scholarly journals Betting on the underdog: the influence of social networks on vote choice

2020 ◽  
pp. 1-8
Author(s):  
Annika Fredén ◽  
Ludovic Rheault ◽  
Indridi H. Indridason
Keyword(s):  
Social Networks ◽  
Real Life ◽  
Vote Choice ◽  
Random Networks ◽  
Popular Support ◽  
Treatment Groups ◽  
Echo Chambers ◽  
Simulated Network ◽  
High Degree ◽  
Small Probabilities

Abstract People are commonly expected not to waste their vote on parties with small probabilities of being elected. Yet, many end up voting for underdogs. We argue that voters gauge the popular support for their preferred party from their social networks. When social networks function as echo chambers, a feature observed in real-life networks, voters overestimate underdogs’ chances of winning. We conduct voting experiments in which some treatment groups receive signals from a simulated network. We compare the effect of networks with a high degree of homogeneity against random networks. We find that homophilic networks increase the level of support for underdogs, which provides evidence to back up anecdotal claims that echo chambers foster the development of fringe parties.

scholarly journals Regular Equivalence for Social Networks

2018 ◽  
Vol 9 (1) ◽  
pp. 117 ◽  
Author(s):  
Pieter Audenaert ◽  
Didier Colle ◽  
Mario Pickavet
Keyword(s):  
Social Networks ◽  
Complex Networks ◽  
Efficient Algorithm ◽  
Large Scale ◽  
Real Life ◽  
Equivalence Classes ◽  
Random Networks ◽  
Formal Definition ◽  
Regular Equivalence ◽  
Definition Of

Networks and graphs are highly relevant in modeling real-life communities and their interactions. In order to gain insight in their structure, different roles are attributed to vertices, effectively clustering them in equivalence classes. A new formal definition of regular equivalence is presented in this paper, and the relation with other equivalence types is investigated and mathematically proven. An efficient algorithm is designed, able to detect all regularly equivalent roles in large-scale complex networks. We apply it to both Barabási–Albert random networks, as well as real-life social networks, which leads to interesting insights.

The economic analysis of rationality in the tradition of Harvey Leibenstein

2020 ◽  
pp. 21-38
Author(s):  
Ivan V. Rozmainsky ◽  
Yulia I. Pashentseva
Keyword(s):  
Economic Analysis ◽  
Real Life ◽  
Informal Institutions ◽  
External Information ◽  
Urban Residents ◽  
The Future ◽  
Information Constraints ◽  
High Degree ◽  
Market Capitalism

The paper is devoted to the economic analysis of rationality in the tradition of Harvey Leibenstein: the authors perceive rationality as “calculatedness” when making decisions, while the degree of this “calculatedness” is interpreted as a variable. Thus, this approach does not correspond to the generally accepted neoclassical interpretation of rationality, according to which rationality is both full and constant. The authors believe that such a neoclassical approach makes too stringent requirements for the abilities of people. In real life, people do not behave like calculating machines. The paper discusses various factors limiting the degree of rationality of individuals. One group of factors is associated with external information constraints such as the complexity and extensiveness of information, as well as the uncertainty of the future. Another group of factors is related to informal institutions. In particular, the paper states that the system of planned socialism contributes to less rationality than the system of market capitalism. Thus, in the post-socialist countries, including contemporary Russia, one should not expect a high degree of rationality of the behavior of economic entities. The paper mentions, in particular, the factors of rationality caused by informal institutions, such as the propensity to calculate, the propensity to be independent when making decisions and the propensity to set goals. The authors also believe that people who live on their own are usually more rational than people who share a common household with someone else. This assumption is verified econometrically based on data on young urban residents collected by the authors. It turned out that the behavior of people included in this database, in general, corresponds to what the authors believed.

A psychologically-inspired fuzzy-based approach for user personality prediction in rumor propagation across social networks

2021 ◽  
pp. 1-15
Author(s):  
V. Indu ◽  
Sabu M. Thampi
Keyword(s):  
Social Networks ◽  
Factor Model ◽  
Five Factor Model ◽  
Principal Component ◽  
Common People ◽  
Rumor Propagation ◽  
Usage Patterns ◽  
User Personality ◽  
Personality Prediction ◽  
High Degree

