scholarly journals Shadowing and shielding: Effective heuristics for continuous influence maximisation in the voting dynamics

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252515
Author(s):  
Guillermo Romero Moreno ◽  
Sukankana Chakraborty ◽  
Markus Brede
Keyword(s):  
Political Competition ◽  
Explanatory Power ◽  
Opinion Dynamics ◽  
Fixed Number ◽  
Pure Nash Equilibrium ◽  
Information Campaigns ◽  
Continuous Regime ◽  
Optimal Allocations ◽  
Game Theoretic ◽  
Continuous Strategies

Influence maximisation, or how to affect the intrinsic opinion dynamics of a social group, is relevant for many applications, such as information campaigns, political competition, or marketing. Previous literature on influence maximisation has mostly explored discrete allocations of influence, i.e. optimally choosing a finite fixed number of nodes to target. Here, we study the generalised problem of continuous influence maximisation where nodes can be targeted with flexible intensity. We focus on optimal influence allocations against a passive opponent and compare the structure of the solutions in the continuous and discrete regimes. We find that, whereas hub allocations play a central role in explaining optimal allocations in the discrete regime, their explanatory power is strongly reduced in the continuous regime. Instead, we find that optimal continuous strategies are very well described by two other patterns: (i) targeting the same nodes as the opponent (shadowing) and (ii) targeting direct neighbours of the opponent (shielding). Finally, we investigate the game-theoretic scenario of two active opponents and show that the unique pure Nash equilibrium is to target all nodes equally. These results expose fundamental differences in the solutions to discrete and continuous regimes and provide novel effective heuristics for continuous influence maximisation.

scholarly journals Health and Voting in Rural America

2021 ◽  
Vol 3 ◽  
Author(s):  
Katie A. Cahill ◽  
Christopher Ojeda
Keyword(s):  
Rural Communities ◽  
Voter Turnout ◽  
Political Competition ◽  
Explanatory Power ◽  
Negative Effects ◽  
Individual Level ◽  
Important Variation ◽  
Level Data ◽  
Rural Places ◽  
The Impact

This research explores the impact of health on voter turnout, with the goal of uncovering important variation in dynamics across rural communities. Drawing on the results of county and individual-level analyses, including novel survey data from an Appalachian community, this study finds that health matters less for rural voters. Models using county-level data indicate that poor health is significantly and negatively related to voter turnout across counties, even when controlling for educational attainment, poverty, diversity, and political competition. However, health loses its explanatory power in rural counties once a control for religiosity is introduced. Health is also a less important predictor in rural places where there is a high cost of voting, a finding counter to the notion that high costs would uniformly amplify the negative effects of health disparities. Models using individual-level data provide support for many of these findings, while also generating new insights into the complexity of rural political behavior. Overall, this study suggests that place has an important role in understanding the engagement of American voters.

scholarly journals The impact of noise and topology on opinion dynamics in social networks

2021 ◽  
Vol 8 (4) ◽  
Author(s):  
Samuel Stern ◽  
Giacomo Livan
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Peer Influence ◽  
Linear Models ◽  
Explanatory Power ◽  
Opinion Dynamics ◽  
And Topology ◽  
Stochastic Setting ◽  
The Impact ◽  
Do So

We investigate the impact of noise and topology on opinion diversity in social networks. We do so by extending well-established models of opinion dynamics to a stochastic setting where agents are subject both to assimilative forces by their local social interactions, as well as to idiosyncratic factors preventing their population from reaching consensus. We model the latter to account for both scenarios where noise is entirely exogenous to peer influence and cases where it is instead endogenous, arising from the agents’ desire to maintain some uniqueness in their opinions. We derive a general analytical expression for opinion diversity, which holds for any network and depends on the network’s topology through its spectral properties alone. Using this expression, we find that opinion diversity decreases as communities and clusters are broken down. We test our predictions against data describing empirical influence networks between major news outlets and find that incorporating our measure in linear models for the sentiment expressed by such sources on a variety of topics yields a notable improvement in terms of explanatory power.

