Code choice and code-switching in Swiss-German Internet Relay Chat rooms

In the German-speaking regions of Switzerland, dialect is spoken by all social groups in most communicative situations, Standard German being used only when prescribed. Swiss dialects rarely appeared in written form before the 1980s, apart from the genre of dialect literature. Due to the growing acceptance of informal writing styles in many European languages, dialect is increasingly employed for written personal communication, in particular in computer-mediated communication (CMC). In Swiss Internet Relay Chat (IRC) rooms, varieties of German are used side by side as all chatters have a command of both standard and dialectal varieties. Depending on the channel, the proportion of dialectal contributions can be as high as 90 percent. The choice of a particular variety depends on both individual preference and on the predominant variety used within a specific thread. In this paper I take a quantitative approach to language variation in IRC and demonstrate how such an approach can help embed qualitative research on code-switching in CMC.     

Gender identity and lexical variation in social media

We present a study of the relationship between gender, linguistic style, and social networks, using a novel corpus of 14,000 Twitter users. Prior quantitative work on gender often treats this social variable as a female/male binary; we argue for a more nuanced approach. By clustering Twitter users, we find a natural decomposition of the dataset into various styles and topical interests. Many clusters have strong gender orientations, but their use of linguistic resources sometimes directly conflicts with the population‐level language statistics. We view these clusters as a more accurate reflection of the multifaceted nature of gendered language styles. Previous corpus‐based work has also had little to say about individuals whose linguistic styles defy population‐level gender patterns. To identify such individuals, we train a statistical classifier, and measure the classifier confidence for each individual in the dataset. Examining individuals whose language does not match the classifier's model for their gender, we find that they have social networks that include significantly fewer same‐gender social connections and that, in general, social network homophily is correlated with the use of same‐gender language markers. Pairing computational methods and social theory thus offers a new perspective on how gender emerges as individuals position themselves relative to audiences, topics, and mainstream gender norms.     

Mapping the two levels of digital divide: Internet access and social network site adoption among older adults in the USA

Older adults have increasingly adopted Internet and social network sites (SNSs), but little communication scholarship has explored systematic differences in access within this population. Using a nationally representative sample of Americans over the age of 50 years from the 2012 Health and Retirement Study, we examine Internet access (N?=?18,851) and SNS adoption patterns (N?=?869) among this sample and explore how these patterns vary by age. Regarding Internet access, results suggest that while the gender divide has reversed in favor of women, older adults who are economically, socioculturally, or physically disadvantaged are less likely to have reliable Internet access. In addition, the view that the various divides in Internet access are less of a concern for those who are younger is only partially supported, as some access-related divides do not vary by age or even decrease with age. For SNS adoption, we found that access to technological resources (diversity of online activities) positively predicts SNS use. Moreover, SNS users are more likely to be younger, female, widowed, and homemakers, perhaps because these individuals are more motivated to use SNSs to complement or compensate for their existing social status. These findings reveal unique challenges and motivations in relation to Internet access and SNS adoption patterns across the later life span.     

Assessing organizational capacity for diffusion: A school-based social network analysis case study

The purposeful design of social networks is increasingly recognized as a fundamental organizational improvement strategy. In the PK-12 education sector, school-based teacher collaboration is the primary vehicle through which educators are able to gain access to essential social capital, and through which leaders promulgate diffusion of innovation and continuous organizational learning. In partnership with school administrators, the authors undertook an evaluation to examine the size, structure, and composition of school-based networks. Social network analysis (SNA) was used to measure and visualize connections (or lack thereof) of ties between teams and between educators. Isolate and disconnected network actors were revealed through visual inspection of the sociograms. Administrators used findings to reconfigure team membership to enhance teacher ability to give and receive support and collaboratively problem-solve, and to ensure greater capacity for diffusion of instructional innovation and organizational learning. This paper contributes to the field’s understanding of how evaluators and organizational leaders can use SNA to measure, visualize, and more purposefully design effective patterns of connection between people through which professional knowledge, support, and innovation will travel.     

