Social Network Interactions Research Articles

Depressive symptoms are associated with social isolation in face-to-face interaction networks

Individuals with depressive symptoms are more likely to be isolated in their social networks, which can further increase their symptoms. Although social interactions are an important aspect of individuals’ social lives, little is known about how depressive symptoms affect behavioral patterns in social interaction networks. This article analyzes the effect of depressive symptoms on social interactions in two empirical settings (Ntotal = 123, Ndyadic relations = 2,454) of students spending a weekend together in a remote camp house. We measured social interactions between participants with Radio Frequency Identification (RFID) nametags. Prior to the weekend, participants were surveyed on their depressive symptoms and friendship ties. Using state-of-the-art social network analysis methods, we test four preregistered hypotheses. Our results indicate that depressive symptoms are associated with (1) spending less time in social interaction, (2) spending time with similarly depressed others, (3) spending time in pair-wise interactions rather than group interactions but not with (4) spending relatively less time with friends. By “zooming in” on face-to-face social interaction networks, these findings offer new insights into the social consequences of depressive symptoms.

Intercultural competence development via online social networking: the Japanese students’ experience with internationalisation in U.S. higher education

ABSTRACTThis study examines the possibility that interaction through social network platforms can serve as an informal means of developing intercultural competence among international students in higher education settings. Japanese students studying in the United States at a university in the Northwestern US were invited to participate in a mixed-method study involving interviews about their social network use and interactions, and a structured questionnaire measure of intercultural competence development. Overall, the results indicate that those in the top tertile of intercultural competence development tended to describe more proactive social ways and benefits of interacting with potential sources of support over social media, whereas those in the bottom tertile tended to describe the importance and use of social media for passive consumption of information. The implications for the incorporation of social network platforms into higher-education programs for internationalisation and intercultural competence development are discussed.

Campus Connections: Student and Course Networks in Higher Education

Residential higher education brings thousands of students together for multiple years and offers them an array of shared intellectual experiences and a network of social interactions. Many of these intellectual and social connections are formed during courses. Students are connected to students through courses they take together, and courses are connected to one another by students who take both. These courses and the students who take them form a bipartite network that encodes information about campus structures and student experiences. Because all institutions of higher education collect and maintain precise records of what courses students take, it is possible to assemble a student-course network that quantitatively describes the interactions among students and courses. We provide an example that demonstrates the identification of courses effective at creating unique connections among students and reveals how students and majors can be strongly connected or dispersed. We show how social network analysis can be used to improve our understanding of the learning environment at the University of Michigan, and we hope that this kind of analysis is of interest to persons at other institutions.

Analysis and control of epidemics in temporal networks with self-excitement and behavioral changes

The complexity of interaction patterns among individuals in social systems plays a fundamental role on the inception and spreading of epidemic outbreaks. Empirical evidence has shown that the network of social interactions may co-evolve with the spread of the disease at comparable time-scales. Time-varying features have also been documented in the study of the propensity of individuals toward social activity, leading to the emergence of burstiness and temporal clustering. These temporal network dynamics are not independent of the disease evolution, whereby infected individuals could experience changes in their tendency to form connections, spontaneously or due to exogenous control policies. Neglecting these phenomena in modeling epidemics could lead to dangerous mispredictions of an outbreak and ineffective control interventions. In this paper, we propose a mathematically tractable modeling framework that relies on a limited number of parameters and encapsulates all these instances of complex phenomena through the lens of activity driven networks. Hawkes processes, Markov chains, and stability theory are leveraged to assist in the analysis of the framework and the formulation of theory-based control interventions. Our mathematical findings confirm the intuition that bursty activity patterns, typical of humans, facilitate epidemic spreading, while behavioral changes aiming at individual isolation could accelerate the eradication of epidemics. The proposed tools are demonstrated on a real-world case of influenza spreading in Italy. Overall, this work contributes new insight into the theory of temporal networks, laying the foundations for the analysis and control of spreading processes over networks with complex interaction patterns.

