Social network analysis (SNA) is an increasingly popular approach that provides researchers with highly developed tools to map and analyze complexes of social relations. Although a number of network scholars have explicated the assumptions that underpin SNA, the approach has yet to be discussed in relation to established philosophies of science. This article argues that there is a tension between applied and methods-oriented SNA studies, on the one hand, and those addressing the social-theoretical nature (...) and implications of networks, on the other. The former, in many cases, exhibits positivist tendencies, whereas the latter incorporate a number of assumptions that are directly compatible with core critical realist views on the nature of social reality and knowledge. This article suggests that SNA may be detached from positivist social science and come to constitute a valuable instrument in the critical realist toolbox. (shrink)

Despite iterative learning design being increasingly implemented, such approaches are often delineated by well-defined periods of design/implementation. However, second-order cybernetics, which suggests a participatory approach to learning design, involves responsively adapting learning environments to meet students’ needs, treating them as agentic participants in the classroom. In our mixed methods study, we investigate whether such a process can facilitate egalitarian participation and collaborative interactions in a technology-assisted classroom. We use the example of a graduate psychology class of 17 students and suggest (...) that adaptation of live-chat activities by a participant observer on the Reddit social media platform that supplemented the in-person lecture dynamically, using a network analysis and qualitative ethnography as a modelling facility mimicked the ongoing feedback loops of social media platforms, enabling students to use social media with a critical eye, and engage in productive collaboration. Our quantitative results present network graphs for weekly eigen centrality to understand the egalitarian nature of the network, and transitivity to understand the likelihood for collaboration between more than two agents. Our qualitative results elaborate selected Reddit posts, and weekly field notes to explain how redesigning the chat weekly helped augment lecture-based discussion with the instructor and critique of student presentations, spurring egalitarian participation through a space-place dialectic. Students also provided end-semester feedback that was analyzed using inductive coding, to design future courseware. (shrink)

In this chapter, we discuss social network analysis as a method for the history of economics. We argue that social network analysis is not primarily a method of data representation but foremost a method of discovery and confirmation. It is as such a promising method that should be added to the toolbox of the historian of economics. We furthermore argue that, to be meaningfully applied in history, social network analysis must be (...) complemented with historical knowledge gained by other means and often by more traditional, mostly qualitative, methods. It should therefore be viewed as a method that complements rather than replaces more established approaches in the history of economics. (shrink)

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach (...) by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. (shrink)

Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It (...) is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts. (shrink)

Local food systems are growing, and little is known about how the constellation of farms and markets change over time. We trace the evolution of two local food systems over six years, including a dataset of over 2690 market connections between 1520 locations. Longitudinal social network analysis reveals how the architecture, actor network centrality, magnitude, and spatiality of these supply chains shifted during the 2012–2018 time period. Our findings demonstrate that, despite growth in the number of (...) farmers’ markets, grocery stores, farms and restaurants in both counties, each local food system also experienced high turnover rates. Over 80% of the market connections changed during the study period. Farms, farmers’ markets, and grocery stores showed a 40–50% ‘survival’ rate, indicating their role in sustaining local food systems over longer time periods. Other actors, such as restaurants, had a much higher turnover rate within the network. Both food systems became more close-knit and consolidated as the center of gravity for both local food systems pulled away from urban areas toward rural farmland. Evidence of both growth and decay within local food systems provides a new understanding of the social networks behind local food markets. (shrink)

Social network research is widely considered atheoretical. In contrast, in this article I argue that network analysis often mixes two distinct theoretical frameworks, creating a logically inconsistent foundation. Relationalism rejects essentialism and a priori categories and insists upon the intersubjectivity of experience and meaning as well as the importance of the content of interactions and their historical setting. Formalism is based on a structuralist interpretation of the theoretical works of Georg Simmel. Simmel laid out a neo-Kantian (...) program of identifying a priori categories of relational types and patterns that operate independently of cultural content or historical setting. Formalism and relationalism are internally consistent theoretical perspectives, but there are tensions between them. To pave the way for stronger middle-range theoretical development, I disaggregate the two approaches and highlight the contradictions that must be addressed or resolved for the construction of any general and inclusive theory. (shrink)

Bourdieu carved out a distinctive analytical niche for his reflexive sociology. His epistemological tool of field analysis, sometimes coupled with statistical correspondence analysis, is particular...