DON and Shapley Value for Allocation among Cooperating Agents in a Network: Conditions for Equivalence

2017 ◽  
Vol 5 (2) ◽  
pp. 143-161 ◽  
Author(s):  
Sridhar Mandyam ◽  
Usha Sridhar
Keyword(s):  
Social Welfare ◽  
Shapley Value ◽  
Centrality Measures ◽  
Pareto Optimal ◽  
Undirected Network ◽  
Social Welfare Maximization ◽  
Optimal Allocations ◽  
Game Theoretic ◽  
Cooperating Agents ◽  
Pareto Optimal Allocations

In a paper appearing in a recent issue of this journal ( Studies in Microeconomics), the authors explored a new method to allocate a divisible resource efficiently among cooperating agents located at the vertices of a connected undirected network. It was shown in that article that maximizing social welfare of the agents produces Pareto optimal allocations, referred to as dominance over neighbourhood (DON), capturing the notion of dominance over neighbourhood in terms of network degree. In this article, we show that the allocation suggested by the method competes well with current cooperative game-theoretic power centrality measures. We discuss the conditions under which DON turns exactly equivalent to a recent ‘fringe-based’ Shapley Value formulation for fixed networks, raising the possibility of such solutions being both Pareto optimal in a utilitarian social welfare maximization sense as well as fair in the Shapley value sense.

scholarly journals Simulating Hidden Dynamics. Introducing Agent-Based Models as a tool for linkage analysis

2019 ◽  
Author(s):  
Martin Wettstein
Keyword(s):  
Linkage Analysis ◽  
Media Effects ◽  
Measurement Errors ◽  
Explanatory Power ◽  
Opinion Dynamics ◽  
Field Conditions ◽  
Panel Surveys ◽  
Agent Based ◽  
Linkage Analyses ◽  
Promising Tool

Linkage analyses use data from panel surveys and content analyses to assess media effects under field conditions and are able to close the gap between experimental and survey-based media effects research. Results from current studies and simulations indicate, however, that these studies systematically under-estimate real media effects as they aggregate measurement errors and reduce the complexity of media content. In response to these issues, we propose a new method for linkage analysis which applies agent-based simulations to directly assess short-term media effects using empirical data as guideposts.Results from an example study modeling opinion dynamics in the run-up of a Swiss referendum show that this method outperforms traditional regression-based linkage analyses in detail and explanatory power. In spite of the time-consuming modeling and computation process, this approach is a promising tool to study individual media effects under field conditions.

scholarly journals Airline Booking Limit Competition Game Under Differentiated Fare Structure

2017 ◽  
Vol 33 (3) ◽  
pp. 615-622 ◽  
Author(s):  
Joonkyum Lee ◽  
Bumsoo Kim
Keyword(s):  
Nash Equilibrium ◽  
Airline Industry ◽  
Relative Magnitude ◽  
Theoretic Approach ◽  
Pure Nash Equilibrium ◽  
Initial Allocation ◽  
Best Response ◽  
Booking Limits ◽  
Game Theoretic ◽  
Game Theoretic Approach

We address a two-firm booking limit competition game in the airline industry. We assume aggregate common demand, and differentiated ticket fare and capacity, to make this study more realistic. A game theoretic approach is used to analyze the competition game. The optimal booking limits and the best response functions are derived. We show the existence of a pure Nash equilibrium and provide the closed-form equilibrium solution. The location of the Nash equilibrium depends on the relative magnitude of the ratios of the full and discount fares. We also show that the sum of the booking limits of the two firms remains the same regardless of the initial allocation proportion of the demand.

scholarly journals Simulating hidden dynamics : Introducing Agent-Based Models as a tool for linkage analysis

2020 ◽  
Vol 2 (1) ◽  
pp. 1-33
Author(s):  
Martin Wettstein
Keyword(s):  
Linkage Analysis ◽  
Media Effects ◽  
Measurement Errors ◽  
Explanatory Power ◽  
Opinion Dynamics ◽  
Field Conditions ◽  
Panel Surveys ◽  
Agent Based ◽  
Linkage Analyses ◽  
Promising Tool

Abstract Linkage analyses use data from panel surveys and content analyses to assess media effects under field conditions and are able to close the gap between experimental and survey-based media effects research. Results from current studies and simulations indicate, however, that these studies systematically under-estimate real media effects as they aggregate measurement errors and reduce the complexity of media content. In response to these issues, we propose a new method for linkage analysis which applies agent-based simulations to directly assess short-term media effects using empirical data as guideposts. Results from an example study modeling opinion dynamics in the run-up of a Swiss referendum show that this method outperforms traditional regression-based linkage analyses in detail and explanatory power. In spite of the time-consuming modeling and computation process, this approach is a promising tool to study individual media effects under field conditions.

