The role of networking and social media tools during job search: an information behaviour perspective

Introduction

Prominent contributors to the field of job search theory have called for (a) a better understanding of how social networks can assist jobseekers to find work, and (b) to extend research on the particular sources and behaviour that are used in this process (Van Hoye, Klehe and van Hooft, 2013, p.15; Wanberg, 2012, p.389). The purpose of this paper is to provide a critical evaluation of the extant literature pertaining to the networking behaviour of young jobseekers, and the adoption of social media tools during this process. Based on the premise that networking is a “fundamental information seeking activity” (Meho and Tibbo, 2003, p.581), Tom Wilson’s (1997) general model of information behaviour is proposed as a potential suitable framework for exploring in greater depth the concept of networking during job search.

The ability of jobseekers to use social networks effectively during job search is considered a key facet of employability in the modern labour market (McQuaid and Lindsay, 2005). Indeed, research shows that around a third (31%) of workers in the UK find employment via their network contacts (Franzen and Hangartner, 2006, p.357). This phenomenon has been explained by the dissemination of job information throughout social structures (Granovetter, 1973; 1983; 1995; Lin, 1999; 2002). This is also recognised in job search theory, which highlights informal sources (i.e. network contacts such as family members and acquaintances) as crucial repositories of job information (Saks, 2005; Van Hoye et al, 2013; Wanberg, 2012). Indeed, the use of informal sources is considered a specific job search method, often referred to as networking (Lambert, Eby and Reeves, 2006; Saks, 2005; Van Hoye et al, 2013; Van Hoye, van Hooft and Lievens, 2009; Wanberg, 2012; Wanberg, Kanfer and Banas, 2000).

Social media tools, and in particular social networking sites such as Facebook and LinkedIn, proffer a potentially crucial utility to networking jobseekers (Mowbray et al, 2016). This can be partly explained by the loosely-knit social circles that such technologies can help to generate across geographical boundaries. They can facilitate membership of multiple networks which, coupled with widespread access to mobile and other “wearable” devices, provide access to “information gathering capacities that dwarf those of the past” (Rainie and Wellman, 2012, p.11). The position taken in this paper is that in order to fully comprehend the networking behaviour of young jobseekers in the 21st century, it is necessary to examine how they engage with the social media tools that support networks in online environments.

In the next section the methods used to source and evaluate the literature included in the review are detailed, followed by a presentation of Wilson’s (1997) model of general information behaviour as a potential theoretical framework for analysing the networking behaviour of young jobseekers.

Method

The research questions that this work sought to address through a review of the relevant literature are as follows:

1. What are the key, offline, modes of networking behaviour employed by young jobseekers during the job search process?
2. How do social media tools support the networking behaviour of the young jobseekers during the job search process?

The main findings from the review are taken from an analysis of sixty-three papers published between 1973 and 2016. In the first instance, the top publications from the field of library and information science were reviewed, including: Information Research, Journal of the American Society for Information Science and Technology, Library and Information Science Research, and The Journal of Academic Librarianship. The review process involved reading the articles from each journal issue of the past five years, and identifying those which were most relevant to the research questions. These were then stored on Mendeley, and categorised thematically in folders titled ‘social networks’, ‘social media tools’, ‘information needs’ etc. Each article was then analysed by highlighting key passages and taking detailed notes on a separate Word file. During this process an index of tags was created, which were grouped together to inform and develop the key themes from the review which are presented in Section 3.

The above task helped to identify substantial gaps in the information science literature as relevant to the research topic. To extend the search, a number of key terms were entered into a variety of online search engines and databases (Please see Table 1 below). These included: ABI/Information Complete, Emerald Journals, Google Scholar, Sage Journals Online, ScienceDirect, and the Wiley Online Library. Many of the papers sourced as a consequence have been published in library and information science, psychology, sociology and computer science titles such as: American Sociological Review, Computers in Human Behavior, Organizational Behavior and Human Performance. A similar process of analysis to the one outlined above was carried out on these articles, with further knowledge gaps being identified. To complement this process, each relevant article was also used for a backwards and forwards chaining of references, and citation analysis. This helped determine the authors and works which were most frequently cited by others in the same field (Hart, 2002, p.39). Each author was then catalogued by research field, and ranked by relevance/prevalence to the topic of networking during job search.

