Social Networks

In this work, the objective is to analyze through an empirical  research the function of  the   social  networks used by the Mosques and Cultural Centers shi'as in Brazil for the promotion of peace and coexistence among the diferent religious groups. Shiite Muslims   in   Brazil   participate   Shiite   Muslims   in   Brazil   actively participate   in   government   political   instances   in   Committees   to Combat Religious Intolerance (CCIR) and use social media to convene, disseminate and strengthen the community and the Islamic speech of peace.  Two   main   examples   will   also   be   presented:   Imam   Hussein Cultural   Center   (CCIH)   and   The   Shiite   Human   Rights   Observatory (OXDIH), both in the city of Rio de Janeiro, Brazil. The discourse and actions   developed   also   support   the   pretension   of   educating   and informing the Brazilian population about the true mission of Islam to promote peace and peaceful coexistence.

In Internet-based social networks, the nodes have the most pivotal role in the processes and outcomes of the networks. Whether they pay attention to a message in the network or ignore it defines the fate of the message. One message is shared and re-shared by millions of users and another is left forgotten. The current study tries to shed light on one aspect of the role of the users in a social network: How are people different in the types of messages to which they pay attention? Some 500 Facebook users were interviewed and a creative method were used to find the public Facebook messages on which they had commented. Then, the researchers coded the data into different categories and carried out statistical analyses looking for significant relations between the types of Facebook users and the types of messages on which they commented. The results of the study include 21 significant relations, suggesting that the approach taken by this study can be promising and if completed by several other studies it could help us find local and universal patterns that affect the flow of information. With enough knowledge on social networks we must be able to design specific messages, for specific groups of people.

Social networks have been resorted to as effective platforms for social mobility in many parts of the world. This mobility occurs when social media users exploit their interpersonal relationships, especially their ‘weak ties’ (Granovetter, 1973). Social networks enable their users to be producers of information, rather than mere consumers, and to be socially and politically well-informed. They have come to function as the alternative media serving citizens rather than governments’ agendas. The paper investigates whether or not social networks are used for social and political mobility in Morocco. Practically, the boycott campaign 2018 in Morocco is considered to uncover the new services these networks are offering. All these issues are investigated in this paper through administering a survey questionnaire to a Moroccan population. A quantitative and a qualitative analysis of 112 questionnaires show that the majority of the participants not only follow social and political content on social media but also share, post, and re-tweet content. The paper indicates that social media are useful platforms for political and social mobility since they are risk-free, costless, and accessible by everybody. The participants do not deny the outstanding roles that social networks play in organizing campaigns as forms of social mobility, yet they do not consider social media a prerequisite for making such events a success because the world has been witnessing successful mass street protests wherein no use of social media platforms has been mentioned.

Abstract: This study aims at measuring the relationship between students‟ attitude toward govern-ment‟s virtual social network policy making with social security feeling, in another word, to which extent social security feeling emphasizing on social networks is determined via users‟ attitude toward government‟s media policy making? Analytical-descriptive method including survey is used in this paper; the method used for data collection is the design of the question-naire. The statistical community was “all the students in Azad University of East Tehran Branch”; the sample included “363 persons” and the sampling method was proportional sort-ing probable. Findings show that, the most correlation is related to the legitimacy index with a correlation coefficient of 85%, planning with correlation coefficient n of 45%, and decision making of government with correlation coefficient n of 41% and government policy making execution index with correlation coefficient n of 44% has the least correlation coefficient. Thus, it can be said that, by increasing legitimacy, planning, and decision making of the gov-ernment, students‟ attitude toward policy making is accelerated and amount of social security of students increase intermediately, that is, a direct and an intermediate correlation relation between three mentioned indices of government‟s media policy making with variable of stu-dents‟ social security. However, there is a weak correlation relation in another index, i.e. poli-cy execution, in another word; there is a direct and weak correlation relation between the re-lated index and social security of students. It means that, students have a negative attitude to-ward non-significant execution of policies and a weak feel of social security.

Expansion of communicational infrastructures and increase in grassroots’ access to media and cyberspace affect public’s needs, political participation and the citizens’ relationship with international, national and local political space. Nowdays[R1] , citizens in different countries have increased their awareness using communicational infrastructures and have spread out news and information in cyberspace and communicational media. They do not act passively in front of the other media like past , but they compare their life quality and legal freedoms with others by observing and evaluating the situation of their own country. In the late [R2] 2010, some protests were raised in Tunisia, Egypt, Libya and Syria that no one could anticipate them. The common point of these protests was their origin rooted in [R3] cyberspace. By dismantling Tunisia, Egypt and Libya’s governments and resignation of Yemen’s president, it can be expected that these movements can be spread in the Middle East, to other totalitarian governments of the region. In the protests process in the region and in particular in Egypt and Tunisia, protesters used cyberspace to coordinate campaigns. The organizers of these protests organizers [R4] in Egypt tried to take attention using devices that their audiences have, and shifted the leadership of protests from political parties and elites to the social networks. The current study tires to answer this question using published documents and reports: In the framework of what process and under the effect of what factors cyberspace contributed to the formation of protests movements in Egypt?