How social ties contribute to collective actions on social media: A social capital approach

In public relations research into civic engagement, the influence of social ties on the individual level has not been adequately studied from a social capital perspective. To fill this gap, this study conducts a one-factor between subjects experiment to examine the difference, if any, between the social influence of strong ties and of weak ties on individuals’ participation intentions in regard to collective actions. This study postulates collective efficacy as a factor possibly associated with the intention to participate in collective actions. The study findings suggest that advocacy about certain social causes, such as veterans affairs, have globally positive effects on publics’ civic engagement intentions, regardless of the norms of the social network with which the individuals are connected. Furthermore, collective efficacy was found to be positively associated with participation in collective actions. The theoretical and practical implications of these findings are discussed.     

A comparative study of social network models: Network evolution models and nodal attribute models

This paper reviews, classifies and compares recent models for social networks that have mainly been published within the physics-oriented complex networks literature. The models fall into two categories: those in which the addition of new links is dependent on the (typically local) network structure (network evolution models, NEMs), and those in which links are generated based only on nodal attributes (nodal attribute models, NAMs). An exponential random graph model (ERGM) with structural dependencies is included for comparison. We fit models from each of these categories to two empirical acquaintance networks with respect to basic network properties. We compare higher order structures in the resulting networks with those in the data, with the aim of determining which models produce the most realistic network structure with respect to degree distributions, assortativity, clustering spectra, geodesic path distributions, and community structure (subgroups with dense internal connections). We find that the nodal attribute models successfully produce assortative networks and very clear community structure. However, they generate unrealistic clustering spectra and peaked degree distributions that do not match empirical data on large social networks. On the other hand, many of the network evolution models produce degree distributions and clustering spectra that agree more closely with data. They also generate assortative networks and community structure, although often not to the same extent as in the data. The ERGM model, which turned out to be near-degenerate in the parameter region best fitting our data, produces the weakest community structure.     

Network centrality and social movement media coverage: A two-mode network analytic approach

This article examines the relationship between structural location (namely, degree centrality) and news media coverage. Our central hypothesis is that the network centrality of social movement actors is positively associated with the prevalence of actors being cited in the print news media. This paper uses two-mode data from a communication network of environmentalists in British Columbia, and examines the relationship between their structural location and the frequency by which they are cited in newsprint media with regard to particular frames (about forest conservation, environmental protest, and related issues). We asked a sample of social movement participants about their ties to a target list of relatively high profile actors (environmental activists). We turned the resulting network matrix into a bipartite graph that examined the relationships amongst the target actors vis a vis the respondents. Next we calculated point in-degree for the target actors. For the target actors we also have data from a representative sample of 957 print news articles about forestry and conservation of old growth forests in British Columbia. We compare the effects of network centrality of the target actor versus several attributes of the target actors (gender, level of radicalism, leadership status) on the amount of media coverage that each of the target actors receives. We find that network centrality is associated with media coverage controlling for actor attributes. We discuss theoretical implications of this research. Finally, we also discuss the methodological pros and cons of using a “target name roster” to construct two-mode data on social movement activists.     

Explorations on mediated communication and beyond: Toward a theory of social media

Although robust theories of radio, television, cinema, journalism, and other areas of mass media already exist, the social media sphere has received relatively little original theorizing. Modeled after Berger and Calabrese’s (1975) seminal “axioms of human communication” article, this essay takes stock of the existing research on social media, and uses the same approach to theorizing about social media, advancing 7 axioms and 21 theorems, and exploring how the propositions chronicled can be used to build social media theory and improve public relations practice.     

Social media dialogues in a crisis: A mixed-methods approach to identifying publics on social media

Despite the promise of social media to engender dialogue, the common approach to studying social media may prioritize monologue, whereby research considers the strategies organizations use in targeting publics, particularly in a crisis. This study uses a mixed-method approach to analyze dialogue in a crisis—semantic network analysis and content analysis. Specifically, this study examines the emotional expression and crisis coping behaviors on social media during two separate terror attacks: the Paris terror attacks in 2015 and the Barcelona terror attacks in 2017. Results demonstrate how publics may be identified and understood through semantic network analysis and content analysis. This study also shows the connection between emotions and coping, expanding the crisis communication literature in public relations, and suggests the need to consider agenda-setting and resilience in crisis communication research. Finally, we discuss this study’s implications for assuming a dialogic orientation in public relations.     