MODELING BELIEF CHANGE IN A POPULATION USING EXPLANATORY COHERENCE

2012 ◽  
Vol 15 (06) ◽  
pp. 1250085 ◽  
Author(s):  
BRUCE EDMONDS
Keyword(s):  
Belief Change ◽  
Coherence Function ◽  
Opinion Dynamics ◽  
Fixed Number ◽  
Core Beliefs ◽  
Large Set ◽  
Shared Beliefs ◽  
The Social ◽  
Explanatory Coherence ◽  
Group Opinion

A simulation model that represents belief change within a population of agents who are connected by a social network is presented based on Thagard's theory of explanatory coherence. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These are conceived of existing against a background of a large set of (unrepresented) shared beliefs. These beliefs are to different extents coherent with each other — this is modeled using a coherence function from possible sets of core beliefs to [-1, 1]. The social influence is achieved through gaining of a belief across a social link. Beliefs can be lost by being dropped from an agent's store. Both of these processes happen with a probability related to the change in coherence that would result in an agent's belief store. A resulting measured "opinion" can be retrieved in a number of ways, here as a weighted sum of a pattern of the core beliefs — opinion is thus an outcome and not directly processed by agents. This model suggests hypotheses about group opinion dynamics that differ from that of many established models.

scholarly journals Convergence of Learning Dynamics in Information Retrieval Games

2019 ◽  
Vol 33 ◽  
pp. 1780-1787
Author(s):  
Omer Ben-Porat ◽  
Itay Rosenberg ◽  
Moshe Tennenholtz
Keyword(s):  
Information Retrieval ◽  
Theoretic Model ◽  
Pure Nash Equilibrium ◽  
Ranking Methods ◽  
Learning Dynamics ◽  
Active Selection ◽  
Current State ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
Selection Of

We consider a game-theoretic model of information retrieval with strategic authors. We examine two different utility schemes: authors who aim at maximizing exposure and authors who want to maximize active selection of their content (i.e., the number of clicks). We introduce the study of author learning dynamics in such contexts. We prove that under the probability ranking principle (PRP), which forms the basis of the current state-of-the-art ranking methods, any betterresponse learning dynamics converges to a pure Nash equilibrium. We also show that other ranking methods induce a strategic environment under which such a convergence may not occur.

Solving a Potential Clustering Game

2019 ◽  
Vol 28 (02) ◽  
pp. 1950006
Author(s):  
Kahina Bouchama ◽  
Arnaud Lallouet ◽  
Mohammed Said Radjef ◽  
Lakhdar Sais
Keyword(s):  
Data Clustering ◽  
Quality Measures ◽  
Unsupervised Classification ◽  
Potential Game ◽  
Pure Nash Equilibrium ◽  
Best Response ◽  
Clustering Quality ◽  
Game Theoretic ◽  
Clustering Approach

Data clustering is the unsupervised classification of a set of objects into groups (clusters), according to their similarities. This can be seen as a form of equilibrium, which is the motivation that led to recent formulations of the data clustering task using game theoretic models. In this context, we propose a novel game-theoretic clustering approach reducing the clustering task to that of searching for a pure Nash equilibrium of a potential game, which corresponds to a stable clustering. Interestingly, the existence and the convergence towards such equilibrium are established, and we experimentally prove that such stability is not always guaranteed by the classical k-means algorithm. We also propose an iterative best-response algorithm for solving this potential clustering game. This algorithm is implemented and tested on several real-world and artificial datasets. Considering most of clustering quality measures, the obtained results are compared to those provided by both the classical k-means and by an hybridization of these two algorithms.

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