the gravity of meaning: physics as a metaphor to model semantic changes
DESCRIPTION
Based on a computed toy example, we offer evidence that by plugging in similarity of word meaning as a force plus a small modification of Newton's 2nd law, one can acquire specific "mass" values for index terms in a Saltonesque dynamic library environment. The model can describe two types of change which affect the semantic composition of document collections: the expansion of a corpus due to its update, and fluctuations of the gravitational potential energy field generated by normative language use as an attractor juxtaposed with actual language use yielding time-dependent term frequencies. By the evolving semantic potential of a vocabulary and concatenating the respective term "mass" values, one can model sentences or longer strings of symbols as vector-valued functions. Since the line integral of such functions is used to express the work of a particle in a gravitational field, the work equivalent of strings can be calculated.TRANSCRIPT
The gravity of meaning: Physics as ametaphor to model semantic changes
Sándor Darányi and Peter [email protected], [email protected]
KEY POINTS• Index terms and term mass;
• Newton’s 2nd law and deterministic me-chanics;
• Velocity and acceleration of languagechange;
• Work in a gravitational field.
FUTURE WORKThe current model yields variable term massover observation periods, which departs fromits roots in classical mechanics. Although ul-timately language may show different ‘symp-toms of behaviour’ as physics does, we areworking on an alternative to yield constantterm mass values, leading to scalability testsand evaluation of the new model.
Secondly, we want to visualize the evolving se-mantic potential fields of document collectionsto understand the nature and importance ofsuch fields for sentence construction as an en-ergetic process.
THE METAPHORThis representation has the following advantages:
• It utilizes physics as a metaphor to model the dynamics oflanguage change;
• It demonstrates the connection between sentence structureand work carried out in a field based on classical (Newto-nian) mechanics, i.e. is feasible to quantify the work con-tent in documents;
• It models such a field as the gravitational potential energyterms possess in the presence of language norms, with sim-ilarity as a force between pairs of them as the gradient ofthe above potential;
• It naturally bridges the gap between language analysis andlanguage generation.
Based on a computed toy example, we offer evidence that by plugging in similarity of word mean-ing as a force plus a small modification of Newton’s 2nd law, one can acquire specific ‘mass’ val-ues for index terms in a Saltonesque dynamic library environment [2]. The model can describetwo types of change which affect the semantic composition of document collections [1]: the ex-pansion of a corpus due to its update, and fluctuations of the gravitational potential energy fieldgenerated by normative language use as an attractor juxtaposed with actual language use yieldingtime-dependent term frequencies [3]. By the evolving semantic potential of a vocabulary and con-catenating the respective term ‘mass’ values, one can model sentences or longer strings of symbolsas vector-valued functions. Since the line integral of such functions is used to express the work of aparticle in a gravitational field, the work equivalent of strings can be calculated.
RESULTS
Evolution of an indexing vocabulary over timet = 0 Doping Football Performance Skiing Trainingd1 5 2 0 0 0d2 4 0 0 3 1d3 0 0 4 0 5d4 6 0 2 0 0d5 0 3 0 0 4t = 1d1 5 2 0 0 0d2 4 0 0 3 1d3 0 0 4 0 5d4 6 0 2 0 0d5 0 3 0 0 4d6 2 3 0 1 1d7 1 0 0 4 5t = 2d1 5 2 0 0 0d2 4 0 0 3 1d3 0 0 4 0 5d4 6 0 2 0 0d5 0 3 0 0 4d6 2 3 0 1 1d7 1 0 0 4 5d8 5 6 1 1 0d9 2 1 1 3 0
Calculation of term mass over t0-t2Doping Football Performance Skiing Training
v1 9 9 0 25 36v2 49 49 4 16 0a 40 40 4 -9 -36F 1.56 1.28 1.24 1.35 1.37m 0.039 0.032 0.31 0.15 0.038
REFERENCES
[1] A. Baker. Computational approaches to the study of language change. Language and Linguistics Compass,2(3):289–307, 2008.
[2] G. Salton. Dynamic information and library processing. 1975.[3] H. White. Cross-textual cohesion and coherence. In Proceedings of the Workshop on Discourse Architectures:
The Design and Analysis of Computer-Mediated Conversation, Minneapolis, MN, USA, April 2002.
MORE INFORMATION
Related papers and more infor-mation are available athttp://www.squalar.org/
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