Collaborative Social Networks Research Articles

Collaborative famine relief: Chinese and British responses to the North China Famine from Melbourne, Victoria

The North China Famine of 1876–79 killed over 10 million people and generated a rise in non-governmental relief both nationally and overseas. This article examines the establishment of the China Famine Fund in Melbourne, Australia, which contributed to famine relief efforts in Shanghai. It demonstrates how the fund’s establishment followed lobbying by Chinese merchants in Melbourne and was made possible by pre-existing Chinese-European collaborative social and commercial networks. In highlighting the fund’s establishment, this article draws attention to the cultural influences of Chinese merchant philanthropy, the global mobilities of famine reportage, and philanthropy as a site for elite cultural encounter.

Untangling Humpback Whale-Watching Management Networks: Collaboration and Conflict in the Northeast Pacific

Humpback whales face emerging anthropogenic challenges such as entanglement in abandoned fishing gear and stranding during their winter migration. Such challenges require collective action solutions involving diverse stakeholders across jurisdictions, social sectors, and geographies. Collaborative governance systems involve conflictual and collaborative interactions. We used a quantitative approach (social network analysis) to map the structure of three social networks: Collaboration in disentanglement, collaboration in stranding, and conflict. We administered a face-to-face survey to 38 stakeholders from four social sectors across seven coastal localities from April to November 2021. We also obtained perspectives from the same stakeholders about pressing conflicts, rule compliance, and law enforcement regarding whale-watching management in the region using a semi-structured questionnaire. We found hints of different dimensions of collaboration occurring simultaneously: Coordination, cooperation, and conflict. Networks played distinct roles in promoting collaboration across sectors, and while the disentanglement network coordinated civil society and the public sector, the stranding network facilitated cooperation within the public sector. The most pressing social conflicts detected by stakeholders were pleasure boats, abandoned fishing gear, and poor rule compliance regarding the distance between boats and whales. Our results suggest that in the context of institutional weakness, collaborative social networks play a crucial role in the management and conservation of coastal and marine common-pool resources.

On Prevention of Attribute Disclosure and Identity Disclosure Against Insider Attack in Collaborative Social Network Data Publishing

On Prevention of Attribute Disclosure and Identity Disclosure Against Insider Attack in Collaborative Social Network Data Publishing

On prevention of attribute disclosure and identity disclosure against insider attack in collaborative social network data publishing

On prevention of attribute disclosure and identity disclosure against insider attack in collaborative social network data publishing

The Way toward Sustainability: Policy Attention Evolution of Chinese Local Governments to Promote Entrepreneurship of Returnees Based on Grounded Theory and Social Network Analysis

As an important livelihood strategy choice to promote the sustainable development of themselves and regions, returnees’ entrepreneurship has played a vital role in the governance of all-level Chinese local governments since the 21st century. The policy attention reflects the importance that the local governments attach to this issue, and the evolution process also reflects relevant policies’ internal rules and characteristics. Based on this, this paper, taking 242 policy texts related to returnees’ entrepreneurship issued by local governments from 2000 to 2021 as the research objects, uses grounded theory and social network analysis in order to explore the policy attention evolution from the aspects of time, space, specific policy domains and cooperative relationship among policy subjects. Finally, this research finds the main conclusions as follows: (1) The policy attention evolution on time dimension has the characteristic of synchronism, different levels and “reciprocal U”. (2) The policy attention evolution on space dimension is closely linked to “pull” and “push” forces of local population flow and has neighborhood effects. (3) The policy attention evolution on specific policy areas will gradually spread and diversify with the change in local governance environment and stage goals. (4) The evolution trend of collaborative social network among policy objects has the characteristic of “loose-central-loose”.

“Social media technologies: a waste of time or a good way to learn and improve technological competences?”

Purpose The purpose of this study is to deepen understanding of the effects of using social media technologies to acquire technological knowledge and organizational learning competences, of technological knowledge competences on organizational learning and finally of organizational learning on organizational performance. Design/methodology/approach The study was performed by analyzing data from a sample of 197 technology firms located in Spain. The hypotheses were tested using a structural equations model with the program LISREL 8.80. Findings This study’s conceptual framework is grounded in complexity theory – along with dynamic capabilities theory, which complements the resource-based view. The study contributes to the literature by proposing a model that reflects empirically how business ecosystems that use social media technologies enable the development of interorganizational and social collaboration networks that encourage learning and development of technological knowledge competences. Research limitations/implications It would be interesting for future studies to consider other elements to conceptualize and measure social media technologies, including (among others) significance of the various tools used and strategic integration. The model might also analyze other sectors and another combination of variables. Practical implications The results of this study have several managerial implications: developing social media technologies and interorganizational social collaboration networks not only enables the organizational learning process but also encourages technological knowledge competences. Through innovation processes, use of social media technologies also contributes to strengthening companies’ strategic positioning, which ultimately helps to improve firms’ organizational performance. Social implications Since social media technologies drive information systems in contemporary society (because they enable interaction with numerous agents), the authors highlight the use of complexity theory to develop a conceptual framework. Originality/value The study also deepens understanding of the connections by which new experiential learning contributes to the generation of coevolutionary adaptive business ecosystems and digital strategies that enable development of interorganizational and social collaborative networks through technological knowledge competences. Only after examining the impact of social media technologies on organizational performance in prior literature, did the authors underscore that both quantity and frequency of social media technology use are positively related to improvement in knowledge processes that lead to employees’ creation and acquisition of new metaknowledge.