Social networks have emerged as a fertile ground for the spread of rumors and misinformation in recent times. The increased rate of social networking owes to the popularity of social networks among the common people and user personality has been considered as a principal component in predicting individuals’ social media usage patterns. Several studies have been conducted to study the psychological factors influencing the social network usage of people but only a few works have explored the relationship between the user’s personality and their orientation to spread rumors. This research aims to investigate the effect of personality on rumor spread on social networks. In this work, we propose a psychologically-inspired fuzzy-based approach grounded on the Five-Factor Model of behavioral theory to analyze the behavior of people who are highly involved in rumor diffusion and categorize users into the susceptible and resistant group, based on their inclination towards rumor sharing. We conducted our experiments in almost 825 individuals who shared rumor tweets on Twitter related to five different events. Our study ratifies the truth that the personality traits of individuals play a significant role in rumor dissemination and the experimental results prove that users exhibiting a high degree of agreeableness trait are more engaged in rumor sharing activities and the users high in extraversion and openness trait restrain themselves from rumor propagation.

scholarly journals AB0369 EFFICACY AND SAFETY OF RITUXIMAB ORIGINATOR AND BIOSIMILAR IN PRIMARY SJÖGREN’S SYNDROME IN A REAL-LIFE SETTING

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1485.3-1485
Author(s):  
F. Carubbi ◽  
A. Alunno ◽  
P. Cipriani ◽  
V. Pavlych ◽  
C. DI Muzio ◽  
...  
Keyword(s):  
Disease Activity ◽  
Real Life ◽  
Primary Sjögren’S Syndrome ◽  
Efficacy And Safety ◽  
Research Support ◽  
Treatment Groups ◽  
Real Life Setting ◽  
Patient Reported ◽  
Time Point

Background:Over the last 2 decades rituximab (RTX) has been widely used, albeit off-label, in primary Sjögren’s syndrome (pSS). Several studies reported that B-lymphocyte depletion with RTX is effective in this disease not only by reducing disease activity but also by affecting the inflammation and the lymphoid organization that occur in target tissues. With the recent release of several RTX biosimilars (bRTX) on the market, the demonstration of their interchangeability with RTX originator (oRTX) is required.Objectives:To compare efficacy and safety of oRTX and bRTX in pSS patients in a real-life setting.Methods:Clinical records of pSS patients referring to a tertiary rheumatology clinic were retrospectively evaluated. Patients having received at least 2 courses of either oRTX or bRTX (1000 mg IV infusion, repeated after 2 weeks -1 course- and the course repeated after 24 weeks) with complete data at baseline and after 3, 6, 9 and 12 months of treatment were enrolled. Disease activity was assessed with the EULAR SS disease activity index (ESSDAI) and its clinical version without the biological domain (ClinESSDAI). Patient-reported symptoms were assessed with the EULAR SS Patient Reported Index (ESSPRI).Results:Seven patients that received oRTX and 7 patients that received bRTX were enrolled. Baseline clinical features, including ESSDAI and ESSPRI were similar in the 2 treatment groups. Both compounds significantly reduced ESSDAI and ESSPRI as early as 3 months and no difference between the groups was observed at any time point (Figure 1). Of interest, ESSDAI slowly decreased until month 6 when the most pronounced reduction was observed. Conversely, ESSPRI dropped to its lowest values already at month 3. With regard to safety, at 12 months of follow-up no adverse event was observed in any of the treatment groups.Conclusion:At 12 months of follow-up, oRTX and bRTX display similar efficacy and safety profiles. The improvement of patient reported outcomes is faster than the improvement of disease activity with both compounds. Our data support interchangeability of oRTX and bRTX in pSS.References:[1]Carubbi F et al. Arthritis Res Ther. 2013;15(5):R172[2]Carubbi F et al. Lupus. 2014;23(13):1337-49Figure 1 ESSDAI and ESSPRI values at every time point in the 2 treatment groups. Asterisks indicate p values <0.05 compared to the other treatment group at the same time pointDisclosure of Interests:Francesco Carubbi Speakers bureau: Francesco Carubbi received speaker honoraria from Abbvie and Celgene outside this work., Alessia Alunno: None declared, Paola Cipriani Grant/research support from: Actelion, Pfizer, Speakers bureau: Actelion, Pfizer, Viktoriya Pavlych: None declared, claudia di muzio: None declared, Roberto Gerli: None declared, Roberto Giacomelli Grant/research support from: Actelion, Pfizer, Speakers bureau: Abbvie, Roche, Actelion, BMS, MSD, Ely Lilly, SOBI, Pfizer

scholarly journals Stacked Community Prediction: A Distributed Stacking-Based Community Extraction Methodology for Large Scale Social Networks