UNDERSTANDING SOCIAL ENGINEERING THREATS IN MASSIVELY MULTIPLAYER ONLINE OLE-PLAYING GAMES: AN ISSUE REVIEW

In this developing virtual era, the recreational activities like online games have turned into very intriguing tasks by giving whole new identities and avatars to individuals. This allows the individual to interact and also do anything that seemed possible as well as impossible in real lives. This virtual identification sometimes crosses into the real world, as they allow gamers to sell virtual game items for real-world money in markets and sometimes even requires use of real money to create or purchase personal property in their online world. This has created an opportunity for virtual crimes involving social and technical risks. The widespread adoptions of such Massively Multiplayer Online Role-Playing Games (MMORPGs) have not only become a dedicated activity for gamers but also act as a platform for social engineers. Social Engineering is considered as an art of collecting sensitive data/information by persuasion or manipulation of individuals and is the first step involving social risk in virtual crimes. MMORPGs were found to be highly socially interactive environments providing the opportunity to not only form relationships but also to be targeted by social engineers. In this study, we are reviewing and evaluating social interactions and psychological factors of MMORPG gamers which are making them vulnerable to social engineering threats. Various studies have assessed the psychological factors making an individual vulnerable to social engineering on social network interactions and also few studies have analysed the behaviours and relationships of gamers in online interactions. Observing such factors, in this study we analysed how the social engineers, disguised as fellow gamer, would target similar psychological vulnerabilities in the gamers by using social interaction platform on MMORPGs to gather personal and sensitive data from the targeted gamers.

Переживание относительной депривации как фактор копинг-стратегии избегания в сетевой коммуникации

Objective: the relationship between a relative deprivation and communication in social networks, in particular, with avoidance coping in the situations of communicative difficulties. Background: the study is focused on coping with difficult situations through the analysis of meta-determinants of construction of the representations about social world, in particular, in the conditions of social network interaction among youth persons. Study design and participants: the study was conducted as a survey involving 193 active users of the social network Vkontakte. Measurements: a double mediation model was tested with a relative deprivation as an independent variable, avoidance coping as a dependent variable, and a perceived threat and an attribution of aggressive intentions as the mediators of this relationship. Results: the results indicate that a relative deprivation is associated with an increase of perceived threat, which in turn increases a likelihood of attributing to people with dissimilar values and attitudes of “bad” intentions and leads to avoiding network interaction. At the same time, the results demonstrate that group threat does not a significant mediator of the relationship between a relative deprivation and network behavior. Conclusions: relative deprivation is associated with avoidance coping in social network communication both directly and indirectly through the actualization of additional social and cognitive variables.

Correction to: Innovation and improvement of visual communication design of mobile app based on social network interaction interface design

Correction to: Innovation and improvement of visual communication design of mobile app based on social network interaction interface design

La cognición en la web a través de un chatbot como elemento disruptivo

Today, the companies try to basic needs of their clients, the use of technology would help solve and have efficient communication in real time with them. Therefore, the objective of this project is to perform a disruptive technological tool, a chatbot, and make an analysis of your employment in uses a social network (Facebook), to break paradigms of behavior in a massive number of users and that maximizes the social The main subject is the commercial impact, complete credibility and satisfaction this tool in the user (around the company that apply chatbot). Nowadays, companies seek to satisfy most of their client's needs; that tool assistance to reduce the troubles between them and the company. Moreover it is well known that today's generations do not live without social networks interactions and even more so that they are buying products through the internet. Finally, there are companies that make use of this technology: Aero México, National Geographic, Starbucks, Next_u, etc.

Improve the performance of peer-to-peer networks within publish/ subscribe systems by using PeerSim simulator within Eclipse Environment

Publish/ subscribe (pub/ sub) is a popular communication paradigm in the design of large-scale distributed systems. We are witnessing an increasingly widespread use of pub/ sub for a wide array of applications in industry, academia, financial data dissemination, business process management and does not end in social networking sites which takes a large area of user interests and used network bandwidth. Social network interactions have grown exponentially in recent years to the order of billions of notifications generated by millions of users every day. So, it has become very important to access in the field of publishing and subscription networks, especially peer-to-peer (P2P) networks in many ways like the publication speed for events And the percentage of loss in the incoming events of the participants. Peer-to-peer systems can be very large and include millions of nodes, those nodes join and leave the network continuously, and these characteristics are difficult to handle. The evaluation of a new protocol in a real environment, particularly in the early stages, was considered impractical. Hence the need for a simulator to perform such a function to facilitate the simulation of researchers and this emulator is an open source simulator running within the Eclipse environment. In this research we have adopted a new method of selecting nodes within the table of vicinity protocol. This method is concentrated in that the far node increases the probability of its inclusion in the table more than the adjacent node. and The proposed network that uses the Polder Cast protocol was modelled using PeerSim software for modelling deployment and subscription networks within the eclipse environment so that the event delivery service is a Peer-2-Peer network and the method used to register is subject-based (Topic-Based). experimental results showed noticeable improvement in the publication speed for events by 51.11% compared to the original design of the protocol. And The percentage of event loss was reduced by 20%.

