Global Social Network Research Articles

Dereplication of microbial metabolites through database search of mass spectra

Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results.

The role of shared ethnicity in facilitating stepwise migration of educated and skilled individuals: The case of Iranian graduate students in Turkey

In this article, we examine the status of Iranian graduate students as stepwise global skilled migrants who enrol at Turkish universities, but with the intention of moving to their final destination country in the West. Based on survey data we analyse their migration strategies and career plans at mezzo-level, and conclude that more than 72 per cent of respondents can indeed be classified as stepwise migrants. First, Turkey is a preferred intermediate country particularly for migration of Iranian graduate students of Turkish–Azeri ethnolinguistic origins. Second, they use social media to communicate with a global social network of friends to facilitate their move to the final destination country. Third, equipped with accumulated ‘migrant capital’ in Turkey they select a final target country based on its employment prospects, extent of democratic freedoms and the quality of higher education. Finally, while in Turkey, as job seekers they also monitor fluctuations in global demands for skilled workers in their respective disciplines.

Глобальные социальные сети: некоторые теоретические вопросы

Глобальные социальные сети: некоторые теоретические вопросы

Imagining Winnipeg: The translocal meaning making of Filipino migrants to Canada

This study examines how, in the words of Appadurai, “locality emerges in a global world” (Appadurai, 1996, p.18). Specifically, it articulates the nature of information practices in the lives of 14 newcomers to Canada who have migrated from the Philippines to the medium‐size city of Winnipeg. Using a qualitative and exploratory approach, this study applies a transnational lens to this area of research to make explicit the detailed activities and outcomes of newcomer information practices, in particular drawing out the dimensions and implications of newcomers' participation within and across local and global social networks, translocal information landscapes, and across their settlement trajectories. The result is a Translocal Meaning Making process that describes how newcomers come to make sense and use information across distinct and sometimes contradictory information spaces. Our findings suggest that migrant information practices shift across space and time and are constituted both individually, through cognitive and affective processes, and socially, through shared imaginaries, through interactions within and across translocal information landscapes, and through complex deterritorialized networks of people and resources.

"Privacy-preserving Ride Sharing Scheme with Global Social Network for vehicles using Big Data"

Objectives: To built up a productive ride sharing come auto pooling application which empowers the client to go to their goals on the fly easily and reasonable subject to time, limit, and money related limitations, guaranteeing the protection and security concerns and guarantees the client for playing it safe on the goal relying upon the customized setting mindful wellbeing levels. Methods: Taxi-sharing framework acknowledges taxi travelers’ ongoing ride demands sent from advanced mobile phones. It plans appropriate taxicabs to get them through ridesharing and private riding, subject to time limit and fiscal requirements. An auto pooling choice for private auto proprietors whoever goes in a customary course. A customized setting mindful security forecast and proposal for goal area is accommodated by guaranteeing precautionary measures. Findings: This plan can accomplish alluring security highlights. Consequently, we built up a productive ridesharing come auto pooling application which empowers the client to go to their goals on the fly easily and reasonable subject to time, limit, and money related limitations, guaranteeing the protection and security concerns and guarantees the client for playing it safe on the goal relying upon the customized setting mindful wellbeing levels. Improvements: Distinctive instances of ride sharing can be improved out by our plan with considering the clients’ inclinations. Keywords: CI Values, Global Social Networks (GSN), Ride Sharing, Taxi Sharing Framework

Real-time community detection in full social networks on a laptop.

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide free services that are valued by billions of people globally.

TBFN: Trust Based Friend Network Design by Analyzing User’s Voice Call and SMS Pattern

Due to rapid development of Web 2.0 Technology social networking have gained explosive growth. This paper proposes a comparatively new approach to build a trust based social network named Trust Based Friend Net (TBFN) for smartphone users. In TBFN, call log and sms log extracted from user’s smartphone are outsourced into the corresponding social network cloud. Analyzing those real datasets the cloud service provider determines trust values of different direct and indirect friends of smartphone users. Global analysis of everyone’s data results in forming a trusted global social network that is free from fake profiles and that minimizes unscrupulous activities.

Knowledge flows from business method software patents: influence of firms’ global social networks

Using patent citations as an indicator of knowledge flows, this paper examines the effects of firms’ global patent social networks on knowledge flows from business method software patents. Patent social networks are considered along several dimensions, including relative centrality, structural equivalence and brokerage roles. Identifying 19,385 software patents applications to the USPTO by 37 countries during 1995–2012, results show that firms positioned with a relative centrality or situated within the same structural equivalent cluster have more citations to their counterpart firms’ patents. Further, among the different brokerage roles, we find positive promotion to knowledge transfer when the citing and cited firms both serve the role of an itinerant as well as that of a gatekeeper/representative, while firms that act as gatekeeper/representative (alone) cite less patents from firms that do not enact this kind of a role. These unique insights provide a better understanding of channels of knowledge transmission and have implications for the pace of technological change.