Bring publics back into networked public relations research: A dual-projection approach for network ecology

This essay critiques the absence of publics in networked public relations research, and proposes the dual-projection approach as a solution to simplify and analyze the multi-mode public relations network ecology (Yang & Taylor, 2015). Compared to most previous studies that employ organization-centric networks where ties stand for hyperlinks, collaborations, or coalitions, the new approach projects organization-public relationships and public-public relationships onto interorganizational ties. By doing so, it (1) brings publics back into networked public relations research; (2) presents organizations and publics—the two most important subjects of public relations research—equally in the same network, (3) drives literature further away from a dyadic view of relationship management, and (4) constitutes one of the first techniques that can analyze direct and timely consequences of organziation-public relationships in the network ecology. To demonstrate the new approach, the network of publics overlap is introduced and applied to US-based LGBTQ advocacy groups. The essay also discusses the theoretical inquiries needed to further dual-projection networks, and invites scholars to create novel ways to incorporate publics into their network studies using dual projection.     

Predictors and outcomes of social network compositions: A compositional structural equation modeling approach

Proportions of a total, including social network compositions (proportions of partner, family, friends, etc.) lie in a restricted space, which challenges statistical analysis. Network compositions can be both dependent and explanatory variables and are usually measured with error by survey instruments. Structural equation models make it possible to correct measurement error bias. Coenders et al. (2011) fitted a factor analysis model to transformed network compositions. In this article, we use another transformation called an isometric log-ratio and we extend the model to include predictors and outcomes. The findings and hypotheses in the literature can be reformulated with isometric log-ratios in a more interpretable manner. For instance, we find relationships of gender with partner support, of education and extraversion with friend support, and of family support with tie multiplexity and closeness.     

Leadership and contagion by COVID-19 among residence hall students: A social network analysis approach

University students have changed their behaviour due to the COVID-19 pandemic. In this paper, we describe the characteristics of PCR+ and PCR- nodes, analyse the structure, and relate the structure of student leaders to pandemic contagion as determined by PCR+ in 93 residential university students. Leadership comes from the male students of social science degrees who have PCR +, with an eigenvector centrality structure, β-centrality, and who are part of the bow-tie structure. There was a significant difference in β-centrality between leaders and non-leaders and in β-centrality between PCR+ and non-leaders. Leading nodes were part of the bow-tie structure. MR-QAP results show how residence and scientific branch were the most important factors in network formation. Therefore, university leaders should consider influential leaders, as they are vectors for disseminating both positive and negative outcomes.     

Stakeholder influence,government power,and new opportunities for Chinese Internet companies: A multilevel network analysis of cross-sector networks

In recent decades, Chinese Internet companies have experienced exponential growth. As the Internet industry increasingly commends tremendous financial resources, they also face growing stakeholder expectations for corporate social responsibility (CSR) actions. One way through which Chinese Internet companies conduct CSR is by building cross-sectoral collaborations with nonprofit and nongovernmental organizations (NGOs) and governmental agencies. Aiming to understand Internet companies’ strategic relationship building on CSR issues, the researchers drew from stakeholder influence theory and research on a network approach to stakeholder influence, and applied multilevel network analysis to model three networks related to Chinese Internet companies’ CSR collaborations. Specifically, we found that power and urgency are significant predictors of the structure of Internet companies’ cross-sector CSR alliance network. Organizations affiliated or endorsed by the central Chinese government are the most desirable CSR stakeholders. Additionally, the study also revealed that for Internet companies, devoting their attention to Internet-related social issues could increase their desirability as strategic stakeholders from other sectors and among Internet companies.     

A sexual affiliation network of swingers,heterosexuals practicing risk behaviours that potentiate the spread of sexually transmitted infections: A two-mode approach

Using the example of the sexual affiliation networks of swingers, this paper examines how the analysis of sexual affiliation networks can contribute to the development of sexually transmitted infection (STI) prevention strategies. Two-mode network methodology and ERGMs are applied to describe the structural composition of the affiliation network and analyse attribute effects. Swingers were found to recruit their sex partners through one large, moderately cohesive network component. Swingers who used drugs or had a longer history of swinging tended to frequent websites instead of clubs. This study confirms the relevance of studying sexual affiliation networks and its additional value for STI epidemiology.     

