The Structure and Dynamics of Linguistic Networks

@inproceedings{Choudhury2009TheSA,
  title={The Structure and Dynamics of Linguistic Networks},
  author={Monojit Choudhury and Animesh Mukherjee},
  year={2009}
}
Using a Heterogeneous Linguistic Network for Word Sense Induction and Disambiguation
TLDR
A hybrid linguistic structure that takes into account lexical and syntactical language information is proposed that aims to shed light into ways of combining distinct types of linguistic information in order to take advantage of each of its components’ unique characteristics.
LaNCoA: A Python toolkit for Language Networks Construction and Analysis
  • D. Margan, A. Meštrović
  • Computer Science
    2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
  • 2015
TLDR
The toolkit provides various procedures for network construction from the text: on the word- level (co-occurrence networks, syntactic networks, shuffled networks), and on the subword-level (syllable networks, grapheme networks) and implements functions for the language networks analysis on the global and local level.
It May Be in the Structure, Not the Combinations: Graph Metrics as an Alternative to Statistical Measures in Corpus-Linguistic Research
The following contribution summarizes a number of problems associated with a methodological focus on statistical measures in corpus linguistics, specifically in the subfield of lexical and
Semantic network analysis of abstract and concrete word associations
TLDR
This work applied semantic network analyses to explore norms of French word associations for concrete and abstract concepts to confirm the generalisability of these properties to the French language and with an emphasis on abstract and concrete concepts.
Networks in the mental lexicon – contributions from Hungarian
TLDR
This paper investigates the network structure of the mental lexicon of a non-Indo-European language, Hungarian, using a word association database which collected word association data online and found that both networks display similar characteristics.
Exploring Hidden Networks Yields Important Insights in Disparate Fields of Study
Cascading blackouts typically occur when nearly simultaneous outages occur in k out of N components in a power system, triggering subsequent failures that propagate through the network and cause
Language Networks: a Practical Approach
TLDR
This manuscript provides a practical tutorial on how to model and characterize texts using network-based features and includes examples of pre-processing and network representations.
Graph-based exploration and clustering analysis of semantic spaces
TLDR
This is the first study that uses graph theory and network science in the considered context and suggests that human built networks possess more intuitive global connectivity patterns, whereas local characteristics of the machine built networks provide much richer information on the contextual usage and perceived meanings of words.
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References

SHOWING 1-10 OF 112 REFERENCES
Modeling the cooccurrence principles of the consonant inventories: A complex network approach
  • International Journal of Modern Physics C, 18(2):281–295,
  • 2007
Unsupervised learning of natural languages
TLDR
This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.
Wordnet, an Electronic Lexical Database for English
  • MIT Press, Cambridge, MA,
  • 1998
Unsupervised Parts-of-Speech Induction for Bengali
TLDR
A study of the word interaction networks of Bengali in the framework of complex networks reveals interesting insights into the morpho-syntax of the language, whereas clustering helps in the induction of the natural word classes leading to a principled way of designing POS tagsets.
Two Regimes in the Frequency of Words and the Origins of Complex Lexicons: Zipf’s Law Revisited*
TLDR
It is made evident that word frequency as a function of the rank follows two different exponents, ˜(-)1 for the first regime and ™(-)2 for the second.
Language as an evolving word web
TLDR
It follows from the theory of the evolution of language that the size of the core part of language, the ‘kernel lexicon’, does not vary as language evolves, and the two regimes in the distribution naturally emerge from the evolutionary dynamics of the word web.
HyperLex: lexical cartography for information retrieval
Part-of-Speech Induction from Scratch
TLDR
A method for inducing the parts of speech of a language and part-of-speech labels for individual words from a large text corpus and classifies both ambiguous and unambiguous words correctly with high accuracy is presented.
...
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