The Snow-Balling Effect of Likes, Ups and Positive Votes

Facebook describes the 'Like Button" as a way for social media users to give positive feedback, to provide connection with sites they care about and recommend to their friends and associates.

Some websites also include a dislike button, so a user can provide a vote against the Web content. There are concerns that these voting system are abused. It affects the way many people choose what to open and view when exploring pages or sites.

Various theories have also been raised about whether or not the votes of a user are influenced by the previous votes. The concept of following the crowd is often called 'snow-balling', because a site that gets some initial likes can get more and more like a ball of snow rolling down a hill.

This article explores some recent research on how previous voting patterns (accumulated likes and dislike scores) can have a conditioning effect on future votes.

This opens up a new way in which the likes and dislikes can be gamed by sowing seeds for the crowd to follow.

It explores the how crowd-following affects voting patterns.

Crowd-following affects accumulated 'likes' on Internet pages. An initial seed of 'likes' can snow ball to a crowd - a flock of likes
Crowd-following affects accumulated 'likes' on Internet pages. An initial seed of 'likes' can snow ball to a crowd - a flock of likes. Source: Public Domain
Popularity has always been bought and swayed in various ways
Popularity has always been bought and swayed in various ways. Source: Public Domain
Family popularity used to be al the go
Family popularity used to be al the go. Source: Public Domain
Some people will always be popular!
Some people will always be popular! Source: Public Domain

Effect of Crowd-Following Behavior on Likes and Dislikes Voting patterns

A recent study on ‘liking’ and ‘disliking’ on the Internet is very revealing.

The researchers were interested whether something is popular and gets many ‘likes’ because it is actually good, or whether there is a crowd-following reaction to add more likes when it is showing signs of being popular.

The researchers manipulated the ‘likes’ on the comments on an unnamed website over a period of 5 months. 

Immediately after a new comment was made the software randomly assigned it an arbitrary ‘like’ or ‘dislike’ it was given an arbitrary up or down vote. 

For a control group of comments no changes were made. 

Most readers tend to make ‘likes’ rather than ‘dislikes’ and so a similar bias was applied to the fake ‘likes’ so that they outnumbered ‘dislikes’ by 2:1.

The study found that for 'likes':


These results were very significant and showed a strong crowd-following or snow-balling behavior in social media

The results for comments that were assigned a fake ‘dislike’ were:

This research has profound implications for social media:

How much are your 'like' and 'dislike' votes influenced by previous vote scores?