In the present technology era, a new trend of using social media or social networking sites (SNSs) has been developed. Social media has a lot to offer when it comes to education in general and second language acquisition (SLA) in particular. This study aimed at investigating the impact of Telegram, as an available social network, on learning L2 vocabulary by Iranian EFL beginners. To achieve this aim, a quasi-experimental research design was used. Thirty one Iranian students, aged 10-14, were selected through the convenience sampling method. The teacher taught English vocabulary to the participants in two ways: for four weeks by using Telegram and for another four weeks through the traditional face-to-face classroom instruction. Comparison of the scores obtained from words taught through Telegram and the scores of the traditionally-taught lexical items gave rise to the conclusion that learning vocabulary through the social network was more effective than the traditional approach. This study could help the teachers and material developers to consider incorporation of technology and common applications in language classes for the purpose of L2 vocabulary acquisition.

Technology has a profound influence on schooling in the 21st century and educators are being challenged to incorporate technological innovation to assist students in their learning. Accordingly, the face of learning is changing in general and new technologies are offering students and teachers with tools and occasions unconceivable before. In this respect, this study aimed to investigate the impact of Telegram (as a mobile technology) on collocation learning and retention of Iranian EFL learners. Participants of this study included 120 EFL learns (in two experimental (N= 60) and control (N=60) groups) who received different treatments over the study. Analyzing the results showed that there was a significant difference between the performances of experimental and control groups, of course, in favor of experimental group who confirming the effect of Telegram on improving collocational knowledge. This study implies that using social media network- Telegram has various pedagogical benefits and it can be very promising in EFL instruction.

The discovery and analysis of community structures in networks has attracted increasing attention in recent years. However there are some well-known quality metrics for detecting and evaluating communities, each of them has its own limitations. In this paper, we first deeply discuss these limitations for community detection and evaluation based on the definitions and formulations of these quality metrics. Then, we perform some experiments on the artificial and real-world networks to demonstrate these limitations. Analyzed quality metrics in this paper include modularity, performance, coverage, normalized mutual information (NMI), conductance, internal density, triangle participation ratio and cut ratio. Comparing with previous works, we go through the limitations of modularity with much more accurate details. Moreover, for the first time, we present some limitations of NMI.  In addition, however it is known that performance has tendency to get high values in large graphs, we explore this limitation by its formulation and discuss several specific cases in which performance even on small graphs gets high scores

Social media has made major changes in various e-commerce areas. One of these marketing cases is in e-commerce systems. The relationship between customers and business is very much appreciated by marketers. The use of social media by customers has given marketers the opportunity to get more information from customer feedback. Recently, in social media, marketers look for customers who have the most impact on other customers. They can influence the ideas of other customers with their opinions about a new product. In addition, influential users can have the greatest impact on specific domains. This domain may be in the domain of a product or service. Therefore, in this article influential users on social media have been studied in terms of impact in different areas. The proposed approach is for influential users using the social knowledge management approach. The knowledge cycle consists of knowledge organization, storage, retrieval, and knowledge discovery and knowledge management, where all explicit and implicit knowledge has been tried to accurately disclose affected users. In this paper, firstly, the problem was adapted to the knowledge management cycle, and in the steps of this cycle, artificial intelligence techniques such as Baysian networks were used to classify and identify influential users .In order to investigate the proposed method, various scenarios based on a variety of data sets are used for evaluation and the results of these studies show the high accuracy of the proposed method in identifying influential users.

Opinion formation is a collective behavior, describing the dynamics of people’s opinions due to their interactions. Nowadays, social media are broadly used and cause a lot of interactions among users who mainly know each other merely as a username, but significantly influence each others’ opinions and emotions. Both emotions and opinions spread across users in social media via their exchanged posts. Furthermore, based on psychology research, emotion affects people’s opinion. In this research, we implemented two binary classifiers to predict the users’ next opinions considering previous posts sent in online community: an original classifier, a classifier based on the social impact model of opinion formation; and an emotion-integrated classifier, a classifier based on the social impact model of opinion formation integrated with an emotion model to achieve an improved model. To evaluate the improved classifier, we used a dataset containing some debates from the CreateDebate.com website and compared the performance of the original classifier with the performance of the emotion integrated classifier. The experiment results show that considering emotions improves the accuracy and precision of the social impact model of opinion formation in social media.

