## 3 Results for the Research Questions
### RQ2: What Are the Expertise Sources Used for Experts Finding Systems?
#### 3.3.1 RQ3a: What Are the Differences between Expertise Retrieval and Expertise Seeking?
On the other hand, further research was carried out in expertise seeking for determining the techniques used when seeking an expert for a particular task. This addressed the issue of associating humans to an expertise field using a human-centered viewpoint. Furthermore, reference [27] also stated that a majority of the expertise seeking studies focused on determining the manner in which a user search for an expert and seeks the relevant expertise for the specific activity. These studies helped in developing models that can identify the factors that influenced the expert finding. Table 5 summarizes these differences. 3.2 What Are the Contextual Factors and Theories That Have Been Integrated with Expert Finding Systems? Most current expert finding systems retrieved people like documents [4; 38], whereas people are unlike documents and are not directly represented as retrievable elements. The representation of experts based on the strength of relationships among a topic and an expert is called representation based on content-based factors [1; 25; 73]. A challenge in content-based expert finding systems is that the systems need to go beyond document retrieval, as they are required to retrieve entities (experts) instead of documents. According to social capital theory [93], the process of expertise exchange is a social process. For example, the authors in reference [94] found that awareness of \"who knows what\" is not enough to find the actual access to expertise, and it needs to be supported by strong relationships. Also, the authors of references [95; 96] found that employees who have expertise about a particular problem may be unwilling to share their expertise with people with whom they do not share positive affective relations. Thus, it is clear that, besides the degree of expertise extracted from documents, there are other important factors that should be taken into account for expert finding systems development, such as contextual factors [1; 25; 27; 39; 71]. The contextual factors are described as factors that influence the manner in which people find and select the experts and can be beyond the various content-based factors [1; 27]. The contextual factors included in the information retrieval (IR) studies have highlighted the concept of the context in the field of information science. Hence, context refers to the term that is maximally 'often used', minimally 'often defined', and 'when defined so variously' [97]. The authors in reference [98] stated that context is not an individual factor but a combination of different factors consisting of several elements or aspects. Thus, context can be used as an umbrella term for describing various factors that could simplify things for a specific purpose. The authors in reference [99] described the major concepts of the contexts used in the IR that were investigated by the 2005 SIGIR workshop, i.e., IR in context (IRiX). The researchers attempted to answer the question, which features of context were important to the IR? This workshop led to the determination of different dimensions for the context (i.e., contextual factors), which were (1) task-related factors, like the task level, task type, and goal; (2) seeker-related factors like behaviour, \begin{table}
\begin{tabular}{c c c c} \hline \hline
**The Concept** & **Definition** & **Research Area** & \begin{tabular}{c} **Sociotechnical** \\ **Perspective** \\ \end{tabular} \\ \hline Expertise Retrieval & \begin{tabular}{c} Developing systems that enable expertise \\ seekers to identify and select experts in a \\ particular area. \\ Developing models to identify the factors \\ \end{tabular} & \
\begin{tabular}{c} information \\ retrieval \\ knowledge \\ management \\ \end{tabular} &
\begin{tabular}{c} system-centered \\ perspective \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The differences between expertise retrieval and seeking.