Snowball sampling is a method where initial participants are used to help researchers find other potential participants who meet eligibility criteria for a study. Researchers first contact stakeholders and ask them for referrals to others, expanding the sample size in a snowball-like fashion. This method is useful when the target population is hard to locate directly, as participants can use their social networks to refer researchers to others. Some advantages are that it allows access to hidden populations and requires less time and resources than other methods. However, it also lacks randomness and researchers have little control over the sampling process.

1. Statistics & Probability
Snowball Sampling

2. What is snowball sampling?
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. The term
"snowball sampling" reflects an analogy to a snowball increasing in size as it rolls
downhill.
Method:
1. Draft a participation program (likely to be subject to change, but indicative).
2. Approach stakeholders and ask for contacts.
3. Gain contacts and ask them to participate.
4. Community issues groups may emerge that can be included in the participation
program.
5. Continue the snowballing with contacts to gain more stakeholders if necessary.
6. Ensure a diversity of contacts by widening the profile of persons involved in the
snowballing exercise.
Applications of snowball sampling:
The participants are likely to know others who share the characteristics that make them
eligible for inclusion in the study.
Snowball sampling is quite suitable to use when members
of a population are hidden and difficult to locate (e.g. samples of the homeless
or users of illegal drugs) and these members are closely connected (e.g.
organized crime, sharing similar interests, involvement in the same groups that
are relevant to the project at hand)
Snowball Sampling

3.  Application field:
1. Social computing:
Snowball sampling can be perceived as an evaluation
sampling in the social computing field. For example, in the interview phase,
snowball sampling can be used to reach hard-to-reach populations.
Participants or informants with whom contact has already been made can use
their social networks to refer the researcher to other people who could
potentially participate in or contribute to the study.
2. Conflict environment:
It has been observed that conducting research in
conflict environment is challenging due to mistrust and suspicion. A conflict
environment, where people or groups thinks their needs and goal are
contradictory to the goals and or needs of other people or group. These
conflicts among groups or people include the differences to claim the area of
territory, resources, trade, civil and religious rights that cause considerable
misunderstanding and heighten the disagreements that lead to an environment
with lack of trust and suspicion. In conflict environment, the entire population
is marginalized to some extent rather than a specific group of people and
makes it very hard for investigators to reach the study subjects to conduct the
research. For example, a threatening political environment under authoritarian
regime creates obstacles for the investigators to conduct the research.
Snowball sampling has demonstrated as a second best method in conducting
research in conflict environments like, in the context of the Israel and Arab
Conflict. Snowball sampling allows the investigators to approach the
marginalized population at cognitive and emotional level and enroll them in
study. Snowball sampling address the conditions of lack of trust that arises
due to uncertainty about the future through trace-linking methodology.
3. Expert information collection:
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. Every
involved expert can suggest another expert who they may know could offer
more information.

4. Advantages and Disadvantages
Advantages:
I. Locate hidden populations :
It is possible for the surveyors to include people in the
survey that they would not have known but, through the use of social network
.
II. Locating people of a specific population:
There are no lists or other obvious sources for locating
members of the population (e.g. the homeless, users of illegal drugs). The
investigators use previous contact and communication with subjects then, the
investigators are able to gain access and cooperation from new subjects.The key
in gaining access and documenting the cooperation of subjects is trust. This is
achieved that investigators act in good faith and establish good working
relationship with the subjects.
III.Methodology:
As subjects are used to locate the hidden population, the
researcher invests less money and time in sampling. Snowball sampling method
does not require complex planning and the staffing required is considerably
smaller in comparison to other sampling methods.
Snowball Sampling can use in
both alternative or complementary research methodology. As an alternative
methodology, when other research methods can not be employed, due to
challenging circumstancing and when random sampling is not possible. As
complementary methodology with other research methods to boost the quality
and efficiency of research conduct and to minimize the sampling bias like quota
sampling.
Disadvantages:
1. Community bias:
The first participants will have a strong impact on the sample. Snowball
sampling is inexact and can produce varied and inaccurate results. The method is heavily
reliant on the skill of the individual conducting the actual sampling, and that individual's
ability to vertically network and find an appropriate sample. To be successful requires

5. previous contacts within the target areas, and the ability to keep the information flow going
throughout the target group.
2. Non-random:
Snowball sampling contravenes many of the assumptions supporting
conventional notions of random selection and representativeness. However, social
systems are beyond researchers' ability to recruit randomly. Snowball sampling is
inevitable in social systems.
3. Unknown sampling population size:
There is no way to know the total size of the overall population.
4. Anchoring:
Another disadvantage of snowball sampling is the lack of definite
knowledge as to whether or not the sample is an accurate reading of the target population.
By targeting only a few select people, it is not always indicative of the actual trends
within the result group. Identifying the appropriate person to conduct the sampling, as
well as locating the correct targets is a time-consuming process such that the benefits
only slightly outweigh the costs.
5. Lack of control over sampling method:
As the subjects locate the hidden population,
the research has very little control over the sampling method, which becomes mainly
dependent on the original and subsequent subjects, who may add to the known sampling
pool using a method outside of the researcher's control.