scholarly journals How social network structure affects decision-making in Drosophila melanogaster

2016 ◽  
Vol 283 (1826) ◽  
pp. 20152954 ◽  
Author(s):  
Cristian Pasquaretta ◽  
Marine Battesti ◽  
Elizabeth Klenschi ◽  
Christophe A. H. Bousquet ◽  
Cedric Sueur ◽  
...  
Keyword(s):  
Decision Making ◽  
Drosophila Melanogaster ◽  
Social Network ◽  
Individual Decision ◽  
Social Network Structure ◽  
The Social ◽  
Survival And Reproduction ◽  
Crucial Information ◽  
Social Encounters ◽  
Selective Information

Animals use a number of different mechanisms to acquire crucial information. During social encounters, animals can pass information from one to another but, ideally, they would only use information that benefits survival and reproduction. Therefore, individuals need to be able to determine the value of the information they receive. One cue can come from the behaviour of other individuals that are already using the information. Using a previous extended dataset, we studied how individual decision-making is influenced by the behaviour of conspecifics in Drosophila melanogaster . We analysed how uninformed flies acquire and later use information about oviposition site choice they learn from informed flies. Our results suggest that uninformed flies adjust their future choices based on how coordinated the behaviours of the informed individuals they encounter are. Following social interaction, uninformed flies tended either to collectively follow the choice of the informed flies or to avoid it. Using social network analysis, we show that this selective information use seems to be based on the level of homogeneity of the social network. In particular, we found that the variance of individual centrality parameters among informed flies was lower in the case of a ‘follow’ outcome compared with the case of an ‘avoid’ outcome.

scholarly journals Formation of raiding parties for intergroup violence is mediated by social network structure

2016 ◽  
Vol 113 (43) ◽  
pp. 12114-12119 ◽  
Author(s):  
Luke Glowacki ◽  
Alexander Isakov ◽  
Richard W. Wrangham ◽  
Rose McDermott ◽  
James H. Fowler ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Social Dynamics ◽  
Small Scale ◽  
East African ◽  
Nomadic Pastoralists ◽  
Social Network Structure ◽  
The Social ◽  
Total Impact ◽  
Social Network Position

Intergroup violence is common among humans worldwide. To assess how within-group social dynamics contribute to risky, between-group conflict, we conducted a 3-y longitudinal study of the formation of raiding parties among the Nyangatom, a group of East African nomadic pastoralists currently engaged in small-scale warfare. We also mapped the social network structure of potential male raiders. Here, we show that the initiation of raids depends on the presence of specific leaders who tend to participate in many raids, to have more friends, and to occupy more central positions in the network. However, despite the different structural position of raid leaders, raid participants are recruited from the whole population, not just from the direct friends of leaders. An individual’s decision to participate in a raid is strongly associated with the individual’s social network position in relation to other participants. Moreover, nonleaders have a larger total impact on raid participation than leaders, despite leaders’ greater connectivity. Thus, we find that leaders matter more for raid initiation than participant mobilization. Social networks may play a role in supporting risky collective action, amplify the emergence of raiding parties, and hence facilitate intergroup violence in small-scale societies.

The social network structure of a semi-free roaming European bison herd (Bison bonasus)

2019 ◽  
Vol 158 ◽  
pp. 97-105 ◽  
Author(s):  
Amandine Ramos ◽  
Lola Manizan ◽  
Esther Rodriguez ◽  
Yvonne J.M. Kemp ◽  
Cédric Sueur
Keyword(s):  
Social Network ◽  
Network Structure ◽  
European Bison ◽  
Bison Bonasus ◽  
Social Network Structure ◽  
The Social

Social Network Analysis

2021 ◽  
pp. 155-184
Author(s):  
Yuh-Wen Chen
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Multiple Criteria Decision Making ◽  
Multiple Objective ◽  
Self Organizing Map ◽  
Social Communities ◽  
The Social ◽  
Long Time

Social network analysis (SNA) is an attractive problem for a long time when social communities were popular since 2010. Scholars like to explore the meaning behind the numerous interactions generated at these social media sites. The primary and essential issue of SNA is to monitor, estimate, and engage the potential influencers who are most relevant and active to network. If we can analyze the social network this way, business enterprises could use minimal efforts to sustain the activity of influential users, improve sales, and enhance their reputations. In this chapter, a research framework based on multiple-criteria decision making (MCDM) is proposed. The authors will show how scholars could use dynamic self-organizing map (SOM) based on multiple-objective evolving algorithm (MOEA) and static weighted influence non-linear gauge system (WINGS) to analyze a social network. Finally, comparisons are made between the innovative approaches and the methods in tradition.

Using Network Analysis for Understanding How Decisions are Made

2011 ◽  
pp. 950-957
Author(s):  
Frédéric Adam
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Decision Aids ◽  
Network Approach ◽  
Organizational Decision Making ◽  
Traditional Research ◽  
The Social ◽  
High Level

Network analysis, a body of research that concentrates on the social networks that connect actors in society, has been found to have many applications in areas where researchers struggle to understand the complex workings of organisations (Nohria, 1992). Social network analysis (SNA) acknowledges that individuals are characterised just as much by their relationships with one another (which is often neglected in traditional research) as by their specific attributes (Knoke & Kuklinski, 1982) and that, beyond individuals, society itself is made of networks (Kilduff & Tsai, 2003). It is the study of the relationships between actors and between clusters of actors in organisations and in society that has been labeled network analysis. These high level observations about network analysis indicate that this orientation has great potential for the study of how managers, groups of managers, and organisations make decisions, following processes that unfold over long periods of time and that are sometimes very hard to fully comprehend without reference to a network approach. This article proposes to investigate the potential application of network analysis to the study of individual and organizational decision making and to leverage its strengths for the design and development of better decision aids.