A Study on Conformity Appeal Attributes and Social Contagion of Beauty-Focused One-Person Media in Sustainable E-Commerce

In the beauty industry, the use of one-person media is making new, more active relationships that differ from those of past online services and information sharing. Therefore, in this study, we developed conformity appeal attributes in one-person media, identifying their effects on information diffusion behavior through social conformity and collaborative innovation networks, to investigate the social contagion effect of information in beauty-focused one-person media and develop a model by connecting them to the conformity threshold of individuals influenced by others. In this study, a total of 694 complete samples of experienced consumers in the beauty-focused one-person media category were selected, and research questions were verified through reliability and validity tests, path analysis, and measurement model analysis. The research results are as follows. First, conformity appeal attributes of beauty-focused one-person media in terms of information cascade, utility value efficiency, reference group influence, and subnetwork structure significantly affected social imitation conformity. However, only subnetwork structure significantly affected social connection conformity. Similarly, only reference group influence and subnetwork structure significantly affected social comparative conformity. Second, social imitation conformity, social connection conformity, and social comparative conformity in beauty-focused one-person media significantly affected cocreation. Third, cocreation in beauty-focused one-person media significantly affected information diffusion behavior. The detailed use of the conformity appeal attribute factors shown in the above results will be combined with functional changes for online and mobile services of beauty companies, and it will be a driving force to create new value for the network. Moreover, the results of this study not only enable social connection among members within the reference group of beauty-focused one-person media but are also applied as an effective phenomenon to explain the continuous maintenance, reinforcement, and expansion of these relationships, thereby enabling researchers to achieve theoretical expansion and evaluation of relevant variables.

Privacy-preserving collaborative social network data publishing against colluding data providers

Privacy-preserving collaborative social network data publishing against colluding data providers

Privacy-preserving Collaborative Social Network Data Publishing Against Colluding Data Providers

Privacy-preserving Collaborative Social Network Data Publishing Against Colluding Data Providers

Personalized travel recommendation: a hybrid method with collaborative filtering and social network analysis

ABSTRACT This study proposes a hybrid method for producing personalized travel recommendation that better meet travellers’individual needs and also improve their online booking experience. The proposed method integrates multi-attribute collaborative filtering with social network analysis within the framework of large-scale group decision-making. It includes four modules, i.e. identification of online opinion experts, construction of a social network, detection of user communities, and interactively produced of personalized travel recommendation. Specifically, the preliminary user filtering and k-means clustering approach are utilized to identify the online opinion experts for a specific travel recommendation issue. Then, social network construction and its community detection process are adopted to alleviate the sparsity problem. Finally, the travel alternatives are ranked to select recommendations, and this is done interactively with travellers to handle the cold start problem. With the proposed method, a better online booking experience can be achieved for travellers, as they are presented with a more appropriate set of recommended options and so can make better travel decisions.

ProficiencyRank: Automatically ranking expertise in online collaborative social networks

Users of online collaborative social networks (e.g., StackExchange, Yahoo! Answers, and Yask, among others) are distributed across a continuous range of expertise, ranging from beginners to experts. However, only a minority of users contribute to their communities by posting questions and answers, while the majority (lurkers) only contribute by voting up or down on others’ posts. Since current methods for ranking expertise are based mainly on user submitted posts, their results are limited to that minority. We introduce ProficiencyRank, a wrapping method on top of PageRank that leverages voting information to determine user expertise for both contributors and lurkers. We validated our method to measure the proficiency of English Language Learners in the Yask social network. The new data set is naturally annotated with self-assessments of proficiency given by the users themselves, providing ground truth for all users. Experimental validation showed that ProficiencyRank produces a meaningful ranking of users that overcame various baselines based on intrinsic and extrinsic information. We conclude that this technology can benefit these communities by expanding the coverage of user expertise/reputation measurement and providing a re-ranking method for the expert finding task.

