Using Social Network Research in HRM: Scratching the surface of a fundamental basis of HRM

This article is the guest editors' introduction to a special issue on using Social Network Research in the field of Human Resource Management. The goals of the special issue are: (1) to draw attention to the points of integration between the two fields, (2) to showcase research that applies social network perspectives and methodology to issues relevant to HRM and (3) to identify common challenges where future collaborative efforts could contribute to advancements in both fields.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.

Official use of social network sites by African universities

The use of social network sites (SNS) has become very valuable to educational institutions. Some universities have formally integrated these social media in their educational systems and are using them to improve their service delivery. The main aim of this study was to establish whether African universities have embraced this emerging technology by having official presence on SNS. A purposive sampling method was used to study 24 universities from which data were obtained by visiting their official websites and following the official links to the most common SNS.

Generic intertextuality in online social activism: the case of the It Gets Better project

The It Gets Better project has been held up as a model of successful social media activism. This article explores how narrators of It Gets Better videos make use of generic intertextuality, strategically combining the canonical narrative genres of the exemplum, the testimony, and the confession in a way that allows them to claim ‘textual authority’ and to make available multiple moral positions for themselves and their listeners. This strategy is further facilitated by the ambiguous participation frameworks associated with digital media, which make it possible for storytellers to tell different kinds of stories to different kinds of listeners at the same time, to simultaneously comfort the victims of anti-gay violence, confront its perpetrators, and elicit sympathy from ‘onlookers’. This analysis highlights the potential of new practices of online storytelling for social activism, and challenges notions that new media are contributing to the demise of common narrative traditions.

Facebook faith - social networking in a faith based community

This paper views the increasing social networking as an efficient emerging ministry to the moveable generation. Through social network such as Facebook, ministry from a pastoral perspective can become more authentic and meaningful. Ministry is relational. Social Networking sites provide a strong platform to being part in other people’s life. Social networking and living online builds community beyond geographical boarders. Young adults and youths digital identity often reflects their faith, this is supported by research which suggests a practice of more openness to share and expose private issues online. Spiritual and religious views are freely shared, creating sacred spaces in the midst of life practising a holistic faith identity in a secular community. Providing a strong platform for information flow, Social Network is attractive in a postmodern society where inviting people to join in events are perceived as non threatening, making church community events transparent and available to people who do not attend church, inviting spiritual friendships and relationships. Social Networking strengthens relationship in a non hierarchical manner and invites the minister into lives where there previously would have been barriers, engaging in prayer and bible study as well as pastoral care through social networking, thus relationships deepens via social networking making people real. It has been observed that, although community building happens on the net, church affiliation loyalty remains to the local community. Therefore presence ministry though social networks emerges as a core form of ministry, where relations to youth who move from local church to university campuses are kept alive. The asynchronous nature of communication within social networking eases the minister in her work. The minister is able to engage with many individuals at the same time. Before the minister could visit one person at a time, now she visits 5-6 individuals at any given time. Therefore social networking not only increases the quality of the work, but also empowers the minister to be more efficient.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Interventions in social networks: impact on mood and network dynamics

Results from two studies on longitudinal friendship networks are presented, exploring the impact of a gratitude intervention on positive and negative affect dynamics in a social network. The gratitude intervention had been previously shown to increase positive affect and decrease negative affect in an individual but dynamic group effects have not been considered. In the first study the intervention was administered to the whole network. In the second study two social networks are considered and in each only a subset of individuals, initially low/high in negative affect respectively received the intervention as `agents of change'. Data was analyzed using stochastic actor based modelling techniques to identify resulting network changes, impact on positive and negative affect and potential contagion of mood within the group. The first study found a group level increase in positive and a decrease in negative affect. Homophily was detected with regard to positive and negative affect but no evidence of contagion was found. The network itself became more volatile along with a fall in rate of change of negative affect. Centrality measures indicated that the best broadcasters were the individuals with the least negative affect levels at the beginning of the study. In the second study, the positive and negative affect levels for the whole group depended on the initial levels of negative affect of the intervention recipients. There was evidence of positive affect contagion in the group where intervention recipients had low initial level of negative affect and contagion in negative affect for the group where recipients had initially high level of negative affect.

