I have followed your posts for a long time and I cannot believe that in your heart of hearts you actually believe that social media review sites are representative of the total population...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115258/
The linked study is very interesting IMO. They were studying game addiction among World of Warcraft players. Obviously we are not discussing something as serious as addiction but you can make some comparisons between two large online groups of people and the sub-groups involved. I found the methodology and the data to be interesting.
For those that don't want to read the whole study here is the conclusion:
Conclusions
Because of the important differences between the self-selected samples and the randomly selected sample, and despite the acknowledged limitations, the study invites careful consideration of the conclusions made from online self-selected samples and the possibility of an overrepresentation of subgroups of more involved or
more concerned users.
Therefore, it
does not appear possible to draw general epidemiological conclusions from Internet-based self-selection surveys (eg, on the prevalence of game addiction among website users or the general population). However, the studies may be of
high interest to subgroups of users who are more involved in the game and the study purpose. In particular, such studies may allow the linking together of different assessed variables (such as mood, motives, or personality and a given behavior) in the studied sample. This remains important, particularly because of the possible advantages of online studies (eg, large sample sizes, possible access to people who are usually more difficult to reach, access to stigmatized behaviors).
The possible collaboration with webmasters may further improve understanding of the representativeness of self-selected samples by the random selection of the users (ie, contacting users by email to build a random sample as control group) or by comparison of the responders to non-responders regarding general characteristics such as features related to website use or, to some extent, potential biases regarding clinical variables (eg, game addiction).