Behavior In Social Networks Research Articles

Social network factors affecting adoption of Mobile app by farmers

Effect of social network on adoption of Mobile app was studied in Nashik and Sangli districts of Maharashtra, India by interviewing 800 grape growers during 2016-17. Individual characteristics like income, landholding, caste, area under grapes and number of smartphones were significant factors determining the adoption of mobile app. In social network factors, village adoption rate, membership, education, landholding and frequency of communication were significant determinants of adoption. Village adoption rate of the technology resembles network behavior. Therefore, both social network characteristics and social network behavior influences the adoption decision of farmers. It shows that adoption is not just mimicking by the farmers, but it is a social learning process. The results emanating from the study provide insights to extension agents to devise strategy for introduction of any technology/ICT in agriculture. The way out to implement the strategy is to use extension methods that focus on social learning like Farmers Field Schools; target the farmers having more education, landholdings and who frequently interact with the large number of farmers to facilitate and enhance the adoption of new technology/ICT.

Social network behavior inappropriateness: the role of individual-level espoused national cultural values

PurposeThe purpose of the current study is to investigate the effects of individual-level (espoused) cultural values (collectivism, power distance, uncertainty avoidance, masculinity and long-term orientation) on the individuals' acceptability of inappropriate social network behaviors.Design/methodology/approachThe study employs survey data collected from 482 social network users (261 in the United States and 221 from India).FindingsResults show that individuals with high power distance, masculinity and long-term oriented cultural values are more accepting of inappropriate social network behaviors of others, while those with strong uncertainty avoidance cultural values have high degree of social network behavior inappropriateness, which is defined as the extent to which behaviors of social network users are considered unacceptable by others.Research limitations/implicationsThe paper highlights the need for more academic research on the intersection of culture and social network behaviors. This study emphasizes the need for adopting an interdisciplinary approach to understand individuals' social network behaviors.Practical implicationsThe paper offers recommendations to global organizations pertaining to the need for creating social network policies in such a way that encourages their global workforce to openly, yet respectfully, share their ideas using social networks.Originality/valueUsing an interdisciplinary approach, the present study extends our understanding of a recently proposed social network behavioral inappropriateness construct and explains how differences in cultural values may lead to differences in individuals' social network behaviors.

Social Experience Interacts with Serotonin to Affect Functional Connectivity in the Social Behavior Network following Playback of Social Vocalizations in Mice.

Past social experience affects the circuitry responsible for producing and interpreting current behaviors. The social behavior network (SBN) is a candidate neural ensemble to investigate the consequences of early-life social isolation. The SBN interprets and produces social behaviors, such as vocalizations, through coordinated patterns of activity (functional connectivity) between its multiple nuclei. However, the SBN is relatively unexplored with respect to murine vocal processing. The serotonergic system is sensitive to past experience and innervates many nodes of the SBN; therefore, we tested whether serotonin signaling interacts with social experience to affect patterns of immediate early gene (IEG; cFos) induction in the male SBN following playback of social vocalizations. Male mice were separated into either social housing of three mice per cage or into isolated housing at 18–24 d postnatal. After 28–30 d in housing treatment, mice were parsed into one of three drug treatment groups: control, fenfluramine (FEN; increases available serotonin), or pCPA (depletes available serotonin) and exposed to a 60-min playback of female broadband vocalizations (BBVs). FEN generally increased the number of cFos-immunoreactive (-ir) neurons within the SBN, but effects were more pronounced in socially isolated mice. Despite a generalized increase in cFos immunoreactivity, isolated mice had reduced functional connectivity, clustering, and modularity compared with socially reared mice. These results are analogous to observations of functional dysconnectivity in persons with psychopathologies and suggests that early-life social isolation modulates serotonergic regulation of social networks.

