Kievit, 2013)</xref>
        of distributional vector spaces built
from diachronic corpora. RSA is a method
extensively used in neuroscience to test cognitive and
computational models by comparing the
geometry of their representation spaces
        <xref ref-type="bibr" rid="ref4">(Edelman,
1998)</xref>
        . Stimuli are represented with a
representational dissimilarity matrix that contains a
measure of the dissimilarity relations of the stimuli
with each other. Different matrices are compared
to evaluate the correspondence of the
representational spaces built from different sources (e.g.,
behavioral and neuroimaging data). We argue
that this method can be applied to compare
distributional representations of the lexicon at
different temporal stages. The hypothesis is that the
elements in the lexical spaces showing larger
geometrical variations in time correspond to the
lexical areas that have undergone major semantic
changes. To the best of our knowledge, this is the
first time RSA is used in diachronic
distributional semantics.
      </p>
      <p>
        Here we present a case study that applies RSA
to track patterns of semantic change within the
lexicon of Ancient Greek. We focus on the first
few centuries AD, when the rise of Christianity
caused a deep and widespread cultural shift
within the Hellenic world. We predict that this shift
will be reflected in the Greek lexicon of the time.
In addition to past studies
        <xref ref-type="bibr" rid="ref1 ref10">(Boschetti, 2009;
O’Donnell, 2005 is a general introduction)</xref>
        , we
apply a bottom-up approach to the detection of
semantic change, with no prior definition of a list
of lemmas to be analyzed. The goal is to develop
a quantitative “discovery procedure” to detect
lexical semantic changes.
      </p>
      <p>From a methodological standpoint, this study
aims to show how Distributional Semantics can
be applied fruitfully to such a small and literary
corpus as the collection of Ancient Greek texts.
The results will also highlight the ways in which
Distributional Semantics can complement the
intuition of the researcher in analyzing semantic
change in Ancient Greek, providing a useful tool
for future studies in Classics.
2</p>
    </sec>
    <sec id="sec-3">
      <title>Materials and Methods</title>
      <p>The corpus used for this study is based on the
TLG-E (Thesaurus Linguae Graecae) collection
of Ancient Greek literary texts. The database was
divided into two sub-corpora, the first of which
contains texts from the 7th to the 1st century BC
(pre-Christian era), while the second one spans
from the 1st to the 5th century AD (early Christian
era). The pre-Christian sub-corpus contains
6,795,253 tokens, while the Christian sub-corpus
totalizes 29,051,269 tokens.</p>
      <p>
        The texts were lemmatized using Morpheus
        <xref ref-type="bibr" rid="ref2">(Crane, 1991)</xref>
        . Any issues with the lemmatization
should not have a significant impact on the
results unless otherwise stated
        <xref ref-type="bibr" rid="ref1">(cf. Boschetti, 2009,
page 60 for a discussion)</xref>
        . After filtering for
stopwords (mainly particles, pronouns and
connectives) and lemmas occurring with a frequency
below 100 tokens, the pre-Christian and
Christian sub-corpus contain, respectively, 4,109 and
10,052 lemmas, which were used both as targets
and dimensions in our vector spaces.
      </p>
      <p>
        A vector space model was then built for each
sub-corpus using the DISSECT toolkit
        <xref ref-type="bibr" rid="ref3">(Dinu et
al., 2013)</xref>
        . Henceforth, we refer to the
preChristian era model as the BC-Space, and to the
Cristian era model as the AD-Space.
Cooccurrences were computed within a window of
11 words (5 content words to the right and to the
left of each target word). Association scores were
weighted using positive point-wise mutual
information (PPMI)
        <xref ref-type="bibr" rid="ref5">(Evert, 2008)</xref>
        ; the resulting
matrices were reduced to 300 latent dimensions
using Singular Value Decomposition (SVD).
2.1
      </p>
    </sec>
    <sec id="sec-4">
      <title>RSA of the distributional vector spaces</title>
      <p>We have adapted the RSA method to discover
semantic changes between the two vector spaces:
1. we identified the words occurring in both
subcorpora with a frequency higher than 100 tokens,
obtaining 3,977 lemmas;
2. we built a representational similarity matrix
(RSM) from the BC-Space (RSMBC) and one
from the AD-Space (RSMAD). Each RSM is a
square matrix indexed horizontally and vertically
by the 3,977 lemmas and containing in each cell
the cosine similarity of a lemma with the other
lemmas in a vector space (this is a minor
variation with respect to the original RSA method,
which instead uses dissimilarity matrices). A
RSM is a global representation of the semantic
space geometry in a given period: vectors
represent lemmas in terms of their position relative to
the other lemmas in the semantic space;
3. for each lemma, we computed the Pearson
correlation coefficient between its vector in RSMBC
and the corresponding vector in RSMAD.