Partner selection is the primary aspect of the formation of knowledge collaboration teams. We propose a method of partner selection for KCTs based on a weighted social network analysis method in which the individual knowledge competence and the collaboration performance of candidates are both considered. To select the desired partners, a biobjective 0-1 model is built, integrating the knowledge competence and collaboration performance, which is an NP-hard problem. Then, a multiobjective genetic algorithm is developed to solve the (...) proposed model. Finally, a real-world example is provided to illustrate the applicability of the model, and the MOGA is implemented to search for Pareto solutions of partner selection for KCT in this case. Moreover, some simulation examples are used to test the efficiency of the algorithm. The results suggest that the proposed method can support effective and practical partner selection. (shrink)

Young adolescents’ online bullying behavior has raised a significant amount of academic attention. Nevertheless, little is known about the social context in which such negative actions occur. The present paper addresses this issue and examines how the patterns of traditional bullying and cyberbullying are related, and how electronic forms of bullying can be linked to the social context at school. To address these questions, social network analysis was applied to examine the networks of social (...) interactions and bullying among an entire grade of 1,458 thirteen- to fourteen-year-old pupils. The results show that cyberbullying is an extension of traditional bullying as victims often face the same perpetrators offline and online, there is evidence of mutual cyberbullying among youngsters, and cyberbullying is more likely to occur in same-gender and same-class students. The implications for future research and prevention of cyberbullying are discussed. (shrink)

Modern cities form city networks through complex social ties. City network research is widely applied to guide regional planning, infrastructure construction, and resource allocation. China put forward the Yellow River Basin Development Strategy in 2019, but no research has been conducted on regional social connections among cities. Based on the gravity model modified by two-way “time distance” between cities, this is the first study to empirically examine the intensity and structure of the entire city network in (...) the Yellow River basin using the social network analysis method and ArcGIS software. The connection rules of the cross-city transfer of city officials in the basin are also investigated to illustrate the official ties between cities. The results suggest that the intensity of two-way connections between cities is generally low in the Yellow River basin and there is a positive correlation between city network development level and regional economic development level. The development gap between cities on the north and south banks is larger than that between the east and west regions, and some cities in the middle and upper reaches of the river are marginalized in the network. The status of the central cities in the Yellow River basin is distinct, but their connecting and leading abilities are not strong, showing an inverted T-shaped spatial distribution. The subgroups of city networks have strong internal connections, while the connection among subgroups is weak and the development shows a partitioned and fragmented pattern, making it difficult to form linkages among the upper, middle, and lower reaches. The “beaded chain” spatial development strategy can be adopted in the river basin planning, giving priority to strengthening the links within subgroups of cities and among adjacent subgroups, building central city chains, and reinforcing the overall basin management. (shrink)

In this study, we sorted out the research hotspots in sports science by bibliometric method and also used social network analysis to explore the relationship between knowledge networks and their scientific performance. We found 38 high-frequency keywords with obvious curricular nature or classical direction of sports science research and 4 high-frequency research groups. The topics of hotspots covered the secondary disciplines of sports science: physical education and training, national traditional sports, sports human science, and sports humanities and (...) sociology. However, sports human science research is less; therefore, accelerating the research of sports human science is the focus of future research. Meanwhile, we use social network structure analysis to study the relationship between knowledge elements in knowledge networks and their scientific performance. In addition to betweenness centrality, the closeness centrality, clustering coefficient, and structural holes of knowledge elements are significantly and positively related to their influence. In the relationship between knowledge elements and productivity, betweenness centrality and closeness centrality show significant positive correlations, and clustering coefficient and structural hole show significant negative correlations. Therefore, knowledge networks can be used to predict the scientific performance of knowledge elements. (shrink)

This paper proposes a state-of-the-art methodology for the analysis of stakeholders and their role and performance related to SMEs in the mining industry in the Chilean region of Coquimbo. The relationships between the actors are studied and prioritized according to their support network position. An individual index for each actor based on their influence on solving problems is provided. The social network analysis was used to know the influence of the actors in the sector through (...) the centrality measures. Furthermore, a methodology to measure stakeholders’ influence based on the multicriteria method analytic network process approach is proposed. Both methods are used to identify the main stakeholders, study their relationships, and identify the most influential actors involved in executing strategies to boost the sector performance. The results show that the network remains cohesive thanks to certain actors, while the links between private actors must be strengthened; likewise, some public actors should assume a more proactive role in dealing with the problems of the sector. (shrink)

We present social network analysis as a complement to other methods in the history of economics. We first discuss why social network analysis is especially promising for the study of the history of recent economics. We then use an example of research using it to highlight some of its characteristics.