A theoretical model for networking jobseekers

The primary contribution of this paper is to propose Wilson’s (1997) general model of information behaviour (see Figure 1) as a suitable theoretical framework which can be used to address the research questions. The theory which was used to develop the model (Wilson, 1981; 1997; 2000) has been heavily cited. It derives from extensive research within the field of information science, rendering it one of the most prominent within the field (Wilson’s model is regularly covered in standard information science textbooks, such as: Bawden and Robinson, 2012; Case, 2002; Ford, 2015). The model is particularly relevant here given that it was derived from an interdisciplinary perspective. Indeed, Wilson (1997, p.570) expounds the value of integrating other academic disciplines within information science to create fruitful new areas of research. As can be seen in Figure 1, Wilson’s (1997) model

includes the following three key components: context of information need, intervening variables, and information seeking behaviour. In light of an examination of the results from the literature review in Section 3 below, these components will be analysed with regards to their suitability as a theoretical framework which can be used to investigate the networking behaviour of young jobseekers, both offline and online.

Findings

The review process documented in the ‘Method’ section led to the identification of three broad research themes pertaining to the networking behaviour of young jobseekers: (1) social network theory, and the use of informal channels of information during job search; (2) the role of networking behaviour in job search; and, (3) The adoption and use of social media tools. These research themes are discussed in detail below.

Social network theory, and the use of informal channels of information during job search

The study of the information sources consulted by jobseekers has been an integral theme of the job search literature (Saks, 2005; Wanberg, 2012). Indeed, in measuring the intensity of job search behaviour, Blau (1993; 1994) conceptualised the process of looking for a job as the engagement in two distinct processes: preparatory job search and active job search. The former of these processes involves activities such as identifying job leads and researching occupations, whilst the latter focuses on actively applying for jobs. The preparatory phase is essentially a period of self-regulated information seeking, wherein both formal and informal information sources can be consulted (Barber et al., 1994; Wanberg, 2012). Informal sources pertain to the jobseekers’ social network i.e. friends, family members, co-workers etc. (Saks, 2005, p.159).

The strength of network ties and the diffusion of job information

An underlying premise of network theory is that social networks have the capacity to beget important informational resources for individuals (see, for example, Burt, 2009; Granovetter, 1973; Lin, 1999). Indeed, individuals often approach their social network for advice or information before expanding their search to include different sources (Huvila, 2011; Wellstead, 2011). With regard to the mobility of the labour market, Granovetter’s (1973) seminal paper introduces the concept of the strength of network ties in the dissemination information via interpersonal contacts. At its core the strength of ties is a distinction between two types of relationship in an individual’s social network: weak and strong ties. Such ties are defined by the frequency of exchange between contacts in the existing relationship. Strong ties, therefore, tend to be close friends and family, whereas weak ties are acquaintances. As they are purported to be more likely to reach distant parts of the social system, Granovetter’s (1973; 1983; 1995) thesis maintains that individuals with higher numbers of weak ties are more likely to be beneficiaries of novel job information. Additionally, it is contended that weak ties have superior utility in the attribution of labour.

Granovetter’s theory has received some empirical support (see, for example, Granovetter, 1974; Yakubovich, 2005). In terms of effective information diffusion, there are other cases outside labour market research which highlight the function of weak ties. For example, using large sets of mobile phone calls, it has been shown that strong ties severely limit the spread of information throughout the social system, and that weak ties are important in retaining the overall integrity of a social network (Karsai, Perra and Vespignani, 2014; Onella et al, 2007). Weak ties also play a crucial role as bridges which help to relay information between social groups in the context of word-of-mouth referrals in consumer behaviour (Brown and Reingen, 1987).

Despite the evidence discussed above, further research suggests that the relationship between tie strength and the mobility of labour is often complex, multidimensional, and seemingly contradictory. For example, Franzen and Hangartner (2006) found strong ties to be more prolific in the allocation of labour. Also, whilst other studies convey the potential of weak ties to the jobseeker, there are indications that this may only be for certain subgroups such as individuals with high status prior jobs (Wegener, 1991), or those who are better educated (Ericksen and Yancey, 1980). Additionally, it is argued that strong ties have more utility for younger people who are entering the job market for the first time (Granovetter, 1973, p.42; Kramarz and Skans, 2014). This could potentially be explained by a lack of access to weak ties, which Granovetter contends are self-generating throughout the term of a career (Granovetter, 1995, p.85).

