scholarly journals Overchoosing: A Mechanism of Tie-Formation in Social Networks

2020 ◽  
Author(s):  
Tasuku Igarashi ◽  
Johank Koskinen
Keyword(s):  
Social Networks ◽  
Formation Process ◽  
Goodness Of Fit ◽  
Network Data ◽  
Formation Processes ◽  
Friendship Network ◽  
Fundamental Mechanism

We introduce the concept of overchoosing as a fundamental mechanism of tie formation in directed social networks. The parameter represents a tendency for actors to send a lot of ties but receive few nominations back, something which implies the importance of modeling reciprocity violation as a basic tie-formation process. Analyzing large friendship network data (N = 1,575) by the stochastic actor-oriented models revealed that, under controlling for several endogenous tie formation processes, the parameter captured the formation of open triads and substantially improved the goodness of fit of the model to the data.

BEHAVIORAL FOUNDATIONS AND EQUILIBRIUM NOTIONS FOR SOCIAL NETWORK FORMATION PROCESSES

2004 ◽  
Vol 07 (01) ◽  
pp. 77-92 ◽  
Author(s):  
NICOLAS CARAYOL ◽  
PASCALE ROUX
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Formation Process ◽  
Network Formation ◽  
Small World ◽  
Payoff Function ◽  
Formation Processes ◽  
Limiting Distributions ◽  
Stochastically Stable ◽  
Social Network Formation

This paper develops a framework for studying social network formation. Partly built upon a formalism used in theoretical economics, the network formation process we introduce is locally driven by agents who maximize a given individual payoff function. We examine two simple models and observe the limiting distributions of stochastically stable networks. We find that these networks share some of the features observed for social networks. In particular, we find critical values of the parameters for which the selected networks exhibit small world properties.

scholarly journals Word-Formation Process on COVID-19 Related Terms as Japanese Language Variation

IZUMI ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 304-315
Author(s):  
Nadya Inda Syartanti
Keyword(s):  
Formation Process ◽  
Word Formation ◽  
Formation Processes ◽  
Preventive Action ◽  
Distribution Method ◽  
Disease Information ◽  
Multiple Processes ◽  
Source Data ◽  
Data Source ◽  
Observation Method

This research aims to identify the types of vocabulary in Japanese, to explore the word-formation process, and to analyse the function of COVID-19 related terms conveyed by various content creators on YouTube channels, from Japan and Indonesia. The seven YouTube channel accounts are Aki no Sora (Indonesia), po.n.go_id or Pocket Nihongo (Indonesia), Sakura Pinku (Indonesia), Wagomu (Indonesia), Omoshiroi Nihongo (Japan), Japanese Ammo with Misa (Japan), and Coto Academy (Japan that used as the data source. Data were collected using the observation method and analysed by the distribution method. The results showed that the COVID-19 related terms are dominated by the type of vocabulary kango as the form or type of vocabulary that is most widely used in matching the COVID-19 related term. Among all word-formation processes, the COVID-19 terms in Japanese identified as borrowing, compounding, and multiple processes. However, the multiple word-formation processes are dominated on COVID-19 terms in Japanese. It related to the domination of the type of kango used. From that, there are multiple functions that are included in COVID-19 terms in Japanese, namely disease information, preventive action, symptom, and announcement. Therefore, this research can be contributed to data analysis, which used morphological analysis in Japanese terms.

Network Perspectives on Crime

2017 ◽  
Author(s):  
Jason Gravel ◽  
George E. Tita
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Peer Influence ◽  
Criminal Behavior ◽  
Social Ties ◽  
Organizational Level ◽  
Network Data ◽  
Adult Health ◽  
The Individual

Though often not mentioned by name, the importance of social networks in explaining criminal behavior, delinquency, and patterns has long been recognized in the study of crime. Theories that explain criminal behavior at the individual level being learned through the impacts of peer influences presume that the transmission of ideas and influences flow among social ties (networks) that link individuals. Cultural theories of crime work in the same way. At the community level, delinquency and criminal behavior are born among members of a community or group that adhere to a particular cultural set of norms or beliefs. The concentration of crime in particular geographic areas results when there are insufficient ties among local residents to affect informal social control in the area. Impacted neighborhoods are often described as socially isolated, lacking social ties to institutions of power that provide the investment and services needed in a healthy community. The history of the formation and activities of street gangs is a clear example of how understanding the ties among individuals, and between groups of these individuals, matter in our understanding these phenomena. Comprehending social ties among gangs and gang members and employment of social network analysis (SNA) have become mainstays of local law enforcement efforts to address the issue of gang violence. Much of the early criminological work that implicated social networks but did not explicitly acknowledge a network by name, or did not employ SNA on formal network data, did so because collecting such data is difficult at best and sometimes impossible. Though criminology has been a “late adopter” of SNA, the field is making great strides in this area. The National Longitudinal Study of Adolescent to Adult Health (Add Health) research program has provided a rich set of network data to explore issues of peer influence. Researchers are using carefully collected social network data at the individual and organizational level to better understand the ability of communities to self-regulate delinquency and crime in an area. Arrest data and field identification stops are being used to generate large networks in an effort to understand how one’s position in a larger social structure might be related to an actor’s involvement in future offending or victimization. As the field of criminology continues to adopt a network perspective in the study of crime, it is important to understand the development of social networks within the field. Critically examining the strengths and weaknesses of network data, especially in terms of the process by which data are generated, can lead to better applications of network analysis in the future.