Loose and Limited Concepts: Using Coauthor Network Analysis to Identify Potential Gaps in the Understanding of Barrier Islands

Houser, C.; Smith, A.; George, E.; Lehner, J., and Lunardi, B., 2021. Loose and limited concepts: Using coauthor network analysis to identify potential gaps in the understanding of barrier islands. Journal of Coastal Research, 37(4), 873–881. Coconut Creek (Florida), ISSN 0749-0208.Understanding of coastal geomorphology expands through collaborative social networks that are expressed through coauthorship. This technical communication examines the structure of coauthorship networks and research on barrier islands with a focus on nearshore bars, rip currents, swash, beach-dune interaction, foredunes, and the backbarrier. Coauthorship in coastal geomorphology is largely based on regional organizational networks and academic lineages, which may limit the cross-fertilization of ideas and techniques that would allow for an improved understanding of barrier island response to storms and sea-level rise. It is also argued that the lack of collaboration has an influence on field sampling strategies and the development of process-based models and machine learning algorithms to predict coastal barrier evolution that ultimately inform coastal management practices.

Participatory network mapping of an emergent social network for a regional transition to a low-carbon and just society on the Dingle Peninsula

ABSTRACT The paper develops a methodological approach that acts as a tool for active change agents working in community and just transition contexts to increase their capacity to engage a wider public in planning. An innovative contribution is made to the literature through the development of a participatory action research (PAR) based approach to social network analysis using a participatory mapping method with relation to sustainable transitions. The method comprises a participatory network mapping approach, adapted from the Net-Map toolkit, which is applied to a multi-stakeholder approach to realising a regional sustainability transition in the Republic of Ireland. Dingle Peninsula 2030 is an initiative aiming to transition a geographic region in the South West of Ireland to a low-carbon society by 2030 across the sectors of energy, agriculture, transport, education, employment, marine and tourism. Due to the scope of the overall project, a diverse range of stakeholders are involved. The method developed is used to undertake a qualitative collaborative social network analysis. The paper focuses on method, by analysing and reflecting upon the use of this participatory approach, in the initial stages of the overall project, in addressing complex sustainability and just transition challenges as they are revealed through a multi-stakeholder approach. Within this, the themes of participatory justice, social learning and visualising complexity are explored; and benefits and future improvements are outlined through reflections from both the researcher and the participant community.

Breaking down the silos: Building resilience through cohesive and collaborative social networks

Building resilience at the local government level will require governance which is able to respond to the growing threats of climate-related risks, while transforming the vulnerabilities of the most marginal populations. This paper considers the influence that social networks have on knowledge exchange and adaptive governance for improving the ability of local governments to build resilience to floods. Using two local government case studies in South Africa, this paper found that the structure of social networks had an effect on the ability of local governments to transform flood vulnerabilities in informal settlements. In the Nelson Mandela Bay metropolitan municipality, poor connections among actors resulted in the formation of institutional silos, limited knowledge-exchange processes and inhibited flood risk governance. In the Mossel Bay local municipality, strong social ties facilitated cohesion amongst actors, supported knowledge sharing and benefited flood risk governance. This paper demonstrates how effective social network structures in local governments can stimulate adaptive risk governance, and contribute to the development of coping, adaptive and transformative capacities.

Global Collaborative Social Network (Share4Rare) to Promote Citizen Science in Rare Disease Research: Platform Development Study.

BackgroundRare disease communities are spread around the globe and segmented by their condition. Little research has been performed on the majority of rare diseases. Most patients who are affected by a rare disease have no research on their condition because of a lack of knowledge due to absence of common groups in the research community.ObjectiveWe aimed to develop a safe and secure community of rare disease patients, without geographic or language barriers, to promote research.MethodsCocreation design methodology was applied to build Share4Rare, with consultation and input through workshops from a variety of stakeholders (patients, caregivers, clinicians, and researchers).ResultsThe workshops allowed us to develop a layered version of the platform based on educating patients and caregivers with publicly accessible information, a secure community for the patients and caregivers, and a research section with the purpose of collecting patient information for analysis, which was the core and final value of the platform.ConclusionsRare disease research requires global collaboration in which patients and caregivers have key roles. Collective intelligence methods implemented in digital platforms reduce geographic and language boundaries and involve patients in a unique and universal project. Their contributions are essential to increase the amount of scientific knowledge that experts have on rare diseases. Share4Rare has been designed as a global platform to facilitate the donation of clinical information to foster research that matters to patients with rare conditions. The codesign methods with patients have been essential to create a patient-centric design.

Is Strategic and Sustainable Leadership Synonymous With Effective Leadership?

The purpose of this study is, after a thorough analysis of the relevant literature, to investigate whether strategic/sustainable leadership and effective leadership – key concepts for the educational sector – are synonymous or whether they complement each other, and indeed whether there is an interdependence between these concepts of leadership. The effectiveness of the school (and any organization) depends on the efficient use of available resources and on the implementation of strategic/sustainable leadership. Τhe coexistence of all members in the school’s leadership and the creation of collaborative social networks are the basic elements for establishing school sustainability.