Security and privacy in online social networking: Risk perceptions and precautionary behaviour

A quantitative behavioural online study examined a set of hazards that correspond with security- and privacy settings of the major global online social network (Facebook). These settings concern access to a user's account and access to the user's shared information (both security) as well as regulation of the user's information-sharing and user's regulation of others' information-sharing in relation to the user (both privacy). We measured 201 non-student UK users' perceptions of risk and other risk dimensions, and precautionary behaviour. First, perceptions of risk and dread were highest and precautionary behaviour was most common for hazards related to users' regulation of information-sharing. Other hazards were perceived as less risky and less precaution was taken against these, even though they can lead to breaches of users' security or privacy. Second, consistent with existing theory, significant predictors of perceived risk were attitude towards sharing information on Facebook, dread, voluntariness, catastrophic potential and Internet experience; and significant predictors of precautionary behaviour were perceived risk, control, voluntariness and Internet experience. Methodological implications emphasise the need for non-aggregated analysis and practical implications emphasise interventions to promote safe online social-network use.

Exercise contagion in a global social network

We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ∼1.1M individuals who ran over 350M km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour change more effectively.

Differences in the Exchange of Contents of Different Countries in Social Network Sites

The global tool social network sites (SNSs) depend on local issues. The paper compares Latvia (LV), Hungary (HU), United Kingdom (UK) and Germany (GER) to identify similarities and differences in the kind of content which is forwarded to private SNSs. The research evaluates if the global tool SNSs depend on local issues e.g. the country of origin of the member. The influence of the cultural background on the intensity to exchange information is explored in the paper. The research has been done via a survey, survey data were analysed with indicators descriptive statistics, ANOVA to test the difference between the countries and correlation analysis to analyse correlation between factors of social capital and the kind of content published in SNSs. Further the paper uses WarpPLS as a method to estimate the influence of the use of SNSs on the exchange of content to investigate results in the analysed countries and SNSs deeper. The tested statement in the paper is that there exist differences in content of SNS and mutuality's between analysed countries. The result of the research is that there are differences in the use of SNS and content of SNS between the analysed countries. It is not possible to transfer communication strategies or marketing strategies which are successful in one country to another country because the differences between the countries are immense. Especially big differences on analysed aspects are between Germany, the UK and the new European Union (EU) member countries - Latvia and Hungary.

Does landscape connectivity shape local and global social network structure in white-tailed deer?

Intraspecific social behavior can be influenced by both intrinsic and extrinsic factors. While much research has focused on how characteristics of individuals influence their roles in social networks, we were interested in the role that landscape structure plays in animal sociality at both individual (local) and population (global) levels. We used female white-tailed deer (Odocoileus virginianus) in Illinois, USA, to investigate the potential effect of landscape on social network structure by weighting the edges of seasonal social networks with association rate (based on proximity inferred from GPS collar data). At the local level, we found that sociality among female deer in neighboring social groups (n = 36) was mainly explained by their home range overlap, with two exceptions: 1) during fawning in an area of mixed forest and grassland, deer whose home ranges had low forest connectivity were more social than expected; and 2) during the rut in an area of intensive agriculture, deer inhabiting home ranges with high amount and connectedness of agriculture were more social than expected. At the global scale, we found that deer populations (n = 7) in areas with highly connected forest-agriculture edge, a high proportion of agriculture, and a low proportion of forest tended to have higher weighted network closeness, although low sample size precluded statistical significance. This result implies that infectious disease could spread faster in deer populations inhabiting such landscapes. Our work advances the general understanding of animal social networks, demonstrating how landscape features can underlie differences in social behavior both within and among wildlife social networks.

Cognitive social network analysis for supporting the reliable decision-making process

With the advancement of the Internet and web technologies, social networks have gained attention as a new paradigm for user-centered information systems. As the amount of accessible information increases, the need for personalized information increases as well. Under such circumstances, social networks that are based on trust between users are increasingly utilized to provide efficient and reliable information management. This paper proposes the cognitive social network analysis that analyzes relationships between users with typical properties. The proposed approach analyzes users’ habitual activities and creates a local social network. The framework then integrates the local networks via the friend of a friend, thereby creating a global social network. User relationships in the global network are reinforced to maximize information sharing. To evaluate the performance of the information shared in the proposed autonomic cognitive social network framework, the accuracy of the information associated with social network was measured using the ROC Curve. In future, we should analyze the social influence factors from relationship between community and users.

Social network model for crowd anomaly detection and localization

In this work, we propose an unsupervised approach for crowd scene anomaly detection and localization using a social network model. Using a window-based approach, a video scene is first partitioned at spatial and temporal levels, and a set of spatio-temporal cuboids is constructed. Objects exhibiting scene dynamics are detected and the crowd behavior in each cuboid is modeled using local social networks (LSN). From these local social networks, a global social network (GSN) is built for the current window to represent the global behavior of the scene. As the scene evolves with time, the global social network is updated accordingly using LSNs, to detect and localize abnormal behaviors. We demonstrate the effectiveness of the proposed Social Network Model (SNM) approach on a set of benchmark crowd analysis video sequences. The experimental results reveal that the proposed method outperforms the majority, if not all, of the state-of-the-art methods in terms of accuracy of anomaly detection.