Shared leadership is not only about individual team members engaging in leadership, but also about team members adopting the complementary follower role. However, the question of what enables team members to fill in each of these roles and the corresponding influence of formal leaders have remained largely unexplored. Using a social network perspective allows us to predict both leadership and followership ties between team members based on considerations of implicit leadership and followership theories. From this social information (...) processing perspective, we identify individual team members’ political skill and the formal leaders’ empowering leadership as important qualities that facilitate the adoption of each the leader and the follower role. Results from a social network analysis in a R&D department with 305 realized leadership ties support most of our hypotheses. (shrink)

Network analysis is a fundamental approach to the study of social structure. This chapter traces its development, distinguishing characteristics, and analytic principles. It emphasizes the intellectual unity of three research traditions: the anthropological concept of the social network, the sociological conception of social structure as social network, and structural explanations of political processes. Network analysts criticize the normative, categorical, dyadic, and bounded-group emphases prevalent in many sociological analyses. They claim that the (...) most direct way to study a social system is to analyze the pattern of ties linking its members. By analyzing complex hierarchical structures of asymmetric ties, they study power, stratification, and structural change. (shrink)

Developing World Bioethics, Volume 22, Issue 3, Page 126-139, September 2022.

This study aims to describe social network and social participation and to assess associations with depressive symptoms in older persons with increased risk for dementia in Germany. We conducted a cross-sectional observational study in primary care patients (aged 60-77) as part of a multicenter cluster-randomized controlled trial (AgeWell.de). We present descriptive and multivariate analyses for social networks (Lubben Social Network Scale and subscales) and social participation (item list of social activities) and analyze (...) associations of these variables with depressive symptoms (Geriatric Depression Scale). Of 1030 included patients, 17.2% were at risk for social isolation (Lubben Social Network Scale < 12). Looking at the subscales, a reduced non-family network was found almost twice as often as a reduced family network. Patients with depressive symptoms had significantly smaller social networks than patients without depression (p < 0.001). They rather engaged in social activities of low involvement level or no weekly social activity at all (p < 0.001). The study shows associations of depressive symptoms with a decreased social network and less social participation in elderly participants. Sufficient non-family contacts and weekly social activities seem to play an important role in mental health and should be encouraged in elderly primary care patients. (shrink)

This paper examines the motivation theory of Rowley and Moldoveanu (2003) on shareholder activism in the context of shareholder resolution networks. Shareholder resolution filings occur both within subnetworks as well as across subnetworks, indicating these motivations are mixed. I extend the motivational issue by also examining the response of the corporation to such activism. That resolutions might migrate from identity to interest motivated groups is examined as an element of future research.

A large amount of data is maintained in every Social networking sites.The total data constantly gathered on these sites make it difficult for methods like use of field agents, clipping services and ad-hoc research to maintain social media data. This paper discusses the previous research on sentiment analysis.

BackgroundIn the pandemic time, many low- and middle-income countries are experiencing restricted access to COVID-19 vaccines. Access to imported vaccines or ways to produce them locally became the principal source of hope for these countries. But developing a strategy for success in obtaining and allocating vaccines was not easy task. The governments in those countries have faced the difficult decision whether to accept or reject offers of vaccine diplomacy, weighing the price and availability of COVID-19 vaccines against the concerns over (...) their efficacy and safety. We aimed to analyze public opinion regarding the governmental strategies to obtain COVID-19 vaccines in three Central Asian countries, focusing particularly on possible ethical issues.MethodsWe searched for opinions expressed either in Russian or in the respective national languages. We provided data on the debate within three countries, drawn from social media postings and other sources. The opinion data was not restricted by source and time. This allowed collecting a wide range of possible opinions that could be expressed regarding COVID-19 vaccine supply and human participation in the vaccine trial. We recognized ethical issues and possible questions concerning different ethical frameworks. We also considered scientific data and other information, in the process of reasoning.ResultsAs a result, public views on their respective government policies on COVID-19 vaccine supply ranged from strongly negative to slightly positive. We extracted the most important issues from public debates, for our analysis. The first issue involved trade-offs between quantity, speed, price, freedom, efficacy, and safety in the vaccines. The second set of issues arose in connection with the request to site a randomized trial in one of the countries (Uzbekistan). After considering additional evidence, we weighed individual and public risks against the benefits to make specific judgements concerning every issue.ConclusionsWe believe that our analysis would be a helpful example of solving ethical issues that can arise concerning COVID-19 vaccine supply around the world. The public view can be highly critical, helping to spot such issues. An ignoring this view can lead to major problems, which in turn, can become a serious obstacle for the vaccine coverage and epidemics’ control in the countries and regions. (shrink)