Several factors such as engagement with peer groups, government policies, personal attitudes can affect people’s opinion about a specific subject. Most of scholars in this area focus on the interaction of individuals in social network and overlook other factors. In this paper, an opinion formation model is presented in which the internal tendencies of individuals are considered as an intrinsic property. In this model, people revise their opinion based on their neighbors’ opinion, trust/distrust between them and their own internal tendency. By internal tendency we mean a set of internal factors which may affect the decision of individuals. Simulation results show that this model is able to predict individuals’ opinion which might present their preferences to different products in social network when parameters of the model are identified and assigned. As this model can predict people’s opinion in the market, it can be used in definition of a marketing or production strategy.

With the fast growth of social media, they have become the most important platform for posting multimodal content generated by users. Much of the data on social networks such as Instagram and Telegram is multimodal data. With the aim of analyzing such multimodal data in social networks, multimodal sentiment analysis has become one of the most significant subjects for researchers in the field of emotion recognition and data mining. Although multimodal sentiment analysis of social media data for English language has been addressed in several researches recently, few studies addressed the problem for the Persian language which is the official language of more than 120 million of people around the word. In this study, a multimodal deep learning model is proposed to address this problem. The proposed method utilizes a bi-directional long short-term memory (bi-LSTM) for processing text posts and a VGG16 convolutional network for analyzing images. A new dataset of Instagram and Telegram posts, MPerSocial, containing 1000 pairs of images and Persian comments is introduced in the current study and used for evaluating the proposed method. The results of experiments show that using the fusion of textual and image modalities improves sentiment polarity detection accuracy by 20% and 8% compared with the scenario in which image and text modalities in isolation. Also, the performance of the proposed model is better than three similar deep and four traditional machine learning models. All codes and dataset used in the current study are publicly available at GitHub.  

The study of marital satisfaction and its determining factors has always been of interest to researchers in the fields of Psychology and Social Sciences. The objective of the present study was to predict marital satisfaction based on social networks and body image in women who chose to have cosmetic surgery through the mediation of emotion regulation. The research methods were correlation and path analysis. The statistical population included all women who chose to have rhinoplasty in beauty clinics in districts 1 to 5 of Tehran in 2021. From among them, 150 women were selected through convenience sampling method. They filled out Olson’s (1998) Marital Satisfaction questionnaire, Mojaradi et al.’s (2014) Social Network questionnaire, Body Image questionnaire (1970) and John and Gross’ (2003) Emotion Regulation questionnaire. Descriptive analysis and path analysis were conducted using SPSS software (version 25) and PLS software (version 3), respectively. The results showed that the direct effects of body image on emotion regulation, emotion regulation on marital satisfaction, virtual social network on emotion regulation, and virtual social network on marital satisfaction were significant (p < 0.05). However, the direct effect of body image on marital satisfaction was not significant (p < 0.05). In addition, the indirect effect of body image mediated by emotion regulation on marital satisfaction, and that of virtual social network mediated by emotion regulation on marital satisfaction of women who chose to have cosmetic surgery were not significant (p < 0.05).

Social media act as a dominant digital channel of communication, and in recent years, the use of social media in the tourism industry has also become very common. The purpose of this study is to determine the effect of social networks on oral advertisements of tourists regarding the role of feelings. This research is based on descriptive-survey method. The required information in this study is gathered through a questionnaire and a library and the statistical population of the tourists' research is in the Tajan River of Sari. The sample size is 383 subjects determined using Cochran's formula and Cronbach's alpha for the whole questionnaire was 0.89. The results of the research show that the social networks are effective on the feelings of the tourists. Therefore, in general, recognizing the feelings of the tourists to the destination should be done according to their desire to carry out advertisements and provide services. In addition, it was found that oral advertisements have a significant effect on the feelings and increasing the resurgence of the tourists to the region. According to the findings of the research, the tourists still trust oral advertisements carried out in the city more than the advertisements provided from the social networks

Social network research analyzes the relationships between interactions, people, organizations, and entities. With the developing reputation of social media, community detection is drawing the attention of researchers. The purpose of community detection is to divide social networks into groups. These communities are made of entities that are very closely related. Communities are defined as groups of nodes or summits that have strong relationships among themselves rather than between themselves. The clustering of social networks is important for revealing the basic structures of social networks and discovering the hyperlink of systems on human beings and their interactions. Social networks can be represented by graphs where users are shown with the nodes of the graph and the relationships between the users are shown with the edges. Communities are detected through clustering algorithms. In this paper, we proposed a new clustering algorithm that takes into account the extent of relationships among people. Outcomes from particular data suggest that taking into account the profundity of people-to-people relationships increases the correctness of the aggregation methods.

