scholarly journals Wasta: Advancing a Holistic Model to Bridge the Micro-Macro Divide

2020 ◽  
Vol 16 (3) ◽  
pp. 657-685 ◽  
Author(s):  
Sa'ad Ali ◽  
David Weir

AbstractThis article offers a synthesis of understandings of wasta, seen as a form of social network prevalent in the Arab Middle East. Whilst there has been increasing interest in this practice, research remains fragmented and has been criticised for its limited theoretical rigor. To address this issue, a systematic review of peer-reviewed journal articles exploring wasta published between 1993 and 2019 was conducted. We analysed the identified papers according to the theoretical lens from which wasta was viewed, creating a bridge between a theoretical focus on the macro aspect of wasta and an alternative focus on its micro aspects, leading to the development of a holistic model of wasta. The model also helps us to understand the complexity of wasta, both as the network itself and as the social ties that exist among its members, and sheds light on the complex nature of the role and interactions of the wasta. The findings respond to calls for more holistic and inclusive research to inform social networks research and bridge the micro–macro divide. This article offers recommendations to future researchers to build on the holistic and emic approach to wasta research adopted here.

Author(s):  
Weiyu Zhang ◽  
Rong Wang

This paper examines interest-oriented vs. relationship-oriented social network sites in China and their different implications for collective action. By utilizing a structural analysis of the design features and a survey of members of the social networks, this paper shows that the way a social network site is designed strongly suggests the formation and maintenance of different types of social ties. The social networks formed among strangers who share common interests imply different types of collective action, compared to the social networks that aim at the replication and strengthening of off-line relationships.


Management ◽  
2019 ◽  
Author(s):  
Sana Ansari ◽  
Dalhia Mani

The field of social networks focuses on the relationships among social actors, and on patterns that emerge from the structure of the social network and its implications (Wasserman and Faust’s Social Network Analysis: Methods and Applications). Social network research argues that actors (e.g., individuals or firms) are embedded within a network of relations, and that their behavior and choices cannot be studied independent of the social relations that shape and structure behavior. Social network perspective views relations among the social actors as ties and regular patterns in relationship as structure. Ties are the relational linkages that allow flow of resources between the actors, both tangible and intangible. Multiple actors form a web of relational ties, which can be either economic, social, or political. Networks can be of different types based on the content of the relational tie between the actors. For instance, collaboration ties between actors make a collaboration network or a co-author relation between actors makes a co-authorship network. Networks can also be at different levels of analysis—for instance, an intraorganizational friendship network is at the level of individuals while a network of intercountry trade relations is at the level of country. Ties between actors can be of different strengths (for instance, friends who meet daily versus once a year) and can also be negative or positive ties (e.g., competition networks versus collaboration networks). This article summarizes the latest research on social ties and network structure by focusing on the main thematic discussions in the field: (1) networks and strategic, governance behavior; (2) workplace networks; (3) collaboration and knowledge networks; (4) networks, personality, and individual differences; (5) entrepreneurial and family business networks; and (6) networks and social media. To ensure a comprehensive review of the topic, the article used search keywords, “networks,” or “network structure,” or “social networks,” or “social ties,” and was limited to articles in the top fourteen management journals, namely: Academy of Management Journal, Strategic Management Journal, Organization Science, Management Science, American Journal of Sociology, American Sociological Review, Administrative Science Quarterly, Academy of Management Review, Journal of Management Studies, Journal of Business Venturing, and Entrepreneurship Theory and Practice. The search was further limited to the six-year period from 2014–2019, since previous articles on organizational networks and brokerage in Oxford Bibliographies have summarized the research in this domain prior to 2014.


2020 ◽  
Vol 4 (2) ◽  
pp. 255
Author(s):  
Nawaar Faizatun Ashri ◽  
Nurhadi Nurhadi ◽  
Okta Hadi Nurcahyono

The purpose of this research was to know the social networks of smoking behavior of active smoker students, especially in high school of Surakarta. This study aimed to describe agents that contribute to form this behavior through social ties based on Marwell theory of Social Networks. The methods that used in this study was descriptive qualitative with ethnography approach. The data was collected through interview using WhatsApp application. The data was analyzed with theory of Social Network from Marwell and compared to related researches. Informants in this study were ten high school students in Surakarta who active in smoking behavior. The results of this study indicated that its habit started from curiosity and imitation of others into an action that receive “support” from people around. It could be concluded that student's decision of smoking was determined by their relationship with the social milieu which was also an active smoker, such as family and peer groups.


Author(s):  
Sanjay Chhataru Gupta

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.


Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.


2021 ◽  
pp. 002076402110175
Author(s):  
Roberto Rusca ◽  
Ike-Foster Onwuchekwa ◽  
Catherine Kinane ◽  
Douglas MacInnes

Background: Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing. Aims: To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit. Method: A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support. Results: The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network. Conclusions: People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.


2020 ◽  
Vol 144 ◽  
pp. 26-35
Author(s):  
Rem V. Ryzhov ◽  
◽  
Vladimir A. Ryzhov ◽  

Society is historically associated with the state, which plays the role of an institution of power and government. The main task of the state is life support, survival, development of society and the sovereignty of the country. The main mechanism that the state uses to implement these functions is natural social networks. They permeate every cell of society, all elements of the country and its territory. However, they can have a control center, or act on the principle of self-organization (network centrism). The web is a universal natural technology with a category status in science. The work describes five basic factors of any social network, in particular the state, as well as what distinguishes the social network from other organizational models of society. Social networks of the state rely on communication, transport and other networks of the country, being a mechanism for the implementation of a single strategy and plan. However, the emergence of other strong network centers of competition for state power inevitably leads to problems — social conflicts and even catastrophes in society due to the destruction of existing social institutions. The paper identifies the main pitfalls using alternative social networks that destroy the foundations of the state and other social institutions, which leads to the loss of sovereignty, and even to the complete collapse of the country.


2017 ◽  
Vol 25 (3) ◽  
pp. 21-39 ◽  
Author(s):  
Luan Gao ◽  
Luning Liu ◽  
Yuqiang Feng

Prior research on ERP assimilation has primarily focused on influential factors at the organizational level. In this study, the authors attempt to extend their understanding of individual level ERP assimilation from the perspective of social network theory. They designed a multi-case study to explore the relations between ERP users' social networks and their levels of ERP assimilation based on the three dimensions of the social networks. The authors gathered data through interviews with 26 ERP users at different levels in five companies. Qualitative analysis was used to understand the effects of social networks and interactive learning. They found that users' social networks play a significant role in individual level ERP assimilation through interactive learning among users. They also found five key factors that facilitate users' assimilation of ERP knowledge: homophily (age, position and rank), tie content (instrumental and expressive ties), tie strength, external ties, and centrality.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.


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