What Twitter teaches us about patient-provider communication on pain.

The objective of this study was to understand how pain patients and health care providers (HCPs) are engaging on Twitter and what insights this engagement might provide. By identifying how information is spread by and between these audiences, organizations such as patient advocacy groups may be better poised to develop and share materials that facilitate online communication between HCPs and pain patients, with an end goal of improving a shared decision-making process around pain management. We analyzed the Twitter audiences most engaged on pain topics by conducting a Social Network Analysis (SNA) of a large network of connected users on Twitter. The analysis segmented users based on the sources they cited and measured their influence based on who follows them. As a point of comparison, we also conducted an SNA of Twitter audiences most engaged on oncology topics. Oncology was chosen as a comparison due to what was perceived to be a highly developed online network of both patients and physicians. The populations included in this research included 12,086 accounts that were highly engaged on pain-related topics, and 12,617 accounts that were highly engaged on oncology-related topics. Network statistics were generated for variables including: word use, sources cited, retweets, and mentions. We also statistically analyzed the Twitter follow relationships among select HCPs and patient groups within each SNA. The creation of separate pain and oncology SNAs allowed the team to compare relationships and engagement related to these topics. We found that on Twitter, pain patients and providers appear to interact less than oncology patients and providers. Pain patients do not appear to follow medical professionals or share medical or health-related information on Twitter to the same extent as oncology patients. In addition, we found that pain patients do not communicate on Twitter in the same language as HCPs. Our results are important because they underscore that challenges in communication are not just problematic in face-to-face interactions, but also in digital social network (Twitter) interactions, serving as an additional roadblock to what can be shared decision-making opportunities around pain management. Contributing to this roadblock is access to quality information and a potential need for an online, evidence-based resource hub that could benefit the pain patient community in the same way that cancer.gov serves as a source of aggregated materials for oncology patients and HCPs. This study is an illustration of how social media networks like Twitter can be used to better understand the relationships, language gaps, and shared resources between pain patients and providers and offers a template for using digital social network (Twitter) interactions to research other difficult-to-treat or rare disease states.

Interaction Models for Detecting Nodal Activities in Temporal Social Media Networks

Detecting nodal activities in dynamic social networks has strategic importance in many applications, such as online marketing campaigns and homeland security surveillance. How peer-to-peer exchanges in social media can facilitate nodal activity detection is not well explored. Existing models assume network nodes to be static in time and do not adequately consider features from social theories. This research developed and validated two theory-based models, Random Interaction Model (RIM) and Preferential Interaction Model (PIM), to characterize temporal nodal activities in social media networks of human agents. The models capture the network characteristics of randomness and preferential interaction due to community size, human bias, declining connection cost, and rising reachability. The models were compared against three benchmark models (abbreviated as EAM, TAM, and DBMM) using a social media community consisting of 790,462 users who posted over 3,286,473 tweets and formed more than 3,055,797 links during 2013–2015. The experimental results show that both RIM and PIM outperformed EAM and TAM significantly in accuracy across different dates and time windows. Both PIM and RIM scored significantly smaller errors than DBMM did. Structural properties of social networks were found to provide a simple and yet accurate approach to predicting model performances. These results indicate the models’ strong capability of accounting for user interactions in real-world social media networks and temporal activity detection. The research should provide new approaches for temporal network activity detection, develop relevant new measures, and report new findings from large social media datasets.