Although Granovetter’s theory has proved controversial, the conceptualisation of tie strength has been the catalyst for an exponential rate of research across a number of fields and disciplines. An understanding of tie strength could also be significant to the study of networking during job search. Thus far the literature focuses on the role of network ties at the intersection of the job search process, wherein individuals are offered their most recent/current job position. To this end, there remains much to be understood regarding the role of network ties of varying strength throughout the entirety of the job search process. It would also be useful to explore the role of weak ties in online environments. Weak ties are integral to the propagation of information throughout online networks (Zhao, Wu and Xu, 2010), and this could prove useful for young jobseekers attempting to access a pool of novel informational resources.

Social networks and the concept of social capital

As recognised by Granovetter (1995, p.151), limiting consideration of the nature of ties to those shared by individuals cannot provide a sufficient understanding of how labour is allocated via network contacts. Equally important is the exploration of wider network characteristics, such as the social capital resources that are contained therein (Lin, 2008, p.4). From a theoretical perspective, indicators of strong social capital could be the potential diversity and range of resources available to individuals via their networks, or occupational status, and influence of their specific network contacts (Lin, 1999, p. 37). Higher levels of social capital can have a key bearing on the employment outcomes of individuals. For example, having a higher proportion of contacts with elevated occupational prestige has been associated with the likelihood of finding a new job (De Graaf and Flap, 1988; Lin, 1981; Moerbeek, 2001, pp.139-150). This could be due to those with higher social capital being able to access a better standard of informational resource from their social networks (Johnson, 2015).

In contrast to the above, poorer levels of social capital can have a deleterious impact on individuals’ employment opportunities. A study of marginalised people in Glasgow, for example, found that participants tended to operate in dense and homogenous networks, with restricted access to ties in the labour market (Quinn and Seaman, 2008). This conclusion is supported in research by Gayen, Raeside and McQuaid (2010), which shows that people with higher levels of unemployed contacts embedded within their social network are more likely to be unemployed themselves. Young people who are entering the labour market for the first time can be particularly vulnerable to low levels of ascribed social capital. For example, youths brought up in single-parent families, or detached from the school system are likely to face unemployment later in life (Caspi et al., 1998). Quinn and Seaman (2008) also found that marginalised young people could often refer to few role models in employment, and these contacts invariably had jobs of low status.

Thus, whilst both strong ties and weak ties are potentially important in the job search process, their utility hinges on the social resources that they relay to the jobseeker. However, the bulk of this research fails to adequately describe the functionality of the informational resources assumed to play a crucial role in determining employment outcomes in the labour market. There is also a focus on accessible social capital and its associations with various outcomes, as opposed to capital which is actually mobilised by jobseekers. To fully understand the job search process, it will be necessary to determine the role of mobilised social capital.

The role of networking behaviour in job search

Defining networking behaviour

Networking has been defined in job search literature as: “individual actions directed toward contacting (…) people to whom the job seeker has been referred for the main purpose of getting information, leads or advice on getting a job” (Wanberg, Kanfer and Banas, 2000, p.492). This suggests that in the job search process networking is largely a transactional activity, wherein already established contacts are used to acquire resources. In this sense, networking during job search is viewed through the lens of mobilising existing sources of social capital.

There is a broad consensus across the organisational and job search literature that the process of networking involves the individual engaging in a series of activities (Gibson et al, 2014; Forret and Dougherty, 2001; McCallum, Forret and Wolff, 2014; Treadway et al., 2010; Van Hoye et al, 2009; Wanberg et al, 2000; Wolff, Moser and Grau 2008). Three empirical studies focus specifically on networking as a job search behaviour, using composite job measures for comparative purposes (Lambert et al, 2006; Van Hoye et al, 2009; Wanberg et al, 2000). Lambert et al (2006) and Wanberg et al (2000) include behaviour such as jobseekers making direct requests to family, friends and acquaintances for job leads. The networking measures used in the third study (Van Hoye et al, 2009) were verified by analysis of data collected from Flemish job seeking manuals from the practitioner literature, focus groups with the Flemish Public Employment Service, and interviews with local jobseekers. However, the purpose of this approach was primarily to determine the general job search methods used by the local population, and the final survey only included two questions about the networking behaviour (Van Hoye et al, 2009, p.682). Evidently, these studies are empirically driven, yet suffer from a lack of theoretically grounded knowledge on networking behaviour.

