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INTERNET-BASED SURVEYS 237
Witte et al. 1999; Hewson et al.2003),withresults
showing that samples taken from users and nonusers
of the Internet did not differ in terms of
income, education, sexual orientation, marital
status, ethnicity and religious belief. However,
they did differ in terms of age, with the Internet
samples containing a wider age range than non-
Internet samples, and in terms of sex, with the
Internet samples containing more males. Hewson
et al. (2003)reportoverallagreaterdiversityof
sample characteristics in Internet-based samples,
though they caution that this is inconclusive,
and that the sample characteristics of Internet
samples, like non-Internet samples, depend on
the sampling strategy used. Stewart and Yalonis
(2001) suggest that one can overcome the possible
bias in sampling through simple stratification
techniques.
A major problem in sampling for Internet
surveys is estimating the size and nature of the
population from which the sample is drawn: a key
feature of sampling strategy. Researchers have no
clear knowledge of the population characteristics
or size, and indeed the same applies to the sample.
The number of Internet users is not a simple
function of the number of computers or the number
of servers (e.g. many users can employ a single
computer or server), though at the time of writing,
a figure of over 500 million users has been suggested
(Hewson et al. 2003:36).Further,itisdifficultto
know how many or what kind of people saw a
particular survey on a web site (e.g. more males
than females), i.e. the sampling frame is unclear.
Moreover, certain sectors of the population may
still be excluded from the Internet, for example:
those not wishing to, or unable to (e.g. because of
cost or availability), gain access to the Internet.
The situation is changing rapidly. In 1997
it was reported (Coomber 1997) that Internet
users tended to be white, relatively affluent and
relatively well-educated males from the developed
world; more recent studies (e.g. Hewson et al.
2003) suggest that the Internet is attracting a
much more diverse population that is closer to the
general population.
There are further concerns about the sampling
on Internet-based surveys. Internet-based
surveys are based largely on volunteer samples,
obtained through general posting on the web
(e.g. an advertisement giving details and directing
volunteers to a site for further information),
or, more popular in the social
sciences, through announcements to specific
newsgroups and interest groups on the web,
e.g. contacting user groups (e.g. through the
SchoolNet). Lists of different kinds of user
(USENET) groups, newsgroups and electronic
discussion groups (e.g. Listservs) can be found
on the web. Several search engines exist
that seek and return web mailing lists,
such as: http://www.liszt.com (categorized by
subject); Catalist (the official catalogue of
LISTSERV lists at http://www.lsoft.com/catalist.
html); Mailbase (http://www.mailbase.ac.uk),
which is a major collection of over 2,500 lists concerning
the academic community in the United
Kingdom; and Meta-List.net (http://www.metalist.net),
which searches a database of nearly a
quarter of a million mailing lists. Dochartaigh
(2002) provides useful material on web searching
for educational and social researchers.
The issue here is that the researcher is
using non-probability, volunteer sampling, and
this may decrease the generalizability of the
findings (though, of course, this may be no
more a problem on Internet-based surveys than
on other surveys). Opportunity samples (e.g. of
undergraduate or postgraduate students using the
web, or of particular groups) may restrict the
generalizability of the research, but this may be
no more than in conventional research, and may
not be a problem so long as it is acknowledged.
The issue of volunteer samples runs deeper, for
volunteers may differ from non-volunteers in terms
of personality (e.g. they may be more extravert or
concerned for self-actualization: Bargh et al. 2002)
and may self-select themselves into, or out of, a
survey, again restricting the generalizability of the
results.
One method to try to overcome the problem
of volunteer bias is to strive for extremely large
samples, or to record the number of hits on
a web site, though these are crude indices.
Another method of securing the participation of
Chapter 10