Snowball sampling uses a small pool of initial informants to nominate, through their social networks, other participants who meet the eligibility criteria and could potentially contribute to a specific study.
These conflicts among people or groups might include claims to territory, resources, trade, civil and religious rights that cause considerable misunderstanding and heighten disagreements, leading to an environment with lack of trust and suspicion.
In a conflict environment, the entire population (rather than a specific group of people) is marginalized to some extent, which makes it hard for investigators to reach potential participants for their research.
Snowball sampling addresses the conditions of lack of trust that arises due to uncertainty about the future through trace-linking methodology.
[11] Snowball sampling can be used to identify experts in a certain field such as medicine, manufacturing processes, or customer relation methods, and gather professional and valuable knowledge.
For instance, 3M called in specialists from all fields that related to how a surgical drape could be applied to the body using snowball sampling.
Exclusion from majority society or fear of exposure or of shaming makes it difficult to contact participants through usual means.
Virtual snowball sampling technique was used in order to find participants for the study of a minority group – Argentinian entrepreneurs living in Spain.
Spanish national statistics classifies them as European citizens only and there is no information about the place of birth tied to the profiles of entrepreneurs in Spain either.
The use of virtual networks in this example of hard to reach population, increased the number of participating subjects and as a consequence, improved the representativeness of results of the study.
[19] Snowball sampling is a recruitment method that employs research into participants' social networks to access specific populations.
Snowball sampling is often used because the population under investigation is hard to approachable either due to low numbers of potential participants or the sensitivity of the topic.
To help mitigate these risks, it is important to not rely on any one single method of sampling to gather data about a target sector.