A generalized model for social collaboration networks

In this paper, we constructed a three-parameter general social collaboration network model (GCNM) using both similarity-based strategy and copying-based strategy. In this model, a connection can be introduced between two nodes if they are similar in attributes or similar in structure (i.e., have many common friends). This model can match various types of real-world social networks by just choosing different values for three parameters, and therefore, can reproduce observed real network characteristics. Particularly, three widely studied models (similarity-based, copying-based, and pure preferential attachment (PA)) are only the special cases of this new model. Specifically, this new model possesses following new characteristics which existing models have difficulty to fulfill in all: 1) it not only exhibits the high average clustering coefficient, but also the high global clustering coefficient and explicit community structure (great number of triangles); 2) it not only makes the connections between the new node and existing nodes, but also between existing nodes; and 3) it has not only linear, but also non-linear relationship between the linking probability and the degree (the connectivity of nodes). Numerical results, which are in good agreement with real-world datasets from different fields, demonstrated all of these.

Increasing students’ social engagement during COVID-19 with Net.Create: collaborative social network analysis to map historical pandemics during a pandemic

PurposeThe authors explored shifts in social interactions, content engagement and history learning as students who were studying one pandemic simultaneously experienced another. This paper aims to understand how the Net.Create network visualization tool would support students as they tried to understand the many complex interactions in a historical text in a remote learning environment and how sustained knowledge building using Net.Create would shape student attitudes toward remote learning, collaboration and engagement.Design/methodology/approachThis paper explores changes in engagement and learning in a survey-level history course on the black death after a shift to remote learning during the COVID-19 pandemic. The authors used activity theory to focus the adaptation of Net.Create, a web-based collaborative social-network-analysis tool and to understand how it supported group-based remote learning. The authors describe how the redesigned activities sustained engagement with historical content and report coded student network entries, reading responses and surveys to illustrate changes in engagement and learning.FindingsThe results suggest that students benefit from personal connections to historical content and their peers. Net.Create supported both through collaborative knowledge-building activities and reflection on how their quarantine experiences compared to the historical content they read. It is possible to avoid student frustrations with traditional “group work” even in a remote environment by supporting collaborative learning using Net.Create and a mix of individual and group contributions.Originality/valueThis is the first use of a collaborative network visualization tool to support large classroom interaction and engagement with history content at the undergraduate level.

Software Agent-Centric Semantic Social Network for Cyber-Physical Interaction and Collaboration

Considerable research has recently focused on integrating cyber-physical systems in a social context. However, several challenges remain concerning appropriate methodologies, frameworks and techniques for supporting socio-cyber-physical collaboration. Existing systems do not recognize how cyber-physical resources can be socially connected so that they interact in collaborative decision-making like humans. Furthermore, the lack of semantic representations for heterogeneous cyber-social-collaborative networks limits integration, interoperability and knowledge discovery from their underlying data sources. Semantic Web ontology models can help to overcome this limitation by semantically describing and interconnecting cyber-physical objects and human participants in a social space. This research addresses the establishment of both cyber-physical and human relationships and their interactions within a social-collaborative network. We discuss how nonhuman resources can be represented as socially connected nodes and utilized by software agents. A software agent-centric Semantic Social-Collaborative Network (SSCN) is then presented that provides functionality to represent and manage cyber-physical resources in a social network. It is supported by an extended ontology model for semantically describing human and nonhuman resources and their social interactions. A software agent has been implemented to perform some actions on behalf of the nonhuman resources to achieve cyber-physical collaboration. It is demonstrated within a real-world decision support system, GRiST (www.egrist.org), used by mental-health services in the UK.

A big data analysis on the five dimensions of emergency management information in the early stage of COVID-19 in China

The all-round and multilevel responses to the epidemic, with professional medical institutions, the governments and the public as the main agents of response and the media as the bridge of communication, are key to developing the public health emergency management system with regard to emerging infectious diseases and diseases with unknown etiology in the information age. This study creates an analysis framework concerning the five dimensions of information—the epidemic itself and the medical, governmental, public and media responses—and analyzes the evolution, interaction and trends of five dimensions using big data within the period of observation For the four dimensions other than the media response, the level of information related to the epidemic and the medical response is relatively high, while the level of response by medical institutions and the governments are similar, and both are higher than the public response. The media coverage of the epidemic remains at a high level of information. In relation to such diseases, the government should take the role of big data analytics seriously, lead a multi-agent social collaboration network, and further strengthen the ‘One Planning Plus Three Systems’ framework related to emergency management in China.