## 3 Related Studies
They have proposed a systematic step-by-step approach called AdvisorNet to find these stakeholders and elicit their requirements. This approach suggests a social network search to find stakeholders in a target company through a set of advisors that act as intermediates. Additionally, [PERSON] et al. [71] have named social network platforms such as LinkedIn, Twitter and ResearchGate as potential sources for selecting a crowd of experts. They have proposed a nichesourcing approach for analyzing sustainability requirements and as well their dependencies. One of the early phases of the approach is identifying a crowd of experienced contributors with certain domain knowledge suitable for software to participate in the crowdsourced task of eliciting sustainability requirements and their dependencies. Other studies have chosen to select a crowd for crowdsourcing RE tasks based on the domain of interest. [PERSON] et al. [61] have proposed an automated tool called PseudoGravity which can identify an interested crowd on Twitter and engage them in requirement elicitation tasks. The tool is a bot that establishes a presence on Twitter by automatically generating content that attracts a targeted crowd, then engages them in tasks such as requirements elicitation. Furthermore, a study conducted by [PERSON] and [PERSON] [63] designed an approach that can identify and select a suitable interested crowd which is beyond organizational reach such as in social network channels. The approach utilizes a set of keywords in various online channels such as LinkedIn and Facebook and targeted them with persona-based advertisements to find a crowd interested in the SmaWoMo software application. The identified crowd are then invited to collaborate in requirements elicitation for the software application. A persona-based method was employed by [PERSON] et al. [60]. Through their method, a persona builder can be used to develop a persona from the start by specifying the main characteristics or make use of predefined personas or even stored ones that have been previously created. Hence, the crowd members who match the defined persona are selected to engage in requirements elicitation tasks. Moreover, [PERSON] et al. [62] in their study have developed a stakeholder identification model which can split tweets into three classes which are technical, non-technical or general public stakeholders. They have built their models using machine learning techniques on collected tweets about a set of 30 well-known mobile and desktop applications. The discussed studies involve some limitations which we have observed. [PERSON] and [PERSON]'s study [63] proposed an approach for identifying the crowd of stakeholders beyond organizational reach. The drawback is that their approach was conducted in a manual manner by using a selected number of keywords to search for an interested crowd on social network sites. Hence, a separate manual search might be required for each type of software when applying this approach. In addition, the AdvisorNet method proposed by [PERSON] et al. [64] is an unautomated systematic method for performing social media searches, particularly on LinkedIn. Their method requires automation to enhance its scalability. Furthermore, relying solely on spatiotemporal availability of the crowd to discover the domain knowledge they possess, as performed by [7], may not be reliable and accurate enough to infer a crowd's domain knowledge. From another perspective, developing a tool that aims to select a crowd holding specific knowledge of a single domain could call for a tool serving each software application domain as performed by [PERSON] and [PERSON] in their study [5]. They have placed their emphasis on a crowd with expertise in ERP from LinkedIn. The same applies for [61], where they have utilized Twitter to develop a social presence in a targeted crowd's domain of interest using their PseudoGravity tool.