scholarly journals Co-Occurrence Network of High-Frequency Words in the Bioinformatics Literature: Structural Characteristics and Evolution

2018 ◽  
Vol 8 (10) ◽  
pp. 1994 ◽  
Author(s):  
Taoying Li ◽  
Jie Bai ◽  
Xue Yang ◽  
Qianyu Liu ◽  
Yan Chen

The subjects of literature are the direct expression of the author’s research results. Mining valuable knowledge helps to save time for the readers to understand the content and direction of the literature quickly. Therefore, the co-occurrence network of high-frequency words in the bioinformatics literature and its structural characteristics and evolution were analysed in this paper. First, 242,891 articles from 47 top bioinformatics periodicals were chosen as the object of the study. Second, the co-occurrence relationship among high-frequency words of these articles was analysed by word segmentation and high-frequency word selection. Then, a co-occurrence network of high-frequency words in bioinformatics literature was built. Finally, the conclusions were drawn by analysing its structural characteristics and evolution. The results showed that the co-occurrence network of high-frequency words in the bioinformatics literature was a small-world network with scale-free distribution, rich-club phenomenon and disassortative matching characteristics. At the same time, the high-frequency words used by authors changed little in 2–3 years but varied greatly in four years because of the influence of the state-of-the-art technology.

Author(s):  
Vasiliki G. Vrana ◽  
Dimitrios A. Kydros ◽  
Evangelos C. Kehris ◽  
Anastasios-Ioannis T. Theocharidis ◽  
George I. Kavavasilis

Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.


2021 ◽  
Author(s):  
◽  
Yen Dang

<p>Understanding academic spoken English is challenging for second language (L2) learners at English-medium universities. A lack of vocabulary is a major reason for this difficulty. To help these learners overcome this challenge, it is important to examine the nature of vocabulary in academic spoken English.  This thesis presents three linked studies which were conducted to address this need. Study 1 examined the lexical coverage in nine spoken and nine written corpora of four well-known general high-frequency word lists: West’s (1953) General Service List (GSL), Nation’s (2006) BNC2000, Nation’s (2012) BNC/COCA2000, and Brezina and Gablasova’s (2015) New-GSL.  Study 2 further compared the BNC/COCA2000 and the New-GSL, which had the highest coverage in Study 1. It involved 25 English first language (L1) teachers, 26 Vietnamese L1 teachers, 27 various L1 teachers, and 275 Vietnamese English as a Foreign Language learners. The teachers completed 10 surveys in which they rated the usefulness of 973 non-overlapping items between the BNC/COCA2000 and the New-GSL for their learners in a five-point Likert scale. The learners took the Vocabulary Levels Test (Nation, 1983, 1990; Schmitt, Schmitt, & Clapham, 2001), and 15 Yes/No tests which measured their knowledge of the 973 words.  Study 3 involved compiling two academic spoken corpora, one academic written corpus, and one non-academic spoken corpus. Each contains approximately 13-million running words. The academic spoken corpora contained four equally-sized sub-corpora. From the first academic spoken corpus, 1,741 word families were selected for the Academic Spoken Word List (ASWL). The coverage of the ASWL and the BNC/COCA2000 in the four corpora and the potential coverage of the ASWL for learners of different vocabulary levels were determined.  Six main findings were drawn from these studies. First, in the first academic spoken corpus, the ASWL and its levels had slightly higher coverage in certain disciplinary sub-corpora than in the others. Yet, the list provided around 90% coverage of each sub-corpus. It helps learners to achieve 92%-96% coverage of academic speech depending on their levels. Second, the BNC/COCA2000 is the most suitable general high-frequency word list for L2 learners from the perspectives of corpus linguistics, teachers, and learners. It provided higher coverage than the GSL and the BNC2000, and had more words known by learners and perceived as being useful by teachers than the New-GSL. Third, general high-frequency words, especially the most frequent 1,000 words, provided much higher coverage in spoken corpora than written corpora in both academic and non-academic discourse. Fourth, despite the importance of general high-frequency words, a reasonable proportion of the learners had insufficient knowledge of these words, which highlights the importance of a word list which is adaptable to learners’ proficiency like the ASWL. Fifth, lexical coverage had significant but small correlations with teacher perception of word usefulness and learner vocabulary knowledge. Sixth, the Vietnamese L1 teachers had the highest correlation between the teacher ratings of word usefulness and the learner vocabulary knowledge. Next came the various L1 teachers, and then the English L1 teachers.  This thesis also provides theoretical, pedagogical, and methodological implications of these findings so that L2 learners can gain better support in their vocabulary development and achieve better comprehension of academic spoken English.</p>


2020 ◽  
Vol 34 (30) ◽  
pp. 2050333
Author(s):  
Guangyao Xu ◽  
Zikai Wu

How to effectively control the trapping process in complex systems is of great importance in the study of trapping problem. Recently, the approach of delayed random walk has been introduced into several deterministic network models to steer trapping process. However, exploring delayed random walk on pseudo-fractal web with the co-evolution of topology and weight has remained out of reach. In this paper, we employ delayed random walk to guide trapping process on a salient deterministic weighted scale-free small-world network with the co-evolution of topology and weight. In greater detail, we first place a deep trap at one of initial nodes of the network. Then, a tunable parameter [Formula: see text] is introduced to modulate the transition probability of random walk and dominate the trapping process. Subsequently, trapping efficiency is used as readout of trapping process and average trapping time is employed to measure trapping efficiency. Finally, the closed form solution of average trapping time (ATT) is deduced analytically, which agrees with corresponding numerical solution. The analytical solution of ATT shows that the delayed parameter [Formula: see text] only modifies the prefactor of ATT, and keeps the leading scaling unchanged. In other words, ATT grows sublinearly with network size, whatever values [Formula: see text] takes. In summary, the work may serves as one piece of clues for modulating trapping process toward desired efficiency on more general deterministic networks.


2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Weiwei Cao ◽  
Xiangnan Feng ◽  
Jianmin Jia ◽  
Hong Zhang

Understanding the structure of the Chinese railway network (CRN) is crucial for maintaining its efficiency and planning its future development. To advance our knowledge of CRN, we modeled CRN as a complex weighted network and explored the structural characteristics of the network via statistical evaluations and spatial analysis. Our results show CRN as a small-world network whose train flow obeys power-law decaying, demonstrating that CRN is a mature transportation infrastructure with a scale-free structure. CRN also shows significant spatial heterogeneity and hierarchy in its regionally uneven train flow distribution. We then examined the nodal centralities of CRN using four topological measures: degree, strength, betweenness, and closeness. Nodal degree is positively correlated with strength, betweenness, and closeness. Unlike the common feature of a scale-free network, the most connected nodes in CRN are not necessarily the most central due to underlying geographical, political, and socioeconomic factors. We proposed an integrated measure based on the four centrality measures to identify the global role of each node and the multilayer structure of CRN and confirm that stable connections hold between different layers of CRN.


Author(s):  
Vasiliki G. Vrana ◽  
Dimitrios A. Kydros ◽  
Evangelos C. Kehris ◽  
Anastasios-Ioannis T. Theocharidis ◽  
George I. Kavavasilis

Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.


Sign in / Sign up

Export Citation Format

Share Document