scholarly journals A longitudinal network analysis of social dynamics in rookscorvus frugilegus: repeated group modifications do not affect social network in captive rooks

2016 ◽  
pp. zow083 ◽  
Author(s):  
Palmyre H. Boucherie ◽  
Sebastian Sosa ◽  
Cristian Pasquaretta ◽  
Valérie Dufour
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Social Dynamics ◽  
Longitudinal Network Analysis

Dynamics and Evolutional Patterns of Social Networks

2011 ◽  
pp. 156-170
Author(s):  
Yingzi Jin ◽  
Yutaka Matsuo
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Real World ◽  
Dynamic Network ◽  
Network Evolution ◽  
Belief Formation ◽  
Network Mining ◽  
Longitudinal Network Analysis ◽  
Relational Network

Previous chapters focused on the models of static networks, which consider a relational network at a given point in time. However, real-world social networks are dynamic in nature; for example, friends of friends become friends. Social network research has, in recent years, paid increasing attention to dynamic and longitudinal network analysis in order to understand network evolution, belief formation, friendship formation, and so on. This chapter focuses mainly on the dynamics and evolutional patterns of social networks. The chapter introduces real-world applications and reviews major theories and models of dynamic network mining.

scholarly journals Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter

2021 ◽  
Vol 4 ◽  
Author(s):  
Quirin Würschinger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Dynamics ◽  
Temporal Dynamics ◽  
New Words ◽  
Network Analyses ◽  
The Social ◽  
Lexical Innovation ◽  
Social Diffusion

Societies continually evolve and speakers use new words to talk about innovative products and practices. While most lexical innovations soon fall into disuse, others spread successfully and become part of the lexicon. In this paper, I conduct a longitudinal study of the spread of 99 English neologisms on Twitter to study their degrees and pathways of diffusion. Previous work on lexical innovation has almost exclusively relied on usage frequency for investigating the spread of new words. To get a more differentiated picture of diffusion, I use frequency-based measures to study temporal aspects of diffusion and I use network analyses for a more detailed and accurate investigation of the sociolinguistic dynamics of diffusion. The results show that frequency measures manage to capture diffusion with varying success. Frequency counts can serve as an approximate indicator for overall degrees of diffusion, yet they miss important information about the temporal usage profiles of lexical innovations. The results indicate that neologisms with similar total frequency can exhibit significantly different degrees of diffusion. Analysing differences in their temporal dynamics of use with regard to their age, trends in usage intensity, and volatility contributes to a more accurate account of their diffusion. The results obtained from the social network analysis reveal substantial differences in the social pathways of diffusion. Social diffusion significantly correlates with the frequency and temporal usage profiles of neologisms. However, the network visualisations and metrics identify neologisms whose degrees of social diffusion are more limited than suggested by their overall frequency of use. These include, among others, highly volatile neologisms (e.g., poppygate) and political terms (e.g., alt-left), whose use almost exclusively goes back to single communities of closely-connected, like-minded individuals. I argue that the inclusion of temporal and social information is of particular importance for the study of lexical innovation since neologisms exhibit high degrees of temporal volatility and social indexicality. More generally, the present approach demonstrates the potential of social network analysis for sociolinguistic research on linguistic innovation, variation, and change.

scholarly journals A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1229
Author(s):  
Liliana Fadul-Pacheco ◽  
Michael Liou ◽  
Douglas J. Reinemann ◽  
Victor E. Cabrera
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Milk Production ◽  
Social Dynamics ◽  
Preliminary Investigation ◽  
Dairy Farm ◽  
The Social ◽  
Automatic Milking System ◽  
Automatic Milking

We have applied social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). The SNA was applied to social groups defined by four pens on a dairy farm, each served by an automatic milking system (AMS). Each pen was equipped with an automatic sorting gate that identified when cows voluntarily moved from the resting area to either milking or feeding areas. The aim of this study was two-fold: to determine if SNA could identify affinity pairs and to determine if milk production was affected when affinity pairs where broken. Cow traffic and milking performance data from a commercial guided-flow AMS dairy farm were used. Average number of milked cows was 214 ± 34, distributed in four AMS over 1 year. The SNA was able to identify clear affinity pairs and showed when these pairings were formed and broken as cows entered and left the social group (pen). The trend in all four pens was toward higher-than-expected milk production during periods of affinity. Moreover, we found that when affinities were broken (separation of cow pairs) the day-to-day variability in milk production was three times higher than for cows in an affinity pair. The results of this exploratory study suggest that SNA could be potentially used as a tool to reduce milk yield variation and better understand the social dynamics of dairy cows supporting management and welfare decisions.

scholarly journals Seven decades of chemotherapy clinical trials: a pan-cancer social network analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xuanyi Li ◽  
Elizabeth A. Sigworth ◽  
Adrianne H. Wu ◽  
Jess Behrens ◽  
Shervin A. Etemad ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Effects ◽  
Social Dynamics ◽  
Scale Free ◽  
High Profile ◽  
The People ◽  
The Social

Abstract Clinical trials establish the standard of cancer care, yet the evolution and characteristics of the social dynamics between the people conducting this work remain understudied. We performed a social network analysis of authors publishing chemotherapy-based prospective trials from 1946 to 2018 to understand how social influences, including the role of gender, have influenced the growth and development of this network, which has expanded exponentially from fewer than 50 authors in 1946 to 29,197 in 2018. While 99.4% of authors were directly or indirectly connected by 2018, our results indicate a tendency to predominantly connect with others in the same or similar fields, as well as an increasing disparity in author impact and number of connections. Scale-free effects were evident, with small numbers of individuals having disproportionate impact. Women were under-represented and likelier to have lower impact, shorter productive periods (P < 0.001 for both comparisons), less centrality, and a greater proportion of co-authors in their same subspecialty. The past 30 years were characterized by a trend towards increased authorship by women, with new author parity anticipated in 2032. The network of cancer clinical trialists is best characterized as strategic or mixed-motive, with cooperative and competitive elements influencing its appearance. Network effects such as low centrality, which may limit access to high-profile individuals, likely contribute to the observed disparities.

A Canonical Action Research Approach to the Effective Diffusion of Information Security with Social Network Analysis

2017 ◽  
Vol 4 (2) ◽  
pp. 22-43
Author(s):  
Duy Dang Pham Thien ◽  
Karlheinz Kautz ◽  
Siddhi Pittayachawan ◽  
Vince Bruno
Keyword(s):  
Social Network ◽  
Action Research ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Security ◽  
Social Dynamics ◽  
Effective Diffusion ◽  
Research Approach ◽  
Action Research Approach ◽  
Effective Use

As modern organisations are using strategic information systems as their competitive advantage, the management of information security (IS) is regarded as a top priority. However, technical measures are no longer sufficient for protecting IS, and the prevalence of centralised IS controls and top-down approach in IS management are challenged by the dynamic socio-organisational environment. In this article, a canonical action research (CAR) project discusses the use of social network analysis (SNA) methods to design and implement a cascading IS training/diffusion, which leveraged the social dynamics in the workplace to enhance the IS-related interactions between the employees in a large construction organisation in Southeast Asia. Through the enhanced IS interactions, which involved the employees' provisions of IS resources and IS influence, results indicated an improvement in the employees' attitudes towards IS. The research outcomes advocated the effective use of SNA methods, in combination with the CAR approach, which included the network metrics and means to select the suitable champions for the diffusion of IS, as well as to measure the diffusion effectiveness. Future directions to develop new IS-related network theories and apply SNA methods to study other IS concepts are also discussed.

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