Like Pollution

Social networking relies on user contributions for content. One way to generate contributions is the user Like Button or Recommendation, where the user "likes" a piece of content like a site, page, picture, quote, etc. Likes provide users a way to express opinions, and the number of likes and source of likes are used by some to gauge the popularity of a site or the suitability of that site for viewing.
Likes are used to determine the demographic of a site, and can be used in several ways:
* Sites can analyze a user's likes to provide content that is customized to that user.
* Site owners can user like data to improve their site's content to appeal to a certain demographic
Liking only works if users recommend sites genuinely, it is when users begin to recommend sites randomly or without any thought process that the system breaks down. Some users have been known to click on every Like Button they see whereas others Like everything their friends like, which can have viral effects. This Gratuitous Liking has negative effects:
* The demographics of a site are no longer are accurate, and site owners cannot use the the statistics for site improvement
* Too many likes too quickly can look like abuse of the system, and lead to repercussions as in filtering from rankings or negative ratings
* Users with too many likes get removed from like statistics or blocked from sites
Sites with too many gratuitous likes are experiencing "Like Pollution", where the volume and sources of a site's Likes are so out of keeping with the site's purpose and demographic that it appears suspect. This can be through social mechanisms as in like-a-thons, or deliberate abuse of the system as in Likejacking. Deliberate abuse is a form of fraud and can be perpetrated by site owners in order to improve their site popularity, although it can have the reverse effect. Deliberate abuse can also take the form of a Like Pollution Attack, where a third party attempts to damage the reputation of another site by making it appear they are engaging in fraud, or gain a competitive advantage by preventing the use of like statistics for site improvement.
Prevention
As yet there is no way for a site to prevent Like Pollution because of the nature of the recommendation mechanisms, and the security vulnerabilities endemic in social networking mechanisms.
Mitigation
Many sites offer an API mechanism for removing likes, which requires development on the part of a site owner. Algorithms for removing likes would depend on a site's purpose and intended demographic but could be based on removing likes from users who have too many likes in a period of time.

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