In this paper, we explore complex network properties of word collocation networks (Ferret, 2002) from four different genres. Each document of a particular genre was converted into a network of words with word collocations as edges. We analyzed graphically and statistically how the global properties of these networks varied across different genres, and among different network types within the same genre. Our results indicate that the distributions of network properties are visually similar but statistically apart across different genres, and interesting variations emerge when we consider different network types within a single genre. We further investigate how the global properties change as we add more and more collocation edges to the graph of one particular genre, and observe that except for the number of vertices and the size of the largest connected component, network properties change in phases, via jumps and drops.
That language shows complex network structure at the word level, was shown more than a decade ago by at least two independent groups of researchers @cite_20 @cite_12 . went further ahead, and designed an unsupervised keyword extraction algorithm using the small-world property of word collocation networks. extended the collocation network idea to rather than words, and observed a small-world structure in the resulting network. Edges between concepts were defined as entries in an English thesaurus. compared word collocation networks of Chinese and English text, and pointed out their similarities and differences. They further constructed in Chinese, showed their small-world structure, and used these networks in a follow-up study to accurately segregate Chinese essays from different literary periods @cite_8 .
@cite_12 @cite_20 @cite_8
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The aim of this study is to map the intellectual structure of digital library (DL) field in China during the period of 2002---2011. Co-word analysis was employed to reveal the patterns of DL field in China through measuring the association strength of keywords in relevant journals. Data was collected from Chinese Journal Full-Text Database during the period of 2002---2011. And then, the co-occurrence matrix of keywords was analyzed by the methods of multivariate statistical analysis and social network analysis. The results mainly include five parts: seven clusters of keywords, a two-dimensional map, the density and centrality of clusters, a strategic diagram, and a relation network. The results show that there are some hot research topics and marginal topics in DL field in China, but the research topics are relatively decentralized compared with the international studies. The text of this paper has passed across many Internet routers on its way to the reader, but some routers will not pass it along unfettered because of censored words it contains. We present two sets of results: 1) Internet measurements of keyword filtering by the Great “Firewall” of China (GFC); and 2) initial results of using latent semantic analysis as an efficient way to reproduce a blacklist of censored words via probing. Our Internet measurements suggest that the GFC’s keyword filtering is more a panopticon than a firewall, i.e., it need not block every illicit word, but only enough to promote self-censorship. China’s largest ISP, ChinaNET, performed 83.3 of all filtering of our probes, and 99.1 of all filtering that occurred at the first hop past the Chinese border. Filtering occurred beyond the third hop for 11.8 of our probes, and there were sometimes as many as 13 hops past the border to a filtering router. Approximately 28.3 of the Chinese hosts we sent probes to were reachable along paths that were not filtered at all. While more tests are needed to provide a definitive picture of the GFC’s implementation, our results disprove the notion that GFC keyword filtering is a firewall strictly at the border of China’s Internet. While evading a firewall a single time defeats its purpose, it would be necessary to evade a panopticon almost every time. Thus, in lieu of evasion, we propose ConceptDoppler, an architecture for maintaining a censorship “weather report” about what keywords are filtered over time. Probing with potentially filtered keywords is arduous due to the GFC’s complexity and can be invasive if not done efficiently. Just as an understanding of the mixing of gases preceded effective weather reporting, understanding of the relationship between keywords and concepts is essential for tracking Internet censorship. We show that LSA can effectively pare down a corpus of text and cluster filtered keywords for efficient probing, present 122 keywords we discovered by probing, and underscore the need for tracking and studying censorship blacklists by discovering some surprising blacklisted keywords such as l�‡ (conversion rate), �„K— (Mein Kampf), and ýE0(NfT�� (International geological scientific federation (Beijing)). Co-occurrence networks of Chinese characters are constructed from collections of essays in different periods of China: the ancient Chinese language, the Chinese language in Wei, Jin, and Southern-Northern Dynasties, the recent Chinese language, and the modern Chinese language, and their statistical parameters are studied. It has been found that 99.6 networks have the scale-free feature and 95.0 networks have the smallworld effect. This study reveals some commonalities and differences among articles in different periods of China from a complex network perspective. There has been a controversial question as to whether the literatures in Wei, Jin, and Southern-Northern Dynasties should belong to the ancient Chinese language or the recent Chinese language in the linguistic study. Our work shows that the statistical parameters of networks in Wei, Jin, and Southern-Northern Dynasties are clearly different from those of networks in the other periods of China, and it seems more reasonable that the literatures in Wei, Jin, and Southern-Northern Dynasties belong to the recent Chinese language. This study aims to reveal the intellectual structure of Library and Information Science (LIS) in China during the period 2008---2012 utilizing co-word analysis. The status and trends of LIS in China are achieved by measuring the correlation coefficient of selected keywords extracted from relevant journals in the Chinese Journal Full-Text Database. In co-word analysis, multivariate statistical analysis and social network analysis are applied to obtain 13 clusters of keywords, a two-dimensional map, centrality and density of clusters, a strategic diagram and a relation network. Based on these results, the following conclusions can be drawn: (i) LIS in China has some established and well-developed research topics; (ii) a few emerging topics have a great potential for development; and (iii), the research topics in this LIS field are largely decentralized as a whole, where there are many marginal and immature topics.