How others’ ratings affect your judgment.
Are you influenced by the opinions of other people—say, in the comments sections of websites? If your answer is no, are you sure?
A study published in Science and coauthored by Sloan professor Sinan Aral suggests that many people are heavily influenced by the positive opinions other people express online—but are much less swayed by negative opinions posted in the same venues. And certain topics, including politics, are more strongly associated with this “herding” effect than others.
The results come from a five-month experiment conducted on a major news-aggregation website that lets readers vote comments up or down. The researchers randomly assigned an up or down vote to 101,281 newly published comments to see how subsequent ratings would be affected. They found that comments with an initial up vote ultimately received a 25 percent higher average rating from other site users than comments not receiving an initial up vote. But a comment’s overall score was not affected by an initial down vote.
“This herding behavior happens systematically on positive signals of quality and ratings,” says Aral. At the same time, he notes, “people are more skeptical of negative social influence. They’re more likely to ‘correct’ a negative vote and give it a positive vote.”
Stories tagged “politics,” “culture and society,” and “business” generated positive herding, but stories posted tagged “economics,” “IT,” “fun,” and “general news” did not.
Aral warns that political operatives, marketers, or anyone who could profit from an exaggerated appearance of popularity could take advantage of this phenomenon to manipulate online ratings.
“These positive ratings also represent bias and inflation,” he says. “The housing bubble was a spread of positivity, but when it burst, some people lost their savings … Stock bubbles represent a positive herding, and they can be dramatically bad in the wrong context.”
That means we should be more analytical when harnessing collective judgments, Aral suggests. “We have to be careful about the design and analysis of systems that try to aggregate the wisdom of crowds,” he says. “You need solid science under the hood trying to understand exactly how these mechanisms work.”