The outcomes of a bibliographic review on political communication, in particular electoral communication in social networks, are presented here. The electoral campaigning are a crucial test to verify the transformations of the media system and of the forms and uses of the linguistic acts by dominant actors in public sphere – candidates, parties, journalists and Gatekeepers. The aim is to reconstruct the first elements of an analytical model on the transformations of the political public sphere, with which to systematize (...) the results of the main empirical research carried out in recent years, in particular those conducted with a promising methodology: Digital Trace Data Analysis. (shrink)

Academic productivity is realized through resources obtained from professional networks in which scientists are embedded. Using a national survey of academic faculty in Science, Technology, Engineering, and Mathematics fields across multiple institution types, we examine how the structure of professional networks affects scholarly productivity and how those effects may differ by race, ethnicity, and gender. We find that network size masks important differences in composition. Using negative binomial regression, we find that both the size and composition of professional networks (...) affect scientific productivity, but bigger is not always better. We find that instrumental networks increase scholarly productivity, while advice networks reduce it. There are important interactive effects that are masked by modeling only direct effects. We find that white men are especially advantaged by instrumental networks, and women are especially advantaged by advice networks. (shrink)

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article (...) is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. (shrink)

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of (...) the distinction between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help to address it. (shrink)

This research explores the marginal stakeholder engagement and propensity to value cocreation in the fast-fashion industry by taking Generation Z consumers (GZCs) as observation unit and social networking sites (SNSs) as context of investigation. By undertaking 24 in-depth interviews with US and Italian GZCs, the study uncovers the main elements that influence their engagement generation on SNSs and highlights that at least four main paradoxes (PXs) exist in this scenario. Specifically, the interviewees reported that they do not trust those (...) brands that make them feel as marginal consumers (PX1) and that they are likely to be extremely loyal to those brands that actively take them into consideration in their activities on SNSs (PX2). In addition, although GZCs concerned about the environment, in most cases, they will buy repeatedly from fast-fashion brands for convenience reasons (PX3). Finally, social dimension of GZCs engagement appears to be influenced by their peers' preferences (PX4). This research is the first that explored GZCs by considering them under the lenses of stakeholder engagement and offering novel insights about common believes on this generation of consumers. Therefore, theoretical and managerial implications are discussed to advance current knowledge on GZCs and to help the development of new strategies to engage them on SNSs. (shrink)

The study of cultural evolution has taken on an increasingly interdisciplinary and diverse approach in explicating phenomena of cultural transmission and adoptions. Inspired by this computational movement, this study uses Bayesian networks analysis, combining both the frequentist and the Hamiltonian Markov chain Monte Carlo (MCMC) approach, to investigate the highly representative elements in the cultural evolution of a Vietnamese city’s architecture in the early 20th century. With a focus on the façade design of 68 old houses in Hanoi’s Old (...) Quarter (based on 78 data lines extracted from 248 photos), the study argues that it is plausible to look at the aesthetics, architecture, and designs of the house façade to find traces of cultural evolution in Vietnam, which went through more than six decades of French colonization and centuries of sociocultural influence from China. The in-depth technical analysis, though refuting the presumed model on the probabilistic dependency among the variables, yields several results, the most notable of which is the strong influence of Buddhism over the decorations of the house façade. Particularly, in the top 5 networks with the best Bayesian Information Criterion (BIC) scores and p<0.05, the variable for decorations (DC) always has a direct probabilistic dependency on the variable B for Buddhism. The paper then checks the robustness of these models using Hamiltonian MCMC method and find the posterior distributions of the models’ coefficients all satisfy the technical requirement. Finally, this study suggests integrating Bayesian statistics in the social sciences in general and for the study of cultural evolution and architectural transformation in particular. (shrink)

