Initial Comparison of Linguistic Networks Measures for Parallel Texts
📝 Original Info
- Title: Initial Comparison of Linguistic Networks Measures for Parallel Texts
- ArXiv ID: 1405.1893
- Date: 2014-07-18
- Authors: Researchers from original ArXiv paper
📝 Abstract
This paper presents preliminary results of Croatian syllable networks analysis. Syllable network is a network in which nodes are syllables and links between them are constructed according to their connections within words. In this paper we analyze networks of syllables generated from texts collected from the Croatian Wikipedia and Blogs. As a main tool we use complex network analysis methods which provide mechanisms that can reveal new patterns in a language structure. We aim to show that syllable networks have much higher clustering coefficient in comparison to Erd\"os-Renyi random networks. The results indicate that Croatian syllable networks exhibit certain properties of a small world networks. Furthermore, we compared Croatian syllable networks with Portuguese and Chinese syllable networks and we showed that they have similar properties.💡 Deep Analysis
Deep Dive into Initial Comparison of Linguistic Networks Measures for Parallel Texts.This paper presents preliminary results of Croatian syllable networks analysis. Syllable network is a network in which nodes are syllables and links between them are constructed according to their connections within words. In this paper we analyze networks of syllables generated from texts collected from the Croatian Wikipedia and Blogs. As a main tool we use complex network analysis methods which provide mechanisms that can reveal new patterns in a language structure. We aim to show that syllable networks have much higher clustering coefficient in comparison to Erd"os-Renyi random networks. The results indicate that Croatian syllable networks exhibit certain properties of a small world networks. Furthermore, we compared Croatian syllable networks with Portuguese and Chinese syllable networks and we showed that they have similar properties.