The Pearson coefficient measures the degree of
semantic shift across the two temporal slices.
The lower the correlation, the more a word
changed its meaning.
3</p>
    </sec>
    <sec id="sec-5">
      <title>Discussion of Results</title>
      <p>The following section focuses on the words that
underwent the biggest changes, i.e. those for
which the correlation scores are lower. The
primary goal will be to establish whether these
words can be clustered into meaningful groups.
This would allow us to pinpoint the areas within
the lexicon of Ancient Greek that have
undergone a significant semantic shift during the early
centuries of Christianity.
3.1</p>
    </sec>
    <sec id="sec-6">
      <title>Qualitative Analysis</title>
      <p>The 50 lemmas with the lowest correlation
coefficients were scrutinized in order to establish
whether meaningful subgroups emerge. (This list
of words is not reproduced here due to space
constraints. They are a subset of the 200 words
used to build the plot in section 4.3.) The
findings in this section, while inevitably limited by
the intuition of the researcher, will provide the
starting point for a more sophisticated analysis to
be performed in the following sections.</p>
      <p>The lemmas under consideration form a
somewhat heterogeneous collection, including
concrete nouns and relatively common verbs
such as ζυγόν (zygón “yoke”) and ἕπομαι
(hépomai “follow”), as well as some proper nouns.
This notwithstanding, a promising subset of
words emerges even at this preliminary stage.
These are a number of nouns designating
eminently Christian concepts, such as παραβολή
(parabolé “parable”, previously “comparison”),
λαός (laós, used for the Christian community as
opposed to non-Christians, previously “people”),
κτίσις (ktísis “creation”, previously “founding,
settling”).</p>
      <p>
        These findings are in line with the idea that the
diffusion of Christianity played a substantial role
in semantic change in the first centuries AD
        <xref ref-type="bibr" rid="ref1">(cf.
Boschetti, 2009)</xref>
        . Other Christian terms, such as
θεός (theós “God”), ἄγγελος (ángelos “angel”,
previously “messenger”), πατήρ (patér “father”),
υἱός (hyiós “son”), also occur among the 100
words with the lowest correlation coefficients.
      </p>
      <p>Another group of lemmas comprises technical
terms whose usage seems to have undergone a
specialization or a shift from one domain of
knowledge to another. These include words such
as ὑπόστασις (hypóstasis “substance”, previously
“sediment, foundation”), δύναμις (dýnamis
“property (of beings)”, previously “power”), or
ῥητός (rhetós “literal” as opposed to
“allegorical”, previously “stated”).
3.2</p>
    </sec>
    <sec id="sec-7">
      <title>Analysis of Nearest Neighbors</title>
      <p>To corroborate the intuitions detailed above, the
10 nearest neighbors for each of the last 50
words according to the correlation coefficient
were retrieved using DISSECT. The process was
repeated for each sub-corpus and the results
compared in order to look for visible shifts,
especially those involving different semantic
domains. A few examples of the results should
suffice to confirm the findings in the last section.</p>
      <p>For instance, among the nearest neighbors for
πνεῦμα (pnêuma “spirit”, previously “breath”) in
the AD-Space we find such words as θεάομαι
(theáomai “contemplate”), ἀληθινός (alethinós
“true”), κτίσις, υἱός, θεός and so forth, while in
the BC-Space the strongest similarity is with
terms pertaining to the domain of physics, such
as ἀήρ (aér “air”), ὑγρός (hygrós “moist”),
θερμός (thermós “hot”). Another clear-cut
example is that of δύναμις, whose neighbors change
from military terms such as πολιορκία (poliorkía
“siege”) and στρατόπεδον (stratópedon
“encampment, army”) to the physical and
philosophical domain, with the closest term being ἐνέργεια
(enérgeia “activity, actuality”, an antonym of
δύναμις in its philosophical sense of
“potentiality”). The case of δύναμις also shows how nearest
neighbor analysis can reveal shifts in the usage
of heavily polysemous words.</p>
      <p>Not all changes observed through the analysis
of nearest neighbors, however, are so easily
predictable. Thus, for instance, the neighbors for
μοῖρα (môira, another highly polysemous word
with meanings spanning from “part” to
“destiny”) in the AD-Space come exclusively from the
domain of astronomy, showing a strong
specialization towards a technical usage (“degree” or
“division” of the Zodiac). Another remarkable
result comes from a geographical adjective,
Ποντικός (Pontikós “coming from Pontus”),
whose nearest neighbors shift from proper names
and philosophical terms in the pre-Christian age
(an association due, without doubt, to the usage
of “Ponticus” as an epithet for authors, e.g.