Patterns of evolutions of social enterprises in France: a focus on work integration social enterprises

The objective of this paper is to characterize the patterns of emergence and evolution of social enterprise in France with a focus on work integration social enterprises (WISEs). After a review of the history of social and solidarity economy practices, identifying the processes that brought these practices to develop, we discuss the boundaries of the notion of social enterprise in the French case. We then briefly present the historical evolution of work integration. On that basis, two models of social enterprise applied to the case of work integration are extracted, crystallizing crucial tendencies. The limits and prospects of social enterprise in the field of work integration in France are discussed in the conclusion.     

Polarized public opinion responding to corporate social advocacy: Social network analysis of boycotters and advocators

Despite growing attention to corporate social-political advocacy, little is known about how publics mobilize and establish relationships in social media when firms are involved in hot-button issues. Using the social network approach, this study examines a network structure which emerged around boycotting and advocating for Starbucks and Budweiser when these two brands responded to President Donald Trump’s immigration ban executive order in 2017. The study identified three unique characteristics in the boycotters’ networks. The boycotters appeared not only in the aggregated brand boycotting networks, but also in the advocators’ networks. In addition, boycotters in Budweiser and Starbucks networks were engaged in boycotting other brands or organizations which were opposed to Republicans or President Trump’s policy. Finally, the network of boycotters was very dense and highly connected among subgroups while that of advocators was sparse. Theoretical and practical implications are discussed.     

Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement

During the #MeToo movement, social movement organizations (SMOs) played a crucial role in the online mobilization by utilizing various message frames and appealing hashtags during the social movement. Applying a co-creational approach and using framing as a theoretical framework, the study explored how SMOs use words and hashtags to participate in the #MeToo movement through Twitter. Based on both semantic network analysis and thematic analysis methods, findings of the study enhance literature of social movement organizations and activism as well as provide practical implications for effective social movement campaigns.     

The health and social impact of Blood Donors Associations: A Social Return on Investment (SROI) analysis

Although research on blood donation abounds, no studies have yet attempted to estimate the socio-economic value generated from Blood Donors Associations (BDAs).To fill this gap, the authors ran a Social Return on Investment (SROI) analysis on four units of the largest BDA in Italy, the Association of Voluntary Italian Blood Donors (“Avis”).This study used multiple methods for data collection and analysis. A systematic literature review helped the identification of proper financial proxies to highlight the economic value of the social and health impacts experienced by Avis members. A focus group with key informants gathered their views on the areas of impact selected for the analysis: early detection of diseases, adoption of healthier lifestyles, social capital, human capital, personal satisfaction and reinforcement of a ‘giving culture’.Primary data collection involved (a) an Activity Based Costing analysis (b) a self-reported questionnaire to 1.066 BDA members and unassociated donors enabling the comparison of the blood donation experience of these two groups. The SROI analysis resulted in four positive ratios, varying between €1.70 and €13.80.This study contributes to the knowledge on impact evaluations in TSOs. Policy implications refer to BDAs deserving financial and material support for their capacity to generate positive social impacts.     

Crisis collective memory making on social media: A case study of three Chinese crises on Weibo

Social media users collectively (re)construct narratives to create memories surrounding past crises. In this study, we connect the concept of collective memory with a public-oriented approach to crisis communication to examine how crisis response frames and collective memory narratives were displayed by different social actors (government, organizations, and publics) on one of China’s social media platforms, Weibo. Findings from a content analysis of 9238 unique posts on three national crises (the 2010 Yushu Earthquake, the 2015 Tianjin Explosions, and the 2018 Vaccine Scandal) reveal that Chinese publics tended to adopt social issue and blaming frames, while the government and organizations were more prone to using informing and corrective action frames. When recalling and reconstructing crisis memories, Chinese publics used more power and contestation narrative, while the government frequently adopted the nationalism narrative; with trauma being the predominant narrative displayed across the three crises and social actors. Crisis response frames of blaming, crediting, and corrective action were significantly associated with narratives of power and contestation, heroism, and nationalism, respectively. Theoretical implications for future research on crisis collective memory making on social media and suggestions for governmental crisis communication are discussed.