Abstract:

The aim of this paper is to present a sampling method using virtual networks to study "hard-to-reach" populations. In the ambit of social research is still questioned the use of technologies. That is, the existence of representativeness bias and selection bias are obstacles to carry on scientific research on Internet. However, in a global context that tends to move simultaneously between physical and virtual reality, we must consider the possibility of using new sources of information. In this sense, our hypothesis is that the use of social networking sites (Web 2.0) can be effective for the study of "hard-to-reach" / "hard-to-involve" populations. The main advantages are that they can expand the geographical scope and facilitates the identification of individuals with barriers to access. Therefore, the use of virtual networks in non-probabilistic samples can increase the sample size and the representativeness. To test this hypothesis we have designed a virtual method using Facebook to identify Argentinean immigrant's entrepreneurs in Spain (214 cases). The characteristic of this population is that they are administrative invisible in National Statistics as Argentineans because some of them have double nationality (non-EU and EU nationality). The combination of this selection technique with an online questionnaire allowed us to observe that the number of cases detected by Facebook and the virtual response rate is higher than traditional snowball technique (e.g. contact with institutions). Our explanation is that people increase their level of confidence because the researcher shows his personal information (Facebook’s profile) and also participates on their groups of interest (Facebook’s groups). Moreover, the online questionnaires administration allows us to control the quality of the information and avoids duplication of cases.

Keywords:

Web 2.0, snowball sampling, social research methodology.