The Implementation of Clique Strategy in Regrouping Program to Increase Farmer’s Interest and Loyalty in Sugarcane Farming

The area size of sugarcane planting nationally shows a decrease. This is also marked by a decrease in the interest of farmers planting sugarcane and low loyalty to the sugar factory. In 2014, the government established a sugarcane management regrouping program. The regrouping program provides benefits for the efficiency of sugarcane planting, more effective in cutting and transport processes, forging farmer group and sugar factory, and increasing farmers' loyalty to the sugar factory. The weakness of the regrouping program is that it emphasizes technical aspects only. The criterion of the social aspect is essential because this always saves problems related to communication networks and establishing cooperation. Through the clique strategy, this can conduct a communication network analysis in regrouping. Regrouping programs can build social interaction and communication networks. The form and level of communication network structure in the regrouping program can place actors or farmers build communication networks and cooperate in sugarcane farming. Understanding the role of cooperation networks between farmers or groups determines the success of regrouping sugarcane.JEL Classification: P32, O35, Q18

LÍDERES POLÍTICAS ARGENTINAS EN TWITTER. UN ESTUDIO EN EL MARCO DE LAS ELECCIONES 2017

Fil: Zunino, Esteban. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mendoza. Instituto de Ciencias Humanas, Sociales y Ambientales; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Politicas y Sociales; Argentina

Information credibility evaluation in online professional social network using tree augmented naïve Bayes classifier

In recent years, companies depend on the Internet for posting job advertisements and attracting qualified personnel. However, with the vast number of Internet users and the tremendous amount of information on the Internet, it is difficult to accurately evaluate the credibility of the information that candidates provide on the Internet. Therefore, we propose an approach to assess information credibility in terms of trustworthiness and authority to identify unreliable user profiles in online professional social networks. Our approach calculates the trustworthiness probabilities of user profile information using the Tree Augmented Naive Bayes (TAN) classifier. It also measures the authority of individual users by applying the PageRank algorithm for analyzing the user interactions in the professional social networks. Finally, a group of LinkedIn users’ profiles is selected for conducting experiments to validate the proposed approach. Experiments based on a real-world scenario show that our approach integrating the TAN Bayes and PageRank algorithm outperforms other existing approaches in classification accuracy. In addition, the approach has been applied to another social network, namely, Maimai in China to further demonstrate its usefulness.

CORRELATES OF LONELINESS AMONG OLDER ASIAN IMMIGRANTS: A SYSTEMATIC REVIEW

Loneliness is a prevalent social concern among older adults, which calls for attention as a condition itself and its influence on mental and physical conditions. However, limited efforts have been made to understand loneliness, particularly among immigrant older adults. Guided by the ecological perspective, the present study contributes to the literature by providing a systematic review of the prevalence and individual-, household-, and community-level correlates of loneliness among Asian older immigrants, one of the fast-growing immigrant population. Following the PRISMA guideline, we systematically searched eight electronic databases to identify relevant empirical research articles. Of the 828 articles identified, ten articles met the inclusion criteria. Majority of these articles focused on older Chinese and Korean immigrants. On the individual level, migration grief, longer length of residence, and weaker ethnic attachment were linked to higher level of loneliness, indicating that immigration can be a challenging experience for later life well-being of Asian older adults. Other identified correlates include mental and functional impairment and worsening health changes. On the household level, while living alone was a commonly identified correlate of loneliness, those who live with family also reported loneliness when they have fewer interactions with their family members. On the community-level, smaller social network and lack of social support and interactions were correlates of loneliness. The findings of the present study are helpful for identifying older Asian immigrants who may be at risk of loneliness and implicates that the efforts to mitigate the loneliness need to be made at various ecological levels.

Student Attitude to Intercultural Communication and Intercultural Interaction in Social Networks

The relevance of this article is conditioned by the need to analyze and study the student views and positions on the issue of intercultural communication and intercultural interaction, as it is obvious that in the foreseeable future we will continue to live in a multi-ethnic, multicultural society and strive for the successful coexistence of many different cultures in social networks. The aim of the study is to identify the attitude of students communicating in social networks to ethnocentrism. The leading methods for the study of this problem are the methods of questioning and testing, allowing making a qualitative analysis of the peculiarities of the attitude of students communicating in social networks, to ethnocentrism, and allowing identifying the position of students on the issue of intercultural communication and intercultural interaction. The article reveals the criteria peculiar to the representatives of different ethnic groups with a high level of ethnocentrism. These students consider everything that happens in their culture to be natural and correct, and in others to be wrong; consider the customs of their group as universal: “what is good for us is good for others”; consider the norms, roles and values of their group to be absolutely correct; act so that the representatives of their group feel like winners; feel hostility towards external groups. It is determined that the presence of a set of these criteria and properties (or most of them) in the ethnic consciousness of the individual, allows us to talk about a high level of ethnocentrism. The novelty and originality of the study lies in the fact that a set of criteria characterizing the opinion of students, supporters of cultural relativism is revealed: they are often in contact with representatives of other ethnic groups and nationalities in social networks; absolutely do not feel discomfort in communicating with foreign cultural representatives, on the contrary, such communication is of great interest; in the formation of any group do not give preference to representatives of their own people, and are guided by other selection criteria; do not regard the culture of their people as a role model for other Nations. A set of criteria is identified for supporters of ethnocentrism: they believe everything that happens in their culture, natural and correct and others wrong; consider the customs of their group as universal; consider the norms, roles and values of their group is certainly correct; feel hostility towards external groups; in General, are rarely in contact with the representatives of other ethnic groups and nationalities; feel discomfort in communicating with other cultures representatives; believe that the loss of identity of their ethnic group is an unambiguously negative phenomenon; they do not consider the cultures of all peoples equally important and equal.