In the last few decades, increasing attention has been given to gender issues in urban design. However, research on the urban environment continues to show large gender inequalities, which are especially evident when studying the use and enjoyment of the public space. This study aims to identify predominant patterns of use in public places and to explore the possible existence of traditional gender roles in the urban space. The study uses, three public spaces in the city of Barcelona as a (...) case study, an innovative combination of systematic observation techniques and network analysis procedures. Variables collected by EXOdES, a dedicated software analysis tool for systematic observation, are represented as nodes of a network system and analyzed using network analysis tools. Findings confirmed that, in spite of the progressive consolidation of feminist urbanism, uses in the public realm resulting from traditional gender roles remained explicitly recognizable. Whereas women’s occupation of space was related to playground and resting areas, generally involving care activities concerned with children or elderly people, men were primarily located in resting and sports areas, practicing sports, or participating in leisure activities. These patterns of use were more prone to emerge when users were part of a group than when they were alone. From a gender perspective, a contribution of the study is that it informed about main aspects of the analyzed public spaces reconfirming the existence of traditional roles in society, and the significance of exploring the public space as a key scenario where social features are explicitly exposed. From a methodological perspective, the processing of observational data with network analysis tools proved to be relevant and suitable for dealing with the intricacies of urban place analysis. Compared to more classical approaches and systems, these techniques allowed to identify and interpret complex systems composed of many variables and relationships in a relatively straightforward manner, which turns it into a useful aid for urban designers and architects. (shrink)

Network analysis is increasingly appreciated as a methodology in the social sciences. In recent years, it is also receiving attention among historians of science. History of economics is no exception in that researchers have begun to use network analysis to study a variety of topics, including collaborations and interactions in scientific communities, the spread of economic theories within and across fields, or the formation of new specialties in the discipline of economics. Against this backdrop, a (...) debate is emerging about how network analysis can help address questions that are pertinent to the history of economics. With this paper, we want to push this debate one step forward by offering and discussing five reasons why network analysis should have a future in the history of economics. (shrink)

As local food activities expand and grow, an important question to answer is how various participants contribute to a local food system’s overall vitality and strength. This paper does so by focusing on the relationships between locally-oriented farm and retail actors and assessing what the configuration of these relationships tells us about the workings of the broader local food system. Such an analysis reveals two things. Empirically, it shows the important role food retailers play in the overall vibrancy of (...) local food exchanges: food retailers form crucial links holding the broader system together and significantly expanding consumer access to local foods. Further, different retailer types have distinct impacts on network configurations, each serving particular roles in the development and maintenance of local food systems. Methodologically, this paper shows the value of applying social network analysis techniques to the study of local food systems: such an approach yields insights that may not be as readily assessable from other strategies. In this paper, I overview common network analysis techniques and apply them to a case study of local food activities in New England, suggesting how such an approach might be applied to local food systems in other places. (shrink)

When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more (...) nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique—epistemic network analysis—to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1) properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2) optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3) differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users. (shrink)

The construction industry consistently ranks amongst the highest contributors to global gross domestic product, as well as, amongst the most corrupt. Corruption therefore inflicts significant risk on construction activities, and overall economic development. These facts are widely known, but the various sources and nature of corruption risks endemic to the Iranian construction industry, along with the degree to which such risks manifest, and the strength of their impact, remain undescribed. To address the gap, a mixed methods approach is used; with (...) a questionnaire, 103 responses were received, and these were followed up with semi-structured interviews. Results were processed using social network analysis. Four major corruption risks were identified: procedural violations in awarding contracts, misuse of contractual arrangements, neglect of project management principles, and, irrational decision making. While corruption risks in Iran align with those found in other countries, with funds being misappropriated for financial gain, Iran also shows a strong inclination to champion projects that serve the government’s political agenda. Root cause identification of corruption risks, namely, the noticeable impact of authoritarianism on project selection in Iran, over criterion of economic benefit or social good, is a significant outcome of this study. (shrink)

The business world is facing a very complicated situation due to the COVID-19 pandemic. Small- and medium-sized companies —both in Spain and at the global level—are seeing their survival jeopardized by a fall in revenues. This scenario is aggravated in the case of micro-SMEs headed by female entrepreneurs. Accordingly, micro-SMEs, particularly those led by female entrepreneurs, need to reinvent themselves to overcome the current adversities that could lead to the destruction of their businesses and hence their jobs. One of the (...) ways to do this is to take advantage of digital transformation. Therefore, the aim of this paper is to analyze which variables influence the financial results of female-led Spanish micro-SMEs when they carry out social marketing actions. For that purpose, an online survey was designed and analyzed using the “PROCESS” macro. Results show that social media marketing actions have significant effects on financial performance. (shrink)

