TURNOUT INTENTION AND RANDOM SOCIAL NETWORKS

2011 ◽  
Vol 14 (01) ◽  
pp. 31-53 ◽  
Author(s):  
CONSTANZA FOSCO ◽  
ANNICK LARUELLE ◽  
ANGEL SÁNCHEZ

How can networking affect the turnout in an election? We present a simple model to explain turnout as a result of a dynamic process of formation of the intention to vote within Erdös–Rényi networks. Citizens have fixed preferences for one of two parties and are embedded in a social network. They decide whether or not to vote on the basis of the attitude of their immediate contacts. They may simply follow the behavior of the majority (followers) or make an adaptive local calculus of voting (calculators). So they have the intention of voting either when the majority of their neighbors are willing to vote too, or when they perceive in their social neighborhood that elections are "close". We study the long-run average intention to vote, interpreted as the actual turnout observed in an election. Depending on the values of the average connectivity and the probability of behaving as a follower/calculator, the system exhibits monostability (zero turnout), bistability (zero and moderate/high turnout) or tristability (zero, moderate and high turnout). By obtaining realistic turnout rates for a wide range of values of both parameters, our model suggests a mechanism behind the observed relevance of social networks in recent elections.

2020 ◽  
Author(s):  
Joseph Bayer ◽  
Neil Anthony Lewis ◽  
Jonathan Stahl

Much remains unknown about moment-to-moment social-network cognition — that is, who comes to mind as we go about our day-to-day lives. Responding to this void, we describe the real-time construction of cognitive social networks. First, we outline the types of relational structures that comprise momentary networks, distinguishing the roles of personal relationships, social groups, and mental sets. Second, we discuss the cognitive mechanisms that determine which individuals are activated — and which are neglected — through a dynamic process. Looking forward, we contend that these overlooked mechanisms need to be considered in light of emerging network technologies. Finally, we chart the next steps for understanding social-network cognition across real-world contexts, along with the built-in implications for social resources and intergroup disparities.


Author(s):  
Boris Milović

Social networks have proven to be very convenient and effective medium for the spreading of marketing messages, advertising, branding and promotion of products and services. Social networks offer companies, nonprofit organizations, political parties etc. sending certain messages for free. In addition, they allow companies access to a wide range of characteristics of their users. Developing appropriate, the winning strategy for marketing in social media is a comprehensive, time-intensive process therefore it is important to know to manage their content. Social networks transform certain classical approaches to marketing. They provide creative and relatively easy way to increase public awareness of the company and its products, and facilitate obtaining feedback and decision making. These are sources of different information about users and groups that they've joined. The success itself of marketing performance on a social network depends on the readiness and training of organizations to perform on them.


2020 ◽  
Vol 34 (02) ◽  
pp. 1878-1885
Author(s):  
Matteo Castiglioni ◽  
Diodato Ferraioli ◽  
Nicola Gatti

We focus on the scenario in which messages pro and/or against one or multiple candidates are spread through a social network in order to affect the votes of the receivers. Several results are known in the literature when the manipulator can make seeding by buying influencers. In this paper, instead, we assume the set of influencers and their messages to be given, and we ask whether a manipulator (e.g., the platform) can alter the outcome of the election by adding or removing edges in the social network. We study a wide range of cases distinguishing for the number of candidates or for the kind of messages spread over the network. We provide a positive result, showing that, except for trivial cases, manipulation is not affordable, the optimization problem being hard even if the manipulator has an unlimited budget (i.e., he can add or remove as many edges as desired). Furthermore, we prove that our hardness results still hold in a reoptimization variant, where the manipulator already knows an optimal solution to the problem and needs to compute a new solution once a local modification occurs (e.g., in bandit scenarios where estimations related to random variables change over time).


2020 ◽  
Vol 29 (3) ◽  
pp. 279-285 ◽  
Author(s):  
Joseph B. Bayer ◽  
Neil A. Lewis ◽  
Jonathan L. Stahl

Much remains unknown about moment-to-moment social-network cognition—that is, who comes to mind as we go about our day-to-day lives. Responding to this void, we describe the real-time construction of cognitive social networks. First, we outline the types of relational structures that comprise momentary networks, distinguishing the roles of personal relationships, social groups, and mental sets. Second, we discuss the cognitive mechanisms that determine which individuals are activated—and which are neglected—through a dynamic process. Looking forward, we contend that these overlooked mechanisms need to be considered in light of emerging network technologies. Finally, we chart the next steps for understanding social-network cognition across real-world contexts, along with the built-in implications for social resources and intergroup disparities.


2013 ◽  
Vol 26 (4) ◽  
pp. 533-539 ◽  
Author(s):  
Hiroko H. Dodge ◽  
Oscar Ybarra ◽  
Jeffrey A. Kaye

People are good for your brain. Decades of research have shown that individuals who have a larger number of people in their social network or higher quality ties with individuals within their network have lower rates of morbidity and mortality across a wide range of health outcomes. Among these outcomes, cognitive function, especially in the context of brain aging, has been one area of particular interest with regard to social engagement, or more broadly, socially integrated lifestyles. Many studies have observed an association between the size of a person's social network or levels of social engagement and the risk for cognitive decline or dementia (e.g. see review by Fratiglioni et al., 2004). The dementia risk reduction associated with a larger social network or social engagement shown by some epidemiological studies is fairly large. The population effect size of increasing social engagement on delaying dementia disease progression could exceed that of current FDA approved medications for Alzheimer's disease.


Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Md. Shafiur Rahman ◽  
Sajal Halder ◽  
Md. Ashraf Uddin ◽  
Uzzal Kumar Acharjee

AbstractAnomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system.


2018 ◽  
pp. 73-89 ◽  
Author(s):  
Boris Milović

Social networks have proven to be very convenient and effective medium for the spreading of marketing messages, advertising, branding and promotion of products and services. Social networks offer companies, nonprofit organizations, political parties etc. sending certain messages for free. In addition, they allow companies access to a wide range of characteristics of their users. Developing appropriate, the winning strategy for marketing in social media is a comprehensive, time-intensive process therefore it is important to know to manage their content. Social networks transform certain classical approaches to marketing. They provide creative and relatively easy way to increase public awareness of the company and its products, and facilitate obtaining feedback and decision making. These are sources of different information about users and groups that they've joined. The success itself of marketing performance on a social network depends on the readiness and training of organizations to perform on them.


Author(s):  
Євген Миколайович Мануйлов ◽  
Юрій Юрійович Калиновський

Problem setting. Nowadays, social networks have become an integral part of communication processes in society. The influence of social networks on the socio-cultural development of Ukraine has both positive and negative manifestations, since both values and antivalues are spread in these communication systems, there are subjects who are guided by the norms of morality and law, and those who neglect them, direct their efforts to the harmonization of a certain sphere of public life, or vice versa, produces xenophobic sentiments, inciting enmity in the domestic society at the cultural, national, religious and other levels. Recent research and publications analysis. Significant numbers of scientific works are aimed at elucidating the signs and criteria of deviating as a social phenomenon. According to A. Demkiv, those values, the worldview and behavior that deviate from the organizational culture that exist in a certain social community are considered deviant. In the context of this research, it is important to note A. Khlebnikova's reflections on the recognition and determination of the axiological status of the social network in modern society and the scientific work of P. Kravchenko, which proves that religion, morality, values, language, traditions contribute to the internal consolidation of local social groups, and in this process, social networks perform a leading role. Researchers A. Onishchenko, V. Gorovoy, V. Popik and others devoted their scientific research to uncovering the negative impact of social networks on the development of the Ukrainian state and its socio-cultural and informational spheres. Paper objective. This research involves the disclosure of the negative impact of value deviations of social network subjects on the domestic socio-cultural area, information and spiritual security of Ukraine. Paper main body. The wide range of values presented in social networks has a consolidating, humanistic nature – they are reproduced by scientific and creative communities, spiritual and cultural associations, volunteer and human rights organizations, and so on. In turn, anti-values are presented in the content of extremist organizations, xenophobic associations of various orientations, which creates an ideological basis for the emergence of social conflicts, disintegration processes, and civil confrontation. Thus, social networks have become an influential actor in the development of the socio-cultural, spiritual, value, information space of our country. Considering Ukrainian society as a holistic formation, it is worth noting that value deviations are those ideas about the ways of being and about spiritual life that do not correspond to the humanistic and national guidelines for the democratic development of Ukrainian society. In the context of the research, worldview guidelines that contradict moral attitudes, existing legal norms, accepted traditions of the domestic society, etc. can be considered as value deviations in social networks. Freedom in social networks has a dual manifestation: on the one hand, it is free opportunities for self-realization of individuals and diverse perspectives for the development of the country's socio‑cultural space, and on the other hand, freedom in social networks creates conditions for the popularization of antihuman attitudes, pseudo-values, xenophobic ideologies and worldview systems. Conclusions of the research.  The value deviations of social network subjects are a logical continuation of the deformations of the moral, political, legal, spiritual and other humanistic direction attitudes that are widespread in Ukrainian society. Undoubtedly, the influence of value deviations on domestic socio-cultural development is destructive and it can manifest itself in illegal, immoral, aggressive models of behavior.


Author(s):  
Vijayaganth V.

Social networks have increased momentously in the last decade. Individuals are depending on interpersonal organizations for data, news, and the assessment of different clients on various topics. These issues often make social network data very complex to analyze manually, resulting in the persistent use of computational means for analyzing them. Data mining gives a variety of systems for identifying helpful learning from huge datasets and a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules. This chapter discusses different data mining techniques used in mining social networks.


2020 ◽  
Author(s):  
Daizaburo Shizuka ◽  
Sahas Barve ◽  
Allison Johnson ◽  
Eric Walters

1.Advances in datalogging technologies have provided a way to monitor the movement of individual animals at unprecedented spatial and temporal scales, both large and small. When used in conjunction with social network analyses, these data can provide insight into fine scale associative behaviors. The variety of technologies demand continuous progress in workflows to translate data streams from automated systems to social networks, based on biologically relevant metrics. 2.Here we present a workflow for generating flexible association matrices from automated radio-telemetry data that can be parsed into both spatial and temporal dimensions. These can then be used to generate and compare social networks across space and time.3.We illustrate this workflow using data collected from an automated telemetry study of acorn woodpeckers (Melanerpes formicivorus), a cooperatively breeding bird. The data were collected continuously over two years at base stations placed within social group territories. We use this system to demonstrate how this flexible data structure can be used to answer a number of biological questions, specifically 1) how assortative are social associations at the population scale, 2) how do association patterns among territory visitors vary across territories, 3) and how does seasonality affect assortative affiliation within groups?4.This flexible method allows one to generate social networks that can be used to ask a variety of biological questions pertinent to a wide range of animal systems, exploiting the investigative power that can be gained by using automated radio-telemetry in conjunction with social network analyses.


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