Facebook & BlackBoard: comparative view of learning environments

For several years, online educational tools such as Blackboard have been used by Universities to foster collaborative learning in an online setting. Such tools tend to be implemented in a top-down fashion, with the institution providing the tool to the students and instructing them to use it. Recently, however, a more informal, bottom up approach is increasingly being employed by the students themselves in the form of social networks such as Facebook. With over 9,000 registered Facebook users at the beginning of this study, rising to over 12,000 at the University of Reading alone, Facebook is becoming the de facto social network of choice for higher education students in the UK, and there was increasing anecdotal evidence that students were actively learning via Facebook rather than through BlackBoard. To test the validity of these anecdotes, a questionnaire was sent to students, asking them about their learning experiences via BlackBoard and Facebook. The results show that students are making use of the tools available to them even when there is no formal academic content, and that increased use of a social networking tool is correlated with a reported increase in learning as a result of that use.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

Confronting social defence mechanisms: avoiding disorganization during crises

Crises cause social disturbances within their host organisation and the patterns of interpersonal ties that emerge are an important determinant of crisis management efficiency. In this article, social network analysis is used within a construction project context, to demonstrate that efficient crisis management depends upon the design and maintenance of an appropriate social fabric. However, crises have defence mechanisms that make management difficult by inducing forces that encourage people to pursue inappropriate social ties. Purposeful social intervention is therefore an essential part of the crisis management process to confront and avoid disorganisation.

Position paper on the future of social networking

Social networking mediated by web sites is a relatively new phenomenon and as with all technological innovations there continues to be a period of both technical and social adjustment to fit the services in with people’s behaviours, and for people to adjust their practices in the light of the affordances provided by the technology. Social networking benefits strongly from large scale availability. Users gain greater benefit from social networking services when more of their friends are using them.This applies in social terms, but also in eLearning and professional networks. The network effect provides one explanation for the popularity of internet based social networking sites (SNS) because the number of connections between people which can be maintained by using them is greatly increased in comparison to the networks available before the internet. The ability of users to determine how much they trust information available to them from contacts within their social network is important in almost all modes of use. As sources of information on a range of topics from academic to shopping advice, the level of trust which a user can put in other nodes is a key aspect of the utility of the system.

Social networks and positive and negative affect

We followed 100 university students in the UK for one week, instructing them to record all face-to-face, phone and digital contacts during the day as well as their positive and negative affect. We wanted to see how positive and negative affect spread around a social network while taking into account participants’ socio-demographic data, personality, general health and gratitude scores. We focused on the participants’ connections with those in their class; excluding friends and family outside this group. The data was analysed using actor-based models implemented in SIENA. Results show differences between positive and negative affect dynamics in this environment and an influence of personality traits on the average number and rate of communication.

Social networks and occupational choice: the endogenous formation of attitudes and beliefs about tax compliance

The paper analyses the emergence of group-specific attitudes and beliefs about tax compliance when individuals interact in a social network. It develops a model in which taxpayers possess a range of individual characteristics – including attitude to risk, potential for success in self-employment, and the weight attached to the social custom for honesty – and make an occupational choice based on these characteristics. Occupations differ in the possibility for evading tax. The social network determines which taxpayers are linked, and information about auditing and compliance is transmitted at meetings between linked taxpayers. Using agent-based simulations, the analysis demonstrates how attitudes and beliefs endogenously emerge that differ across sub-groups of the population. Compliance behaviour is different across occupational groups, and this is reinforced by the development of group-specific attitudes and beliefs. Taxpayers self-select into occupations according to the degree of risk aversion, the subjective probability of audit is sustained above the objective probability, and the weight attached to the social custom differs across occupations. These factors combine to lead to compliance levels that differ across occupations.

Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

Weighted alpha-rate dominating sets in social networks

We are looking into variants of a domination set problem in social networks. While randomised algorithms for solving the minimum weighted domination set problem and the minimum alpha and alpha-rate domination problem on simple graphs are already present in the literature, we propose here a randomised algorithm for the minimum weighted alpha-rate domination set problem which is, to the best of our knowledge, the first such algorithm. A theoretical approximation bound based on a simple randomised rounding technique is given. The algorithm is implemented in Python and applied to a UK Twitter mentions networks using a measure of individuals’ influence (klout) as weights. We argue that the weights of vertices could be interpreted as the costs of getting those individuals on board for a campaign or a behaviour change intervention. The minimum weighted alpha-rate dominating set problem can therefore be seen as finding a set that minimises the total cost and each individual in a network has at least alpha percentage of its neighbours in the chosen set. We also test our algorithm on generated graphs with several thousand vertices and edges. Our results on this real-life Twitter networks and generated graphs show that the implementation is reasonably efficient and thus can be used for real-life applications when creating social network based interventions, designing social media campaigns and potentially improving users’ social media experience.