This study examines the Italian Twitter landscape during the 2015 Syrian and 2022 Ukrainian refugee crises, with a focus on the evolution of anti-refugee discourse. Through the analysis of 400,000 tweets, we sought to identify attitudinal communities, track changes in user positions, and evaluate the trending potential of the communities. Our findings indicate a shift in opinion leaders within the anti-refugee community from 2015, alongside a persistent ability to influence public discourse. Additionally, while the pro-Ukrainian refugee community has grown, (...) incorporating previously neutral users, it remains loosely connected. Finally, the shifts in attitudes of Italian populist leaders regarding Syrian and Ukrainian refugees are interpreted in light of the changes in user attitudes as observed in the communication networks. This research highlights the importance of computational communication methods for investigating fringe groups absent from mainstream discourse, and underscores the necessity of content moderation and proactive digital activism to counter anti-refugee sentiment online. (shrink)

Network analysis is increasingly appreciated as a methodology in the social sciences. In recent years, it is also receiving attention among historians of science. History of economics is no exception in that researchers have begun to use network analysis to study a variety of topics, including collaborations and interactions in scientific communities, the spread of economic theories within and across fields, or the formation of new specialties in the discipline of economics. Against this backdrop, a (...) debate is emerging about how network analysis can help address questions that are pertinent to the history of economics. With this paper, we want to push this debate one step forward by offering and discussing five reasons why network analysis should have a future in the history of economics. (shrink)

In response to the lack of research on the online social network structure of athletes, elements of research on the online social network structure of athletes were constructed based on the whole network perspective and through the study of the characteristics of the whole online social network structure of athletes, in order to provide reference for the physical and mental health development of athletes from a new perspective. Data were collected through questionnaires, and (...) several software programs were used to preprocess and analyse the collected data. Through the analysis of the online whole network structure, it was found that the network density of the online support network was generally greater than that of the online discussion network, and athletes still showed stronger practical support demands and behaved more rationally in the process of training and learning life, while from the perspective of the relationship structure, the athletes’ family and classmates’ online support is weaker than that in previous studies; in terms of the whole network, strong relationships still dominate in this population, while attention should be paid to the impact of weak relationships. (shrink)

Life goals or aspirations can be distinguished as intrinsic or extrinsic, with different implications for well-being. In this study we used network analysis to reexamine this intrinsic-extrinsic distinction, illustrating how novel candidate aspirations can be mapped along this dimension using innovative methods. We identify four previously unexamined life aspirations, predicting that aspiring for power and social adherence would group with extrinsic goals, whereas aspiring for self-expression and mastery would group with intrinsic goals. In two samples (n = (...) 196; n = 346) we analyze both the original life-goal variables and these novel aspirations using factor analysis, multidimensional scaling, circumplex modeling, and a network analysis using a graphical least absolute shrinkage and selection operator (glasso) to estimate the network structure of aspirations using EBIC. Replicating past intrinsic-extrinsic distinctions, all four methods further classified power and social adherence as extrinsic goals, and self-expression and mastery as intrinsic goals. The intrinsic-extrinsic distinction was also clearly visible in the network analysis. Finally, consistent with hypotheses, power and social adherence were unrelated to wellness indicators, whereas self-expression and mastery correlated positively with well-being indicators and negatively with ill-being indicators, supporting their hypothesized nature as extrinsic and intrinsic, respectively. (shrink)

It is increasingly common in natural and social sciences to rely on network visualizations to explore relational datasets and illustrate findings. Such practices have been around long enough to prove that scholars find it useful to project networks in a two-dimensional space and to use their visual qualities as proxies for their topological features. Yet these practices remain based on intuition, and the foundations and limits of this type of exploration are still implicit. To fill this lack of (...) formalization, this paper offers explicit documentation for the kind of visual network analysis encouraged by force-directed layouts. Using the example of a network of Jazz performers, band and record labels extracted from Wikipedia, the paper provides guidelines on how to make networks readable and how to interpret their visual features. It discusses how the inherent ambiguity of network visualizations can be exploited for exploratory data analysis. Acknowledging that vagueness is a feature of many relational datasets in the humanities and social sciences, the paper contends that visual ambiguity, if properly interpreted, can be an asset for the analysis. Finally, we propose two attempts to distinguish the ambiguity inherited from the represented phenomenon from the distortions coming from fitting a multidimensional object in a two-dimensional space. We discuss why these attempts are only partially successful, and we propose further steps towards a metric of spatialization quality. (shrink)