Influence network design via multi-level optimization considering boundedly rational user behaviours in social media networks

Social media networks have been playing an increasingly more important role for both socialization and information diffusion. Political campaign can gain more supporters by attracting more mass attention and influencing them directly, while commercial campaigns can increase their companies’ profits by expanding social media connection with new users. To build the optimal network structure to influence the whole, this paper studies mathematical models to simulate the users’ behaviours interacting with others in the information provider’s network. The behaviours of concerns include information re-posting and following/unfollowing other users. Linear threshold propagation model is used to determine the re-posting actions, Boundedly Rational User Equilibrium (BRUE) models are used to determine the following or unfollowing actions. Hence, the topology of the network changes and depends on the information provider’s plan to post various kinds of information. A three-level optimization model is proposed to maximize total number of connections, the goal of the top level. The second level simulates user behaviours under BRUE. The third level maximizes the each user’s utility defined in the second level. This paper solves this problem using exact algorithms for a small-scale synthetic network. For a large-scale problem, this paper uses heuristic algorithms based on large neighbourhood search. This paper also discusses possible reasons why the BRUE model may be a more accurate simulation of users’ actions compared to game theory. Comparisons from the BRUE model to game theoretical model show that the BRUE model performs significantly better than game theoretical model.

Predicting Mental Health From Followed Accounts on Twitter

The past decade has seen rapid growth in research linking stable psychological characteristics (i.e., traits) to digital records of online behavior in Online Social Networks (OSNs) like Facebook and Twitter, which has implications for basic and applied behavioral sciences. Findings indicate that a broad range of psychological characteristics can be predicted from various behavioral residue online, including language used in posts on Facebook (Park et al., 2015) and Twitter (Reece et al., 2017), and which pages a person ‘likes’ on Facebook (e.g., Kosinski, Stillwell, & Graepel, 2013). The present study examined the extent to which the accounts a user follows on Twitter can be used to predict individual differences in self-reported anxiety, depression, post-traumatic stress, and anger. Followed accounts on Twitter offer distinct theoretical and practical advantages for researchers; they are potentially less subject to overt impression management and may better capture passive users. Using an approach designed to minimize overfitting and provide unbiased estimates of predictive accuracy, our results indicate that each of the four constructs can be predicted with modest accuracy (out-of-sample R’s of approximately .2). Exploratory analyses revealed that anger, but not the other constructs, was distinctly reflected in followed accounts, and there was some indication of bias in predictions for women (vs. men) but not for racial/ethnic minorities (vs. majorities). We discuss our results in light of theories linking psychological traits to behavior online, applications seeking to infer psychological characteristics from records of online behavior, and ethical issues such as algorithmic bias and users’ privacy.

Utilizing Facebook for professional integration of three ethnic groups in Israel

This study proposes a conceptual model for utilization of Facebook for professional integration of ethnic minorities, based on the social capital and weak social ties theories. In particular, the research focuses on differences among ethnic groups of Facebook users in their willingness to create intergroup work relations and its various influence factors. A designated questionnaire was composed and administered to 120 subjects from three ethnic groups in Israel: Jewish, Muslim-Arab and Druze. We found that the proportion of intergroup professional relations was higher on Facebook than in the offline workspace in all three groups. There were numerous differences between the three examined groups: self-disclosure was significantly higher for Druze and Jewish users than for the Arab users, while the willingness to create intergroup professional connections was much higher for the two minorities than for the Jewish users. This study contributes to understanding the factors that influence social network behaviour of different ethnic groups. Our results indicate that social networking sites can catalyse creation of intergroup professional relations. Utilization of social networking sites as a platform for professional promotion might constitute a first step in the process of professional and cultural integration of minorities in the ethnically heterogeneous society.

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

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.

Online literary creativity of digital natives: genre and thematic analysis

The article presents the results of a genre-thematic analysis of 1129 texts recognized as the most popular in 2019 on the platform Ficbook.net. It was found that young people of generation Z - the authors of these works (prose, poetry, journalism), were broadcasting existential anxiety and depression, tell stories which content is mainly related to violence and sex. The research is innovative in connection with empirical material that has not been studied before in the context of the problems of socialization of the digital generation. The features of socialization and motivation of "digital natives" representatives, their behavior in social networks and in real life are revealed. The results obtained can be useful for specialists in media communications, as well as psychologists, sociologists and teachers.