Sustaining a Global Social Network: a quasi-experimental study.

To examine the longer term impact on the social network of participating nurses in the Global Nursing Leadership Institute (GNLI2013) through using differing frequencies of follow-up to assess impact on maintenance of network cohesion. Social network analysis is increasingly been used by nurse researchers, however, studies tend to use single point-in-time descriptive methods. This study utilizes a repeated measures, block group, control-intervention, quasi-experimental design. Twenty-eight nurse leaders, competitively selected through a double-blind peer review process, were allocated to five action learning-based learning groups. Network architecture, measures of cohesion and node degree frequency were all used to assess programme impact. The programme initiated and sustained connections between nurse leaders drawn from a geographically dispersed heterogeneous group. Modest inputs of two to three e-mails over a 6-month period seem sufficient to maintain connectivity as indicated by measures of network density, diameter and path length. Due to the teaching methodology used, the study sample was relatively small and the follow-up data collection took place after a relatively short time. Replication and further cohort data collection would be advantageous. In an era where many policy solutions are being debated and initiated at the global level, action learning leadership development that utilizes new technology follow-up appears to show significant impact and is worthy of wider application. The approach warrants further inquiry and testing as to its longer term effects on nursing's influence on policy formulation and implementation.

Prior-Learning, Cumulative Science Experiences and the Absorptive Capacity of Bio-Entrepreneurs: A Case of the East Midlands Region, England

<p>In the modern healthcare and medical sectors corporate bio-pharmaceutical firms continue to scale down their in-house research and development (R&D) activities in favour of outsourcing the services to bio-tech ventures. These small but, entrepreneurial research-oriented organisations have increased dramatically. They are predominantly owned by bio-entrepreneurs who are extensively experienced scientists. In the science-based industry they operate in, innovation “ecosystems” consisting of global business and social networks are a common feature. As such, they have to consistently exploit them to complement the knowledge gaps in their enterprises. In that context, the paper sets out to investigate five bio-entrepreneurs currently active in biotechnology within the East Midlands region in England. It particularly examines the role performed by their prior-learning and their cumulative science experiences in recognising, assimilating and productively applying science-related knowledge acquired in their innovation “ecosystems”.</p>

Competition between global and local online social networks

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Discovering internal social relationship for influence-aware service recommendation

Existing approaches, such as semantic content-based or Collaborative Filtering-based recommendations, fail to exploit social aspects of services because services lack social relationships and do not consider social influence. In this paper, we propose a methodology for connecting distributed services in a global social service network (GSSN) to facilitate discovering internal social relationship for social influence-aware service recommendation. First, we propose a novel platform for constructing a GSSN by linking distributed services with social links based on quality of social link. We then propose a flexible model of the effective awareness of social influence, which provides a quantitative measure of the strength of influence between services. Next, a novel social influence-aware service recommendation approach is proposed based on GSSN using internal social relationship among services. The experimental results demonstrated that our new approach can solve the service recommendation problem with a low usage threshold and high accuracy, where the user preferences are exploited by a recommend-as-you-go method.

Tavern and the internet sociability: A tomarin

Although the tavern as a social institution and the internet as technology do not constitute phenomena of the same kind, comparing them has sociological significance in the context of tavernology. In this paper, such comparison will include comparing the tavern and the internet sociability based on the functions that theorists attach to the one or the other phenomenon. The basic hypothesis is that most functions attributed to the tavern can be applied to the internet and vice versa, which points to the conclusion that what is at the core of the social aspect of the internet use is, in fact, the copying of patterns of sociability from a real into a virtual space. Consequently, the tavern and the internet sociability are not conflicting but complementary concepts. The internet sociability in fact represents 'the version 2.0' of its tavern counterpart, because it is derived from the patterns of social relationships peculiar to the period of modernity which the global social network upgrades, shifts to a virtual space, and at the same time, as each new phenomenon does, creates new controversies and dilemmas.

Benefits of Enterprise Social Networking Systems for High Energy Physics community

The emergence of social media platforms in the consumer space unlocked new ways of interaction between individuals on the Web. People develop now their social networks and relations based on common interests and activities with the choice to opt-in or opt-out on content of their interest. This kind of platforms have also an important place to fill inside large organizations and enterprises where communication and collaborators interaction are keys for development. Enterprise Social Networking Systems (ESN) add value to an organization by encouraging information sharing, capturing knowledge, enabling action and empowering people. CERN is currently rolling out an ESN which aims to unify and provide a single point of access to the multitude of information sources in the organization. It also implements social features that can be added on top of existing communication channels. While the deployment of this kind of platforms is not without risks we firmly believe that they are of the best interest for our community, opening the opportunity to evaluate a global social network for High Energy Physics (HEP).