Predictors and outcomes of networking

The measures of networking outlined above were produced for the purposes of conducting empirical studies to test predictors of engagement in networking behaviour. Extant research suggests that personality traits are significantly associated to networking: both higher levels of conscientiousness and extraversion predict higher levels of networking intensity (Van Hoye et al, 2009; Wanberg et al, 2000). A proactive personality has also been associated with engagement in networking behaviour (Lambert et al, 2006). It is notable that in organisational behaviour research, extraversion and conscientiousness have also been significantly associated with engagement in networking behaviour, alongside self-esteem (Forret and Dougherty, 2001). Other factors have also been important, such as possessing an advanced degree, and coming from a higher socio-economic background (Forret and Dougherty, 2001).

Research on the outcomes of networking during job search is sparse. However, evidence does suggest that, taken in isolation, increased levels of networking intensity are related to lower levels of unemployment insurance benefit exhaustion and a higher likelihood of reemployment (Wanberg et al, 2000). Networking is also associated with an increased number of job offers, although the effects of this have been found to be incremental (Van Hoye et al, 2009).

The findings outlined in this section provide an insight into how networking behaviour is associated with job outcomes, and the characteristics of those who engage in networking: please see Table 3 for a synthesis of the results. However, methodologically these studies are empirically driven and lack sufficient theoretical grounding. As such, the concept of networking as an information seeking behaviour during job search is one that remains underdeveloped in the job search literature.

Networking behaviour in information behaviour research

A few information behaviour studies deal with networking behaviour explicitly. For example, networking has emerged as a key information seeking behaviour through qualitative studies of certain occupational or demographic groups. Academics, for example, report networking behaviour to be an integral part of their information seeking and sharing pursuits (Foster and Ford, 2003; Meho and Tibbo, 2003). Studies by Huvila (2011) and Wellstead (2011) also report networking behaviour via qualitative analysis. In these studies, the potential barriers people face to effective networking are uncovered. These include a disinclination by males to ask for advice to avoid appearing weak (Wellstead, 2011), and young people having to turn to non-network sources because their immediate network is unable or unwilling to answer their queries (Huvila, 2011). The latter example could be indicative of low levels of social capital contained within a social network.

Another theme of research in information science which is related to, but does not explicitly reference, networking behaviour is that of finding information in serendipitous circumstances. Ruben, Burkell and Quan Haase (2011) for example, found that the opportunistic sourcing of information often happens when individuals are in the company of, or come across, other individuals who have informational resources sought in another context. These exchanges happen in offline and online environments, with both strangers and acquaintances. A recurring theme in several of the cases cited in the paper was that all the information seekers had a ‘prepared mind’, so even though they found the information whilst engaged in an activity which was not related to their information seeking goal, they were in a frame of mind which allowed them to notice the opportunity. A review of serendipity literature by Agarwal (2015) reached a similar conclusion. Here it was concluded that these chance encounters are particularly beneficial to individuals who are in a state of alertness about their information seeking goals, whilst not necessarily taking part in purposive information seeking behaviour. It is possible that alert jobseekers could take advantage of opportunistic information acquisition in similar circumstances. This is particularly so given that social media tools create a digital environment which can facilitate serendipity in information seeking (McCay-Peet, Toms, and Kelloway, 2015).

The qualitative approaches used in the bulk of these studies could be applied to the concept of networking during job search to gain a richer understanding of networking as a theoretical construct. Also, whilst they draw attention largely to offline networking behaviour, the studies conducted by Foster and Ford (2003) and Meho and Tibbo (2003) indicate that digital technologies can be crucial in facilitating and extending opportunities to network during information seeking. Given the proliferation of social media tools over the past decade, it would be beneficial to understand what role these have in the networking behaviour of young jobseekers.

The adoption of social media tools

Social media tools, personality traits, and demographics

A substantial portion of the literature on the adoption of social media tools focuses on the characteristics of users, and their behaviour. For example, in the information behaviour literature, personality traits are shown to be key internal drivers of different approaches to information seeking (Ford, 2015, pp.109-111). Extraversion, neuroticism, openness to experience and sociability have all been significantly related to the levels of informational use of Facebook, whilst for Twitter this has been correlated with conscientiousness and a need for cognition (Hughes, Rowe and Batey, 2012).