Potential of the dynamic approach to data analysis

Explores the potential of a dynamic data analysis approach to study user behavior in social networks. Currently, information appears on social networks that allows differentiating user groups by their activity within the technical capabilities of a particular social network. The description of the information field of Tomsk is presented, a brief analysis is given. A dynamic approach to the study of user behavior, the structure of nodes and connections of social networks makes it possible to identify the rate of growth or decrease in the size of the network, the redistribution of connections between groups. There are four main stages in the analysis of social networks: 1) data collection; 2) selection of data for analysis; 3) selection and application of the analysis method; and 4) drawing conclusions. To obtain a complete picture of the information field of the Tomsk region, posts for 2019 were unloaded from all regional communities. All posts were classified based on training sample and specialized machine learning algorithm.

Медиапотребление членов виртуальных экологических протестных сообществ (на примере конфликта вокруг мусорного полигона в Архангельской области)

The growing influence of social media has significantly affected various aspects of sociopolitical life, including social movements and protest activity. Social networks are becoming a part of everyday life, influencing the processes of media consumption. Traditional media are no longer the main source of news, being replaced by social media. Users of social networks largely build their individual agenda setting, forming their own news feed, subscribing to a particular virtual community (media, parties, etc.). Realizing this, the latter are trying to make use of it by creating virtual communities on social networks. Over the past decade, observers have noted that social networks are beginning to play a significant role in public life in Russia. In this regard, the problem of user behavior in various social networks seems to be important for research, including such an important component of everyday life as news consumption. This work analyzes news consumption patterns of members of virtual communities created on the VKontakte social network in connection with one of the most noticeable socio-ecological conflicts of the last decade around the construction of a landfill in Shies. In this study, the author planned to compare members of “anti-garbage” communities and members of territorial communities (Arkhangelsk Oblast and the Komi Republic) in relation to news consumption. He decided to limit the scope to two areas of news consumption by community members: environmental and political agendas. Interest in the environmental agenda could be expressed by joining virtual environmental communities. Similarly, interest in the political agenda could be expressed by joining communities offering political news. In addition, members of “anti-garbage” communities were surveyed in relation to the extent to which they followed the most notable protest events of the past year, not related to the environmental agenda. The study revealed the difference between members of communities created in connection with the Shies landfill project from members of territorial communities in their interest in various federal virtual communities offering political news. The analysis showed that the agenda setting of members of “anti-garbage” communities, in comparison with the agenda setting of members of territorial communities, formed by an individual news feed, is more alternative to the official agenda. Users interested in news in connection with an acute socio-ecological conflict are more interested in news provided by “independent” media and opposition political movements. In this regard, we can speak about the greater politicization of citizens concerned about the acute environmental conflict. The analysis also revealed a connection between the agenda setting formed by virtual communities and the interest of members of “anti-garbage” communities in protest events that go far beyond the environmental agenda.

Analysis of the conditions of the relation between intention and behaviour in online social networks

Analysis of the conditions of the relation between intention and behaviour in online social networks

Social network, environmental cognition and organic fertilizer application behavior of small farmers

Small farmers are the main organizational form of agricultural production and management in China, and it is very important to study their organic fertilizer application behavior to promote the development of green agriculture in China. Based on the survey data of 334 small farmers in Sichuan Province, this paper uses bivariate Probit model to analyze the influence of social network and environmental cognition on organic fertilizer application behavior. The research shows that:(1) The application of commercial organic fertilizer and farmyard manure by small farmers has a significant complementary effect.(2) Social network has a significant positive impact on organic fertilizer application behavior, and there are significant differences between kinship social network and friendship social network on organic fertilizer application behavior.(3) The level of environmental cognition has a significant positive effect on the application behavior of organic fertilizer. Therefore, it is necessary not only to make full use of and expand the social network of small farmers, but also to pay attention to improving their environmental awareness and promoting organic fertilizer application behavior.