Introduction: User trust is one of the main ethical principles that affect the success or failure of a social network platform. The multiplicity and interaction of users in social networks leads to the risks of data breach or disclosure of users' information. Therefore, the importance of correct decision-making by the managers of this social network and the prediction of events is of great importance. Therefore, the main goal of this research is to identify the main factors affecting users' trust and solutions to compensate the lost trust among the users of this social network. Material and Methods: The current research was applied and among post-event researches. The statistical population of this research was media and communication experts who were selected using a random sample of 52 people. The questionnaire tool was made by the researcher. Data analysis was done with Kolmogorov-Smirnov test, Friedman test and dynamic systems analysis, and SPSS and Vensim simulation software were used. Results: In this research, 34 factors affecting trust in social networks were investigated. The most important of which were internet fraud, the release of malicious software, the disclosure of personal information, the type of social networks and adherence to ethical principles, etc., and things such as cooperation and coordination between people, responsibility and commitment, benevolence, excessive use of social media in priority. There is an end. The validity of this model was proved by evaluating the appropriateness of the model boundary based on the purpose of the model and ensuring the realistic behavior of the model under limit conditions. Conclusion: It is possible to increase the trust of users as well as the solutions for breaching data and privacy of users through the construction of cause and effect loops and finding the root of their main causes. Also, the effective factors and its solutions in the form of three balance circles were investigated and rooted.

Retailers need to take care of their customers and attract new customers through introducing and advertising their products, considering that social network marketing communication has created a new and profound transformation in businesses. Retailers need to exploit and be more effective. Making their connections in the created space. Therefore, in this research, we present a model for the effectiveness of marketing communication in social networks for the first time in the retail industry in Iran. The statistical population of the research was determined by using targeted sampling among experts, including academic professors and marketing managers of retail companies, and using coding in the software, four main themes were extracted from interviews with the statistical population and related to the subject of research and information. Among the researcher's notes, the codes (concepts) of branding, brand preference, sales increase, word of mouth, and commercial advertising have been the most frequent. This model can be used by retail owners and business managers to create a sustainable competitive advantage through social networks, increasing the effectiveness of market communication.

Social networks advertisements can be employed as a powerful means of communication to achieve goals such as sales, profitability and reinforcing brand image. Organizations managers have established a department titled “public relations” in their organizations, through which they communicate with individuals inside and outside the organization, so that they can fulfill their goals at lower costs and within shorter time by informing and persuading those individuals. In this regards, the present study is aimed at evaluating the extent to which public relations of private organizations employ social networks to introduce their products and services. Research population consists of managers and public relation experts of private sector’s organizations in Yazd, Iran. The present study takes a survey method and is regarded as field-work research. Sampling method is based probability and availability. Due to the limited population, 76 individuals were selected as the sample through limited population formula. Data was analyzed via Smart-PLS. results reveal that public relations of private organizations employ social networks at an optimal and acceptable level to introduce their products and services. Hence the hypothesis of the study is confirmed.

Virtual space and the associated social networks, like many other emerging phenomena, have both positive and negative consequences in various aspects of life. The undeniable impact of this space is particularly significant in the national security of countries, as it can create numerous opportunities for national security along with the changes and developments it brings about. This research aims to identify the opportunities that social networks create for the infrastructure of national security. Data were collected through grounded theory and in-depth interviews with 16 experts in the fields of politics and virtual space. The data were analyzed using open, axial, and selective coding methods, employing the Strauss and Corbin approach. The research results indicate that virtual social networks can provide unique opportunities for national security by strengthening the infrastructures of social, political, cultural, economic, and environmental security. The research results are presented in the form of a paradigm model of opportunities.

Purpose: Rumor management in the context of social networks for government organizations is very important in order to maintain the organization's reputation and improve its performance. Therefore, the current research was conducted with the aim of designing a qualitative pattern of rumor management in the context of social networks in the Iranian government organizations. Methodology: The current research in terms of purpose was applied and in terms of its implementation method was qualitative. The research population was experts in the field of public administration and organizational behavior in the field of research. The sample of the present study according to the principle of theoretical saturation was estimated to be 15 people which this number was selected by the purposeful sampling method and they were subjected to semi-structured interviews, and its validity was confirmed by the triangulation method and its reliability was estimated by the Cohen's kappa coefficient method 0.719. Data were analyzed by coding method in MAXQDA-2020 software. Findings: The findings of this research indicated that 95 open codes, 5 core codes and 2 selective codes were identified for rumor management in the context of social networks in the Iranian government organizations. In this study, the selected codes were included the malicious rumors with three core codes of bad feelings, rumor transmission and thinking power, and innocent rumors with two core codes of trust building and reference support. Finally, the output of the software was drawn for the qualitative pattern of rumor management in the context of social networks in the Iranian government organizations. Conclusion: Based on the findings of the present research, the managers of Iranian government organizations can prevent their destructive effect on the advancement of the organization's goals by managing malicious rumors and innocent rumors.