2021 ◽  
Vol 5 (1) ◽  
pp. 14
Author(s):  
Christos Makris ◽  
Georgios Pispirigos
Keyword(s):  
Social Networks ◽  
Graph Partitioning ◽  
Large Scale ◽  
Real Life ◽  
Information Networks ◽  
Digital Marketing ◽  
Partitioning Problems ◽  
Iterative Solutions ◽  
Community Extraction ◽  
Stability And Accuracy

Nowadays, due to the extensive use of information networks in a broad range of fields, e.g., bio-informatics, sociology, digital marketing, computer science, etc., graph theory applications have attracted significant scientific interest. Due to its apparent abstraction, community detection has become one of the most thoroughly studied graph partitioning problems. However, the existing algorithms principally propose iterative solutions of high polynomial order that repetitively require exhaustive analysis. These methods can undoubtedly be considered resource-wise overdemanding, unscalable, and inapplicable in big data graphs, such as today’s social networks. In this article, a novel, near-linear, and highly scalable community prediction methodology is introduced. Specifically, using a distributed, stacking-based model, which is built on plain network topology characteristics of bootstrap sampled subgraphs, the underlined community hierarchy of any given social network is efficiently extracted in spite of its size and density. The effectiveness of the proposed methodology has diligently been examined on numerous real-life social networks and proven superior to various similar approaches in terms of performance, stability, and accuracy.

AN EFFICIENT APPROACH FOR THE THREE-DIMENSIONAL CONTAINER PACKING PROBLEM WITH PRACTICAL CONSTRAINTS

2004 ◽  
Vol 21 (03) ◽  
pp. 279-295 ◽  
Author(s):  
ZHIHONG JIN ◽  
KATSUHISA OHNO ◽  
JIALI DU
Keyword(s):  
Three Dimensional ◽  
Real Life ◽  
Packing Problem ◽  
Utilization Rate ◽  
Benchmark Problems ◽  
Rectangular Container ◽  
Efficient Packing ◽  
High Degree ◽  
Practical Constraints ◽  
Inherent Stability

This paper deals with the three-dimensional container packing problem (3DCPP), which is to pack a number of items orthogonally onto a rectangular container so that the utilization rate of the container space or the total value of loaded items is maximized. Besides the above objectives, some other practical constraints, such as loading stability, the rotation of items around the height axis, and the fixed loading (unloading) orders, must be considered for the real-life 3DCPP. In this paper, a sub-volume based simulated annealing meta-heuristic algorithm is proposed, which aims at generating flexible and efficient packing patterns and providing a high degree of inherent stability at the same time. Computational experiments on benchmark problems show its efficiency.

The Effect of Lesion Characteristic on Remineralization and Model Sensitivity

1992 ◽  
Vol 71 (3_suppl) ◽  
pp. 811-813 ◽  
Author(s):  
F. Schäfer ◽  
S.J. Raven ◽  
T.A. Parr
Keyword(s):  
Real Life ◽  
High Sensitivity ◽  
Lesion Size ◽  
Experimental Conditions ◽  
Treatment Groups ◽  
Human Enamel ◽  
Enamel Sample ◽  
Two Factors ◽  
Treatment Bias

A major criterion for assessing the value of any experimental model in scientific research is the degree of correspondence between its results and data from the real-life process it is designed to model. Intra-oral models aimed at predicting the anti-caries efficacy of toothpastes or other topical treatments should therefore be calibrated against treatments proven to be effective in a caries clinical trial. For this to be achieved, it is necessary that a model with high sensitivity be designed, while at the same time retaining relevance to the process to be modeled. This means that the effects of the various experimental conditions and parameters of the model on its performance must be understood. The purpose of this paper was to assess the influence of two specific factors on the performance of an in situ enamel remineralization model, which is based on human enamel slabs attached to partial dentures. The two factors are initial lesion severity and origin of enamel sample. The results indicated that initial lesion size affected whether net remineralization or net demineralization occurred during in situ treatment. Samples with an initial range of from 1500 to 2500 (ΔZ) tended more toward demineralization than did samples with ΔZ > 3500. This means that treatment groups must be well-balanced with respect to initial lesion size. Differences in initial demineralization severity between different tooth locations must also be considered so that systematic treatment bias can be avoided. The solution used in the model discussed here is based on a balanced experimental design, which allows this effect to be taken into account in the data analysis.