Research on the Link Prediction Model of Dynamic Multiplex Social Network Based on Improved Graph Representation Learning

In the natural and social systems of the real world, various network can be seen everywhere. The world where people live can be seen as a combination of network with different dimensions. Link prediction formalizes the interaction behavior between people. Traditional link prediction methods mainly study the user behavior of static social network. This article studied the dynamic graph representation learning so as to put forward an improved link prediction model in dynamic social network. Besides, the interactions in the real world can be multiple, links at different moments may have different meanings. The proposed model firstly solved the problem of link prediction on multiple kinds of edges. The whole embedding of each node is separated into two parts, basic embedding and edge embedding. Then the proposed model selected time slices for dynamic social network to get the graph embeddings in different snapshots. What's more, the t+1 time step embedding vector was used to validate t time step prediction effect and the proposed model performed better than traditional graph representation learning methods.

Certain aspects of regulation of attorneys' behavior in social networks

Introduction. Some aspects of a lawyer's behavior on social networks are regulated by the Rules of Attorney Ethics. However, these provisions have been criticized by lawyers since their adoption. Therefore, an analysis of the norms of those Rules is appropriate to address issues related to their application in practice. The purpose of this paper is to Analyze the provisions of the Rules of Advocate Ethics in terms of regulating the behavior of a lawyer on social networks. Investigate the practice of applying such provisions as well as the possibility of further improving legal regulation in this area. Results. The paper deals with the issues of regulation of lawyers' behavior in social networks, analyzes the norms of the Rules of Attorney ethics, examines potential negative consequences of application current version of those norms for both individual lawyers and for the whole institute of advocacy. Furthermore, it contains certain suggestions of how to improve legal regulation of this area. Emphasis on the existence of the unspecified concept of “lawyer's authority”. It is determined, that the interpretation of those concept is left to the discretion of the Qualification and Disciplinary Commission of the Advocacy. But such a wide competence may lead to committing some abuses by this authority. The problem of formation of additional duties of lawyers than those provided by the Rules of attorney ethics is revealed. The legitimacy of such responsibilities has been proven. The paper examines potential negative consequences of application current version of those norms for both individual lawyers and for the whole institute of advocacy. Namely, due to the lack of a clear possibility to identify the person leaving the record on the social network, it is considered to be difficult and sometimes impossible to prove the guilt of a particular lawyer. Furthermore, the paper contains certain suggestions of how to improve legal regulation of this area. In particular, the position of scholars on the impossibility of applying, according to lawyers on social networks, such disciplinary sanctions as suspension or termination of the right to practice law was supported. Authors consider it expedient to include information in the Unified Register of Lawyers of Ukraine to confirm the profile of a lawyer on a social network. Conclusion. The necessity of developing a system of methodical recommendations for solving cases of this category is stated. It is proposed to develop methodological recommendations by analyzing the accounts of users of various social networks and summarizing the information obtained with the possible involvement of specialists in the field of IT-technologies.

Social Net Users’ Behavior as a Forming Factor of Social Representations about Spouse

The present research traced the connection between the behavior of social net users and 1) the content they view devoted to romantic relationships and 2) their social representations about their prospective spouse. The survey involved 525 respondents and an authentic questionnaire of three blocks. The first block of questions was based on a content analysis of young people's essays and social net entries. It featured social representations about romantic relationships and marriage. The second block was connected with socio-demographic characteristics. The third block analyzed the use of social networks and other communication channels. The study revealed a link between one’s behavior in social networks and social representations about a romantic partner, married life, and family relations. Users that frequently viewed social media posts about relationships between men and women were not marriage-oriented and did not seek long-term romantic relationships. They viewed romantic relationships as an exciting adventure and they entertained a possibility of having different partners at different life stages. Such elements in social representations may lead to a more tolerant attitude to such phenomena as unregistered marriage, divorce, and serial monogamy.

Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data.

