Social influence bias

However, the composition of the term "social influence bias" requires critical examination to understand the way that it affects individuals' and groups' lives.

[7] This phenomenon was first described in a paper written by Lev Muchnik,[8] Sinan Aral[9] and Sean J. Taylor[10] in 2014,[11] then the question was revisited by Cicognani et al., whose experiment reinforced Munchnik's and his co-authors' results.

As on many such sites, preceding opinions are visible to a new reviewer, he or she can be heavily influenced by the antecedent evaluations in his or her decision about the certain product, service or online content.

[13] This form of herding behavior inspired Muchnik, Aral and Taylor to conduct their experiment on influence in social contexts.

The study lasted for 5 months, the authors randomly assigned 101 281 comments to one of the following treatment groups: up-treated (4049), down-treated (1942), or control (the proportions reflect the observed ratio of up-and down-votes.

Positively manipulated comments did receive higher ratings at all parts of the distribution, which means that they were also more likely to collect extremely high scores.

The community performed a correction which neutralized the negative treatment and resulted non-different final mean ratings from the control group.

The observed positive herding effect was present in the "politics," "culture and society," and "business" subreddits, but was not applicable for "economics," "IT," "fun," and "general news".

Cicognani, Figini and Magnani came to similar conclusions after their experiment conducted on a tourism services website: positive preceding ratings influenced raters' behavior more than mediocre ones.

The bandwagon effect, a subgroup of social influence bias, means that you are drawn to and are more likely to make a decision in order to conform to a group that is making that same decision.
Effect of manipulation on voting behaviour. A: probabilities to up-vote. B: probabilities to down-vote. C: Mean final scores (number of up-votes minus number of down-votes) of the manipulated and control group comments inferred from Bayesian linear regression, 95% confidence intervals shown. [ 11 ]
Mean final scores of positively manipulated and control group comments as the results of Bayesian linear regression (95% confidence interval shown). [ 11 ]