Personality factors have also been shown to have a bigger impact on the use of social media tools for information seeking than variables such as the academic discipline or class-level amongst students (Kim, Sin and Tsai, 2014). As is the case for offline networking, extraversion has been positively associated with numbers of Facebook friends, membership of Facebook groups, and frequency of use of social media tools (Amichai-Hamburger and Vinitzky, 2010; Correa, Hinsley and de Zuniga, 2010; Ross et al, 2009; Rowe, Batey and Lee, 2012). However, the relationship between personality traits and online social networking is more complex. For example, neuroticism (i.e. being anxious and moody) is frequently associated with SNS use, and it has been shown that introverted users are more likely to share information on their Facebook profiles than those who display higher levels of extraversion (Amichai-Hamburger and Vinitzky 2010; Ehrenberg et al, 2008; Ross et al, 2009; Zywica and Danowski, 2008).

Demographics have also been a keen focus of scholars who study social media adoption, with gender proving to be a significant variable. For example, male college students generally use a broader range of social media tools to perform information tasks than their female counterparts (Sin and Kim, 2013; Kim et al, 2014). Additionally, females are more inclined to use social networking sites for social purposes than for task-oriented reasons (Lin and Lu, 2011), and to use them more frequently (Mowbray et al, 2016; Zywica and Danowski, 2008). Age also plays a role in determining which social media tools individuals will adopt for information seeking purposes. Young undergraduate students, for example, are more likely than their older counterparts to seek everyday information from social networking sites (Kim et al, 2014; Sin and Kim, 2013), and younger people generally use social networking sites more frequently (Mowbray et al, 2016).

Social media tools and job search

More than half of jobseekers in the UK are using social media tools during job search (Adecco, 2014). Indeed, information seeking on businesses and to self-educate are two of the most common self-reported reasons why users adopt social media tools (Whiting and Williams, 2013). However, there is a general lack of academic research pertaining to information seeking during job search which could elucidate these findings. For example, health studies shows that users of social networking sites are only inclined to seek information for minor ailments and general lifestyle advice on platforms such as Facebook, due to concerns about their contacts’ lack of medical knowledge (Zhang, 2012). This perceived veracity of an online community’s lead users and their contributions has a significant impact on behavioural intentions to use specific platforms (Koch, Toker, and Brulez, 2011). These perceptions could also be crucial in determining the extent to which young jobseekers use social media tools during job search. This could particularly be the case for younger jobseekers, who tend to favour Facebook over LinkedIn in their search for information relating to employment, and therefore could be relying more on their personal networks for advice (Nikolaou, 2014).

The focus of research pertaining to social media adoption has often centred on the personality traits of users. The aggregate of the findings from these studies suggests a broader range of personality types engage in online social networking than is the case with offline networking. Based on this evidence, it is a reasonable supposition that social media tools could provide a crucial outlet for young jobseekers looking for information, and particularly those who are disinclined to engage in networking offline. However, further research is required to determine the how young people engage with social media tools during job search, and for what purpose. It is for this purpose that Wilson’s (1997) general model of information behaviour is proposed as a framework.

Using Wilson’s model to study networking behaviour during job search

Wilson’s model: context of information need

According to Wilson (1981, p.6), the main factors which contribute to the context of information need are personal, environmental, and role related. It is clear from the literature review above that personal factors such as personality traits, and environmental factors such as number of strong ties have a bearing on the networking behaviour of jobseekers (Van Hoye et al., 2009; Wanberg et al., 2000). However, more could be understood about the context of jobseekers’ information needs. Other environmental factors such as cultural concerns could be important. For example, men can often operate in a cultural environment wherein asking for help is interpreted as a sign of weakness (Wellstead, 2011). Additionally, individuals have varying levels of access to social capital in their networks which could undermine their ability to source relevant information (Huvila, 2011; Raeside and McQuaid, 2010). This concern is crucial for young jobseekers, who are more likely to be reliant on family members for advice (Quinn and Seaman, 2008).

In terms of role, there are a number of key contextual factors which are not addressed in the current networking literature. For example, does the employment status of jobseekers impact their networking behaviour? Also, ascertaining the occupation sought by the jobseeker could be an important contextual factor. These issues are particularly relevant to understand networking during job search; as investigating the basic needs which drive the motivations of individuals could elucidate the subsequent direction of their behaviour (Deci and Ryan, 2008). As such, the focus on the context of information need is a critical component of Wilson’s (1997). This would validate its use to further explore the networking behaviour of young jobseekers.