Advanced Machine Learning Technique to Handle Filtering Unwanted Messages in Online Social Networks

Social networks are increased in present days because of communication between different users like Face book, Google and Twitter. Major fundamental issue behind online social networks is control user’s messages in-front of sharing rumor related messages and posts unwanted messages. It is still main challenge to define user’s share other user’s details in social network communication. In this paper, Greedy Heuristic based Advanced Short Text Classifier (GHASTC) used to classify filtering with rumor related classification for multi user’s interaction in social networks. This hybrid approach gives direct control to users to control unwanted data posted on own space. The proposed approach works with rule based filtering system, which consists a customized filtering for unwanted content in online social networks. The experimental results show efficient filtering results with comparison of traditional techniques.

Settlement scaling theory: Bridging the study of ancient and contemporary urban systems

A general explanatory framework for the social processes underpinning urbanisation should account for empirical regularities that are shared among contemporary urban systems and ancient settlement systems known throughout archaeology and history. The identification of such shared properties has been facilitated by research traditions in each field that define cities and settlements as areas that capture networks of social interaction embedded in space. Using Settlement Scaling Theory (SST) – a set of hypotheses and mathematical relationships that together generate predictions for how measurable quantitative attributes of settlements are related to their population size – we show that aggregate properties of ancient settlement systems and contemporary metropolitan systems scale up in similar ways across time, geography and culture. Settlement scaling theory thus provides a unified framework for understanding and predicting these regularities across time and space, and for identifying putative processes common to all human settlements.

Posterior Contraction Rates for Stochastic Block Models

With the advent of structured data in the form of social networks, genetic circuits and protein interaction networks, statistical analysis of networks has gained popularity over recent years. The stochastic block model constitutes a classical cluster-exhibiting random graph model for networks. There is a substantial amount of literature devoted to proposing strategies for estimating and inferring parameters of the model, both from classical and Bayesian viewpoints. Unlike the classical counterpart, there is a dearth of theoretical results on the accuracy of estimation in the Bayesian setting. In this article, we undertake a theoretical investigation of the posterior distribution of the parameters in a stochastic block model. In particular, we show that one obtains near-optimal rates of posterior contraction with routinely used multinomial-Dirichlet priors on cluster indicators and uniform or general Beta priors on the probabilities of the random edge indicators. Our theoretical results are corroborated through a small scale simulation study.

Efficient team structures in an open-ended cooperative creativity experiment

Creativity is progressively acknowledged as the main driver for progress in all sectors of humankind's activities: arts, science, technology, business, and social policies. Nowadays, many creative processes rely on many actors collectively contributing to an outcome. The same is true when groups of people collaborate in the solution of a complex problem. Despite the critical importance of collective actions in human endeavors, few works have tackled this topic extensively and quantitatively. Here we report about an experimental setting to single out some of the key determinants of efficient teams committed to an open-ended creative task. In this experiment, dynamically forming teams were challenged to create several artworks using LEGO bricks. The growth rate of the artworks, the dynamical network of social interactions, and the interaction patterns between the participants and the artworks were monitored in parallel. The experiment revealed that larger working teams are building at faster rates and that higher commitment leads to higher growth rates. Even more importantly, there exists an optimal number of weak ties in the social network of creators that maximizes the growth rate. Finally, the presence of influencers within the working team dramatically enhances the building efficiency. The generality of the approach makes it suitable for application in very different settings, both physical and online, whenever a creative collective outcome is required.