scholarly journals The Effect of Interactive Multiple Intelligences Activities Flip Module: Its Effects on Students’ Multiple Intelligences

2019 ◽  
Vol 8 (11) ◽  
pp. 342-348
Keyword(s):  
Multiple Intelligences ◽  
Test Analysis ◽  
Pedagogical Tool ◽  
Intra Class Correlation ◽  
Treatment Groups ◽  
Computer Based Learning ◽  
Intelligence Activity ◽  
Computer Based ◽  
High Degree ◽  
Intra Class Correlation Coefficient

This study aims to test an interactive pedagogical tool using a computer-based learning approach. The purpose of building Multiple Intelligences Activities Flip Module is to increase students’ potentials through their multiple intelligences. The true-experimental study design is used and the samples are randomly selected as control and treatment groups. Pre and post tests are used to measure the effectiveness of this interactive flip module in relations to multiple intelligences significant differences. The findings of the study reveal that the interactive Multiple Intelligences Activity flip module has a high degree of reliability whereby the average measure for Intra-class Correlation Coefficient is .771 with a 95% confidence interval from .520 to .931 (F(9,486)= 4.644, p<.000). Based on MANCOVA test analysis, the researchers have rejected the null hypothesis. The study has demonstrated that the Multiple Intelligence Activity flip module has increased the scores of multiple intelligences tests for treatment groups.

scholarly journals Training of a future social professional for the formation of safe adolescent behavior in social networks

2021 ◽  
Keyword(s):  
Social Networks ◽  
Information Exchange ◽  
Professional Training ◽  
Social Groups ◽  
Real Life ◽  
Well Being ◽  
The Internet ◽  
Stage Of Development ◽  
Safe Behavior ◽  
Definition Of

The article analyzes different approaches to the definition of «social networks» as technological complexes of organization and management of electronic information exchange among the subjects of social relations, united by common interests, information needs and skills. Based on the analysis of the scientific literature the essential characteristics of social networks that affect the formation and development of the adolescent's personality are revealed. Role of social networks at the present stage of development of society, which is manifested in the representation of interests not only of social groups but also of entire social groups, is defined in the article. The negative impact of social networks on the personality of the adolescent, which is manifested in the expansion of adolescents in cyberspace, the desire for independence and adulthood, selfexperimentation, which leads to risky activities both on the Internet and in real life are revealed. Concept of safe behavior in social networks as a set of actions of the individual when using the Internet, helping to meet the needs and at the same time prevent the possibility of causing damage to physical, mental, social well-being and property of man and others is analyzed. The basic rules of safe behavior in social Internet communities are highlighted. The structural components of safe behavior of adolescents in social networks are singled out: cognitive, motivational and actionreflexive; the concept of «professional training of future social professionals for the formation of safe behavior of adolescents in social networks» is revealed. Readiness is revealed as a result of the process of training future social specialists for professional activity on the formation of safe behavior of adolescents in social networks; the author's definition of the concept «readiness of future social professionals to form safe behavior of adolescents in social networks» is given. Components of readiness of future social workers to form safe behavior of teenagers in social networks, such as cognitive, motivational-personal and activity, are described.

scholarly journals Optimizing community detection in social networks using antlion and K-median

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Amany A. Naem ◽  
Neveen I. Ghali
Keyword(s):  
Social Networks ◽  
Objective Function ◽  
Community Detection ◽  
Optimization Problem ◽  
Real Life ◽  
Optimization Methods ◽  
Population Based ◽  
Detection Problem ◽  
Network Communities ◽  
Antlion Optimization

Antlion Optimization (ALO) is one of the latest population based optimization methods that proved its good performance in a variety of applications. The ALO algorithm copies the hunting mechanism of antlions to ants in nature. Community detection in social networks is conclusive to understanding the concepts of the networks. Identifying network communities can be viewed as a problem of clustering a set of nodes into communities. k-median clustering is one of the popular techniques that has been applied in clustering. The problem of clustering network can be formalized as an optimization problem where a qualitatively objective function that captures the intuition of a cluster as a set of nodes with better in ternal connectivity than external connectivity is selected to be optimized. In this paper, a mixture antlion optimization and k-median for solving the community detection problem is proposed and named as K-median Modularity ALO. Experimental results which are applied on real life networks show the ability of the mixture antlion optimization and k-median to detect successfully an optimized community structure based on putting the modularity as an objective function.

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