Symmetry of Network Patterns

1974 ◽  
pp. 129-187
Author(s):  
A. V. Shubnikov ◽  
V. A. Koptsik ◽  
David Harker
Keyword(s):  
Network Patterns

scholarly journals Functional traits shape small mammal-helminth network: patterns and processes in species interactions

Parasitology ◽  
2021 ◽  
pp. 1-36
Author(s):  
Thiago dos Santos Cardoso ◽  
Cecilia Siliansky de Andreazzi ◽  
Arnaldo Maldonado Junior ◽  
Rosana Gentile
Keyword(s):  
Functional Traits ◽  
Small Mammal ◽  
Species Interactions ◽  
Patterns And Processes ◽  
Network Patterns

scholarly journals Study on Tourism Flow Network Patterns on May Day Holiday

2021 ◽  
Vol 13 (2) ◽  
pp. 947
Author(s):  
Shanshan Wu ◽  
Lucang Wang ◽  
Haiyang Liu
Keyword(s):  
Transportation Network ◽  
Edge Structure ◽  
Flow Network ◽  
Factors Affecting ◽  
Spatial Distribution Characteristics ◽  
Transportation Modes ◽  
May Day ◽  
High Level ◽  
Network Patterns ◽  
Main Factor

The development of tourism is based on tourism flow and studying a tourism flow network can help to elucidate its mechanism of operation. Transportation network is the path to realize the spatial displacement of tourism flow. This study used “Tencent migration” big data to explore the spatial distribution characteristics and rules of tourism flow in China, providing suggestions for the development of tourism. The results demonstrate that the 361 cities studied can be divided into three types: destination-oriented, tourist-origin-oriented, and destination-oriented and tourist-origin-oriented. There are significant differences in the quantity of flow, the area of concentration, and the factors affecting the flow in the three types of cities. The larger the flow of tourism between cities, the higher the network level, and the wider the network range. The high-level nodes are closely related, while the peripheral nodes are more widely distributed, with weak attractiveness and inconvenient traffic, forming a “core-edge” structure. Different network patterns are established for different modes of transportation. The degree of response of different types of transportation to distance is the main factor influencing the network patterns of diverse paths. These findings have practical implications for the choice of appropriate travel destinations and transportation modes for tourists.

Big data analysis of trends in the second-hand apparel market: a comparison between 2014 and 2019

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanghee Kim ◽  
Hongjoo Woo
Keyword(s):  
Big Data ◽  
Design Methodology ◽  
Semantic Network ◽  
Distribution Channels ◽  
Subject Area ◽  
Future Research ◽  
Semantic Network Analysis ◽  
Content Type ◽  
The Past ◽  
Network Patterns

Purpose According to the perspective of evolutionary economic theory, the marketplace continuously evolves over time, following the changing needs of both customers and firms. In accordance with the theory, the second-hand apparel market has been rapidly expanding by meeting consumers’ diverse preferences and promoting sustainability since 2014. To understand what changes in consumers’ consumption behaviors regarding used apparel have driven this growth, the purpose of this study is to examine how the second-hand apparel market product types, distribution channels and consumers’ motives have changed over the past five years. Design/methodology/approach This study collected big data from Google through Textom software by extracting all Web-exposed text in 2014, and again in 2019, that contained the keyword “second-hand apparel,” and used the Node XL program to visualize the network patterns of these words through the semantic network analysis. Findings The results indicate that the second-hand apparel market has evolved with various changes over the past five years in terms of consumer motives, product types and distribution channels. Originality/value This study provides a comprehensive understanding of the changing demands of consumers toward used apparel over the past five years, providing insights for retailers as well as future research in this subject area.

Social Networks and the Willingness to Communicate: Reciprocity and Brokerage

2018 ◽  
Vol 38 (2) ◽  
pp. 194-214
Author(s):  
H. Colin Gallagher
Keyword(s):  
Second Language ◽  
Social Network ◽  
English For Academic Purposes ◽  
Willingness To Communicate ◽  
Network Ties ◽  
Structural Variables ◽  
Psychological Models ◽  
Reciprocal Structures ◽  
Discussion Partners ◽  
Network Patterns

Psychological models of second language (L2) communication have focused on cognitive, affective, and motivational precursors to L2 communication, while largely neglecting sociostructural factors. One way to conceptualize structural variables is in terms of social network reciprocity (mutually acknowledged network ties) and brokerage (social intermediaries). To investigate whether network positions predict willingness to communicate in the second language (L2 WTC), a cohort of English-for-Academic-Purposes students ( N = 67) was surveyed about discussion partners within the group. An autologistic actor attribute model was used to examine social network patterns of L2 WTC. As hypothesized, students involved in reciprocal structures reported stronger L2 WTC, as well as those in brokerage positions between larger social clusters. Contrary to initial hypotheses, local forms of brokerage held a negative association with WTC, suggesting the possible role of network closure. Results indicate that communicativeness is supported by tight-knit predictable exchanges, and by being in a position to influence the social diffusion of information.

scholarly journals An Empirical Study on the Current Feeder Shipping Network Patterns among Malaysian Feeder Service Providers

2017 ◽  
Vol 33 (4) ◽  
pp. 177-188
Author(s):  
Muhamad Nasir Rahmatdin ◽  
Noorul Shaiful Fitri Abdul Rahman ◽  
Mohammad Khairuddin Othman
Keyword(s):  
Empirical Study ◽  
Service Providers ◽  
Network Patterns

scholarly journals Tracking mood fluctuations with functional network patterns

2018 ◽  
Vol 14 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Nykan Mirchi ◽  
Richard F Betzel ◽  
Boris C Bernhardt ◽  
Alain Dagher ◽  
Bratislav Mišić
Keyword(s):  
Functional Network ◽  
Network Patterns
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