Wilson’s model: intervening variables

Wilson’s (1997) model illustrates that individuals with information needs face a number of intervening variables which can either hinder or enable involvement in the information seeking process. These variables can be psychological, demographic, interpersonal, environmental, or even related to the source characteristics of the information channel (e.g. social media tools). This paper has underlined how offline social networking can be influenced by a myriad of variables, such as personality types, demographics, and the composition of social networks. In order to derive a realistic interpretation of the offline and online networking behaviour of young jobseekers, it is important to determine which intervening variables act as enablers and barriers to information seeking through social networks. For example, given that the use of social media for general purposes is significantly higher than social media use for job search (Adecco Group, 2014, p.8), there is clear scope to ascertain the factors that enable or hinder job search behaviour amongst young jobseekers. Therefore, the focus on intervening variables again validates the use of Wilson’s (1997) model for further research in this area.

Wilson’s model: information seeking behaviour

As discussed in Section 3, the methods employed in previous networking research make broad assumptions about the nature of networking as an information seeking activity. This provides further justification for the use of Wilson’s (1997) model, which draws attention to different categories of information seeking behaviour, such as: active search, ongoing search, passive attention and passive search. Differentiating between modes of behaviour is particularly relevant. As explained by Wilson (1997, p.562), passive attention can happen during activities such watching the television, or other such times where information could be unintentionally gathered. Passive search is described as when the individual is engaged in another behaviour or search, and comes across information which happens to be relevant to them in the process. As the review has shown, young people are frequently engaged in the use of social networking sites throughout the course of the day (Mowbray et al, 2016). With increased engagement with social media tools amongst recruiters (Adecco Group, 2014, p.35), the possibility of passive acquisition of information during job search must also be investigated, in addition to active networking behaviour. This is particularly apparent when taking into consideration the findings from research into the serendipitous acquisition of information in digital environments (McCay-Peet, Toms, and Kelloway, 2015).

Conclusion

This review paper has presented and analysed the key themes of research pertaining to the networking behaviour of young jobseekers, in both offline and online environments. Three areas of research have been identified as relevant to this topic: (1) social network theory, and the use of informal channels of information during job search, (2) the role of networking behaviour in job search, and (3) the adoption and use of social media tools. The ensuing discussion highlights where the themes intersect, and draws attention to gaps in the literature wherein further research is required to elucidate the process of networking during job search. Finally, a prominent model from the field of information behaviour theory has been proposed as a framework for conducting further work in this area. By incorporating the three key stages of Wilson’s (1997) general model of information behaviour into future studies (i.e. context of information need, intervening variables, and information seeking behaviour), this paper maintains that a holistic understanding of networking during job search can be attained, which will relate to and extend previous research in the area.

Wilson’s model is currently being utilised as a framework to research the networking behaviour of young jobseekers in Scotland, in an ongoing study funded by the ESRC (grant no. ES/J500136/1) and Skills Development Scotland. Using a mixed methods approach, the study seeks to develop an understanding of networking as a concept during job search based on a collection of qualitative data, as supported by social media tools. Based on this data, a quantitative design will then be implemented to elucidate the networking behaviour of young Scottish jobseekers at a nationwide level, across a range of demographics. It is anticipated that the research will provide a contribution to knowledge in the field of information science investigating networking as a method of information seeking during job search. Additionally, findings from the study are expected to make a practical contribution to Skills Development Scotland’s policy objectives in the careers information and guidance services industry.

Acknowledgements

This paper is part of a wider project funded by Skills Development Scotland and the Economic and Social Research Council (grant no. ES/J500136/1). The authors would like to thank the reviewers for their constructive feedback on the paper.

About the authors

John Mowbray is a doctoral candidate in the Centre for Social Informatics and the Employment Research Institute at Edinburgh Napier University. His research interests include networking as an information behaviour, social media use, and the impact of social networks on employability. He can be contacted at j.mowbray@napier.ac.uk
Hazel Hall is Professor and Director of the Centre for Social Informatics within the School of Computing at Edinburgh Napier University in Scotland. Her research interests include information sharing in online environments, knowledge management, social computing/media, online communities and collaboration, library and information science research, and research impact. She can be contacted at h.hall@napier.ac.uk, and at http://hazelhall.org.
Robert Raeside is a professor of Applied Statistics and is the Director of the Employment Research Institute at Edinburgh Napier University in Scotland. His research interests are all aspects of employment and employability, demographic change and social networks. He can be contacted at r.raeside@napier.ac.uk.
Pete Robertson is a lecturer at the School of Applied Sciences at Edinburgh Napier University, where he leads the career guidance programme. His research interests include employment, career counselling, and support for disadvantaged or unemployed job seekers. He can be contacted at p.robertson@napier.ac.uk