Influences of End Surface Angle of Workpiece on Burr Formation in High Speed Machining

2009 ◽  
Vol 69-70 ◽  
pp. 384-388
Author(s):  
Qin Xi Shen ◽  
Gui Cheng Wang ◽  
Hai Jun Qu ◽  
Yun Ming Zhu
Keyword(s):  
Aluminum Alloy ◽  
Formation Process ◽  
High Speed ◽  
Shear Angle ◽  
Burr Formation ◽  
High Speed Machining ◽  
Formation Processes ◽  
Key Factors ◽  
2024 Aluminum Alloy ◽  
Surface Angle

The end surface angle of workpece is one of key factors that affect burr sizes and shapes. In this paper, the burr formation process of different end surface angle is simulated with elastic plastic nonlinear element method based on ABAQUS. The influence of end surface angle of workpiece on burr formation processes in high-speed machining 2024 Aluminum alloy is analyzed. The influence of end surface angle on burr sizes and shapes is studied based on equivalent shear strain and negative shear angle. The results have investigated the mechanisms of burr formation fundamentally, which is the basis of burr minimization.

Social networks in arid Australia: a review of concepts and evidence

2008 ◽  
Vol 30 (1) ◽  
pp. 167 ◽  
Author(s):  
R. R. J. McAllister ◽  
B. Cheers ◽  
T. Darbas ◽  
J. Davies ◽  
C. Richards ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Natural Resources ◽  
Social Structure ◽  
West Coast ◽  
Arid Regions ◽  
Weak Links ◽  
Network Data ◽  
Semi Arid

Arid systems are markedly different from non-arid systems. This distinctiveness extends to arid-social networks, by which we mean social networks which are influenced by the suite of factors driving arid and semi-arid regions. Neither the process of how aridity interacts with social structure, nor what happens as a result of this interaction, is adequately understood. This paper postulates three relative characteristics which make arid-social networks distinct: that they are tightly bound, are hierarchical in structure and, hence, prone to power abuses, and contain a relatively higher proportion of weak links, making them reactive to crisis. These ideas were modified from workshop discussions during 2006. Although they are neither tested nor presented as strong beliefs, they are based on the anecdotal observations of arid-system scientists with many years of experience. This paper does not test the ideas, but rather examines them in the context of five arid-social network case studies with the aim of hypotheses building. Our cases are networks related to pastoralism, Aboriginal outstations, the ‘Far West Coast Aboriginal Enterprise Network’ and natural resources in both the Lake-Eyre basin and the Murray–Darling catchment. Our cases highlight that (1) social networks do not have clear boundaries, and that how participants perceive their network boundaries may differ from what network data imply, (2) although network structures are important determinants of system behaviour, the role of participants as individuals is still pivotal, (3) and while in certain arid cases weak links are engaged in crisis, the exact structure of all weak links in terms of how they place participants in relation to other communities is what matters.

The 2004 GSS Finding of Shrunken Social Networks: An Artifact?

2009 ◽  
Vol 74 (4) ◽  
pp. 657-669 ◽  
Author(s):  
Claude S. Fischer
Keyword(s):  
Social Networks ◽  
Social Isolation ◽  
General Social Survey ◽  
Network Data ◽  
Technical Error ◽  
Social Survey ◽  
The People

McPherson, Smith-Lovin, and Brashears (2006, 2008b) reported that Americans' social networks shrank precipitously from 1985 to 2004. When asked to list the people with whom they discussed “important matters,” respondents to the 2004 General Social Survey (GSS) provided about one-third fewer names than did respondents in the 1985 survey. Critically, the percentage of respondents who provided no names at all increased from about 10 percent in 1985 to about 25 percent in 2004. The 2004 results contradict other relevant data, however, and they contain serious anomalies; this suggests that the apparently dramatic increase in social isolation is an artifact. One possible source of the artifact is the section of the 2004 interview preceding the network question; it may have been unusually taxing. Another possible source is a random technical error. With as yet no clear account for these inconsistencies and anomalies, scholars should be cautious in using the 2004 network data. Scholars and general readers alike should draw no inference from the 2004 GSS as to whether Americans' social networks changed substantially between 1985 and 2004; they probably did not.

scholarly journals A multi-species repository of social networks

2018 ◽  
Author(s):  
Pratha Sah ◽  
José David Méndez ◽  
Shweta Bansal
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interactions ◽  
Evolutionary Biology ◽  
Quantitative Information ◽  
Network Data ◽  
Data Format ◽  
Invaluable Tool ◽  
Multiple Species ◽  
Taxonomic Groups

AbstractSocial network analysis is an invaluable tool to understand the patterns, evolution, and consequences of sociality. Comparative studies over the spectrum of sociality across taxonomic groups are particularly valuable. Such studies however require quantitative information on social interactions across multiple species which is not easily available. We introduce the Animal Social Network Repository (ASNR) as the first multi-taxonomic repository that collates more than 650 social networks from 47 species, including those of mammals, reptiles, fish, birds, and insects. The repository was created by consolidating social network datasets from the literature on wild and captive animals into a consistent and easy-to-use network data format. The repository is archived at https://bansallab.github.io/asnr/. ASNR has tremendous research potential, including testing hypotheses in the fields of animal ecology, social behavior, epidemiology and evolutionary biology.

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