In the 4.5 decades since Altmann (1974) published her seminal paper on the methods for the observational study of behaviour, automated detection and analysis of social interaction networks have fundamentally transformed the ways that ecologists study social behaviour. Methodological developments for collecting data remotely on social behaviour involve indirect inference of associations, direct recordings of interactions and machine vision. These recent technological advances are improving the scale and resolution with which we can dissect interactions among animals. They are also revealing new intricacies of animal social interactions at spatial and temporal resolutions as well as in ecological contexts that have been hidden from humans, making the unwatchable seeable. We first outline how these technological applications are permitting researchers to collect exquisitely detailed information with little observer bias. We further recognize new emerging challenges from these new reality-mining approaches. While technological advances in automating data collection and its analysis are moving at an unprecedented rate, we urge ecologists to thoughtfully combine these new tools with classic behavioural and ecological monitoring methods to place our understanding of animal social networks within fundamental biological contexts.

The effects of professional competency and workplace social networking on hotel employees’ career success

ABSTRACT Changing working conditions have made careers unpredictable and a successful end of career hard to achieve, so employees need to manage their careers successfully. This study investigates the effects of professional competency and workplace social networking behaviour on career success. Using a survey technique, 711 responses were obtained from hotel employees in Turkey. The findings indicate that professional competency and workplace social networking have a positive effect on career success. The most remarkable detail in the results of the study, is that workplace social networking, especially relationships with the supervisor, is a priority in career development.

Predicting Individual’s Posting Behaviors in Social Network with Markov Chain

Online social networks like twitter are self-organized systems with emergent behaviors from the individual interactions. Predicting the users’ behaviors like posting, replying or retweeting is one of the most important issue. In the paper, we present a method to model the twitter users’ posting behavior with the other users’ response. We also contrast the simulation precision with the model that does not involve the other users’ response. We make use of a stochastic model with Markov chain to predict a specific user’s next tweeting behavior. From the result by contrasting the simulation data and the real data, we demonstrate that the engineering method is able to predict individual posting behaviors based on time windows. In addition, the proposed model involving other users’ response is better than that only considering posting time sequences.

Adolescent Sports Behavior and Social Networks: The Role of Social Efficacy and Self-Presentation in Sports Behavior

Social networks are a complex system that members communicate, create new connections or destroy existing connections, and further deliver major impacts on each member’s life. Given the spread of the Internet and increased academic pressure, sedentary and prescreen behaviors are very common among adolescents; meanwhile, sports behaviors are gradually decreasing. This situation has had an adverse effect on health. This paper used a questionnaire survey to investigate the influence of social networks on adolescent sports behavior, including the intermediary role of social efficacy and moderating effect of self-presentation. The questionnaire survey was conducted on 568 students from 6 high schools in Shaanxi, Henan, and Shandong Provinces. After this, factor analysis and weighted least squares method were used for the empirical test. Based on theoretical and empirical analysis, this paper found the following: (1) Social networks of adolescents have obvious positive predictive effects on their sports behavior. A single online social network and an offline social network, instrumental network, emotional network, and mixed network have obvious positive predictive effects on adolescent sports behaviors. However, under the influence of multiple types of social networks, an offline social network has a negative predictive effect, while a mixed network has effects that are not as obvious. (2) Social efficacy plays an intermediary role in the relationship between social network and adolescent sports behavior. (3) The moderating effect of self-presentation is not significant.

Distributed Estimation and Control of Node Centrality in Undirected Asymmetric Networks

Measures of node centrality that describe the importance of a node within a network are crucial for understanding the behavior of social networks and graphs. In this paper, we address the problems of distributed estimation and control of node centrality in undirected graphs with asymmetric weight values. In particular, we focus our attention on $\alpha$-centrality, which can be seen as a generalization of eigenvector centrality. In this setting, we first consider a distributed protocol where agents compute their $\alpha$-centrality, focusing on the convergence properties of the method; then, we combine the estimation method with a consensus algorithm to achieve a consensus value weighted by the influence of each node in the network. Finally, we formulate an $\alpha$-centrality control problem which is naturally decoupled and, thus, suitable for a distributed setting and we apply this formulation to protect the most valuable nodes in a network against a targeted attack, by making every node in the network equally important in terms of {\alpha}-centrality. Simulations results are provided to corroborate the theoretical findings.