Heraclides) to names of currency and trade wares,
probably as a reflection of the integration of
Pontus as a Roman province (with the obvious
repercussions on trade) in the 1st century AD.
3.3</p>
      <p>
        t-SNE Plot
As a final analysis, we embedded the RSMAD
vectors for the 200 words with the lowest
correlation coefficient with the corresponding RSMBC
vectors in a two-dimensional space with t-SNE
(Figure 1), a technique for dimensionality
reduction and data visualization that overcomes some
of the limitations of standard multidimensional
scaling
        <xref ref-type="bibr" rid="ref5 ref9">(van der Maaten and Hinton, 2008)</xref>
        . This
procedure allows for easy identification of
clusters, thus revealing the semantic relation between
the most recent meanings of the words that
underwent the greatest semantic change.
      </p>
      <p>A number of small clusters can be observed in
the plot. Near the left periphery, the most
relevant group is composed of terms pertaining to
Christian theology (from κύριος kýrios “Lord”,
λαός and θεός, to παρουσία parousía “Advent”
and ποιμήν poimén “shepherd”). The position of
ψῦχος (psŷkhos “cold”) nearby is due to the
mislemmatization of some inflected forms of ψυχή
(psyché “soul”) under this lemma, as revealed by
nearest neighbor analysis. To the left of this
group, a small cluster of terms pertaining to
Christian exegesis (ῥητός, παραβολή, διασαφέω
diasaphéo “illustrate”) can be recognized.</p>
      <p>The upper portion of the plot houses technical
terms from the domains of medicine (the
uppermost groups), astronomy and geometry, while
philosophical terminology is found in the outer
right area. Some smaller groups are also
noticeable, such as μνᾶ (mnâ “mina”) and δραχμή
(drakhmé “drachma”), both units of currency, on
the left, and πρώτιστος (prótistos “the very first”)
and Τίμαιος (the proper name Tímaios, Latin
Timaeus), both connected to (Neo-)Platonic
philosophy, on the right.</p>
      <p>All in all, despite a certain amount of noise,
the plot in Figure 1 supports the findings detailed
so far. We can see how the main semantic
changes in the Greek lexicon between the pre-Christian
and Christian era affected the domains of religion
(in a broader sense) and/or technical language.
Within these domains, some more fine-grained
relations between words that underwent
significant semantic shifts can be observed.
4</p>
    </sec>
    <sec id="sec-8">
      <title>Conclusion</title>
      <p>
        This paper shows how Distributional Semantics
can be used as an exploratory tool to detect
semantic change. In this case study on Ancient
Greek, the proposed method based on
distributional RSA not only confirms the hypothesis that
the diffusion of Christianity was a crucial cause
of semantic change in the Greek lexicon, but also
allows for the identification of unexpected
patterns of evolution, such as the apparent
specialization in the usage of technical terms. This last
phenomenon could also be influenced by the fact
that the AD-corpus is richer in philosophical and
technical treatises; however, a documented
change in the proportion of different possible
usages of a word is in itself a very informative
result, especially in a field such as Classics, where
the analysis of (literary) texts is paramount.
Further research should undoubtedly highlight the
effect of corpus composition. A focus on shorter
periods of time might be of interest, since, for
instance, the rise of technical prose writing is a
characteristic of the Hellenistic Age
        <xref ref-type="bibr" rid="ref6">(cf. e.g.
Gutzwiller 2007, pages 154-167)</xref>
        .
      </p>
      <p>
        From a methodological standpoint, the fact
that the results obtained from such a small corpus
of purely literary texts are both meaningful and
informative is of great relevance. Furthermore,
the choice to adopt a data-driven approach
proved fruitful, in that it brought to light
directions of change that were not expected a priori.
For traditional research in Classics, a
computational approach to the lexicon of Ancient Greek
is compelling because it provides new
information about a language for which the judgments
of native speakers are unavailable
        <xref ref-type="bibr" rid="ref11">(cf. Perek,
2016)</xref>
        . The results of this study show how
Distributional Semantics can complement the
assertions of the philologist, as well as help discover
patterns of lexical change that would otherwise
be impossible to grasp beyond an intuitive level.
      </p>
    </sec>
  </body>
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