scholarly journals Infectious disease and sickness behaviour: tumour progression affects interaction patterns and social network structure in wild Tasmanian devils

2020 ◽  
Vol 287 (1940) ◽  
pp. 20202454
Author(s):  
David G. Hamilton ◽  
Menna E. Jones ◽  
Elissa Z. Cameron ◽  
Douglas H. Kerlin ◽  
Hamish McCallum ◽  
...  
Keyword(s):  
Social Network ◽  
Cancer Progression ◽  
Population Change ◽  
Tumour Progression ◽  
Interaction Patterns ◽  
Social Network Structure ◽  
Devil Facial Tumour Disease ◽  
The Social ◽  
Transmissible Cancer ◽  
Host Behaviour

Infectious diseases, including transmissible cancers, can have a broad range of impacts on host behaviour, particularly in the latter stages of disease progression. However, the difficulty of early diagnoses makes the study of behavioural influences of disease in wild animals a challenging task. Tasmanian devils ( Sarcophilus harrisii ) are affected by a transmissible cancer, devil facial tumour disease (DFTD), in which tumours are externally visible as they progress. Using telemetry and mark–recapture datasets, we quantify the impacts of cancer progression on the behaviour of wild devils by assessing how interaction patterns within the social network of a population change with increasing tumour load. The progression of DFTD negatively influences devils' likelihood of interaction within their network. Infected devils were more active within their network late in the mating season, a pattern with repercussions for DFTD transmission. Our study provides a rare opportunity to quantify and understand the behavioural feedbacks of disease in wildlife and how they may affect transmission and population dynamics in general.

scholarly journals Social Comparisons are Associated with Poorer and Riskier Financial Decision Making, no Matter whether Encounters are Sporadic or Repeated

2016 ◽  
Vol 19 ◽  
Author(s):  
Alfonso Barrós-Loscertales ◽  
Antonio M. Espín ◽  
José C. Perales
Keyword(s):  
Decision Making ◽  
Social Interaction ◽  
Financial Risk ◽  
Social Comparisons ◽  
Social Conditions ◽  
Financial Decisions ◽  
The Social ◽  
Binary Choices ◽  
Social Encounters ◽  
Financial Decision

AbstractPrevious research suggests that social comparisons affect decision making under uncertainty. However, the role of the length of the social interaction for this relationship remains unknown. This experiment tests the effect of social comparisons on financial risk taking and how this effect is modulated by whether social encounters are sporadic or repeated. Participants carried out a computer task consisting of a series of binary choices between lotteries of varying profitability and risk, with real monetary stakes. After each decision, participants could compare their own payoff to that of a counterpart who made the same decision at the same time and whose choices/earnings did not affect the participants’ earnings. The design comprised three between-subjects treatments which differed in the nature of the social interaction: participants were informed that they would be matched with either (a) a different participant in each trial, (b) the same participant across all trials, or (c) a “virtual participant”, i.e., a computer algorithm. Compared to the non-social condition (c), subjects in both social conditions (a and b) chose lotteries with lower expected value (z = –3.10, p < .01) and higher outcome variance (z = 2.13, p = .03). However, no differences were found between the two social conditions (z = 1.15, p = .25 and z = 0.35, p = .73, respectively). These results indicate that social comparison information per se leads to poorer and riskier financial decisions, irrespective of whether or not the referent other is encountered repeatedly.

scholarly journals Offspring social network structure predicts fitness in families

2012 ◽  
Vol 279 (1749) ◽  
pp. 4914-4922 ◽  
Author(s):  
Nick J. Royle ◽  
Thomas W. Pike ◽  
Philipp Heeb ◽  
Heinz Richner ◽  
Mathias Kölliker
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Conflicts Of Interest ◽  
Parus Major ◽  
Social Structures ◽  
Emergent Properties ◽  
Social Network Structure ◽  
The Social ◽  
The Individual

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

The social network structure of a wild meerkat population: 2. Intragroup interactions

2009 ◽  
Vol 64 (1) ◽  
pp. 81-95 ◽  
Author(s):  
Joah R. Madden ◽  
Julian A. Drewe ◽  
Gareth P. Pearce ◽  
Tim H. Clutton-Brock
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Social Network Structure ◽  
The Social

Estimating Policy Positions Using Social Network Data

2016 ◽  
Vol 35 (1) ◽  
pp. 53-67 ◽  
Author(s):  
Alejandro Ecker
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Science Research ◽  
Policy Position ◽  
Policy Positions ◽  
Political Actors ◽  
External Data ◽  
Social Network Structure ◽  
Big Data Applications ◽  
The Social

Social network site (SNS) data provide scholars with a plethora of new opportunities for studying public opinion and forecasting electoral outcomes. While these are certainly among the most promising big data applications in political science research, a series of pioneering studies have started to uncover the vast potential of such data to estimate the policy positions of political actors. Adding to this emerging strand in the scholarly literature, the present article explores the validity of (individual) policy positions derived from the social network structure of the microblogging platform Twitter. At the aggregate party level, cross-validation with external data sources suggests that SNS data provide valid policy position estimates. In contrast, the empirical analysis reveals only a moderate connection between individual policy positions retrieved from the social network structure and those retrieved from members of parliament individual voting record. These results thus highlight the potential as well as important limitations of SNS data in indicating the policy positions of political parties and individual legislators.

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