Digital Marketing

Definition of social algorithm

The word social is currently in fashion, we have social networks, social software, social bookmarking and now social algorithm. Social networks are the activity, social software are the tools that make social networks possible, but what is a social algorithm?

The following is an attempt to define what a social algorithm is.

Social networks.

Let’s look at the examples. Famous social networking sites include Flickr, YouTube, MySpace, Friendster, Wikipedia, Facebook,, and the virtual gaming world of Second Life. Flagging and tagging are considered social media activities. The purpose of the network is for people to meet, collaborate, or simply share something (photos, music, movies, information, etc.).

Social programs.

Social software are the tools that make it possible for people to network. These range from email, mailing lists, RSS, IRC, instant messaging, Napster like P2P, blogs, wikis, AJAX, Web 2, etc. Its characteristic is that the network must be interactive and from the bottom up (users provide content). This software used to be called group-ware. Some of these programs are quite old, but others, like blogs, are more recent. Wikis have been around since Wiki’s father Ward Cunningham started them, but they were considered for geeks only then, and have been widely accepted only in recent years. Some programs are documented through wikis, and companies and educational institutions have started using them.


So what is a social algorithm? An algorithm is like a cooking recipe or a computer program with step-by-step instructions for executing a procedure. Algorithms are expressed in pseudocode, are easy for people to understand, and are more abstract than computer programs. The programs are said to implement some algorithm, being a machine-level translation of the pseudocode.

Although most algorithms are numeric, they do not need to be, as shown in recipes, logical unification algorithm, string matching, facial recognition, etc.


Social algorithms differ from general algorithms in that they involve agents, and the algorithm is the result of the interaction of agents. The ant colony algorithm is an example, with ants as agents, and it is used to solve some problem, such as the shortest path or the peddler problem. Social algorithms can be used for distributed problem solving like the ant colony algorithm, but it is not necessary.

Google’s PageRank algorithm is said to be the deciding factor for Google to win the battle of the web. The PageRank algorithm ranks websites using many criteria, including the number of incoming links, each with a weight that is the PageRank of the referring site (the algorithm is recursive and near real time).

To get an idea of ​​the algorithm, here is a description:

The original PageRank algorithm was described by Lawrence Page and Sergey Brin in various posts.

is given by

PR (A) = (1-d) + d (PR (T1) / C (T1) + … + PR (Tn) / C (Tn))


PR (A) is the PageRank of page A,

PR (Ti) is the PageRank of the Ti pages that link to page A,

C (Ti) is the number of outbound links on the Ti page and

d is a damping factor that can be set between 0 and 1.

Since PageRank defines the ranking of sites in a search, it affects many things and ultimately many people who earn income from the sites. Therefore, the people, who are the agents here, try to modify the parameters of their site to increase their ranks. This is commonly known as SEO – Search Engine Optimization.

This is an example where the algorithm provides rules for the social network and in doing so modifies the behavior or actions of the agents. There has been abuse of the algorithm, in one case someone builds websites based on (almost) links with no content, but manages to get a high PageRank. Such anomalies are likely to be resolved as the PageRank algorithm is evolving as well.

Internet auctions and reverse auctions, such as those provided by EBay, are also algorithms that provide the rules of the game, where we are the players. is a social bookmarking site, the original suggestion gets 1 digg, and people can go back to digging if they like the suggestion, or dig it up if they don’t like it. The number of excavations indicates the popularity of the suggestion. This system will favor groups of people who collaborate to seek suggestions among themselves.

We see that social algorithms have weaknesses, often exploited by certain people. Hence the need to improve social algorithms.

Netflix is ​​a famous case, they have offered a million dollars to anyone who can improve the accuracy of their existing algorithm by 10%.

Non-human players and avatars.

Returning to the definition of social algorithm as a multi-agent based algorithm, where the agents are people, we believe that this definition should be broadened to include cases where people are replaced by animals or software surrogates. I would consider a simulation of the Digg algorithm, or a simulation of market operations using intelligent agents such as social algorithms. So is the ant colony algorithm, which substitutes animals for people. Also swarms, flocks, etc.

Cellular automata are a borderline case, they are agent-based, but are often used to simulate physical and chemical processes. If it were used to mimic human activity, it would be a social algorithm.

The evolution algorithm as an abstraction from the Darwinian process is also a social algorithm.

Genetic algorithms and their variations are included here.

Evolutionary game theory.

The field of social algorithms intersects with evolutionary game theory. Game theory studies the strategies used by agents, for example, in trading, auctions, marketing, voting, etc. The Prisoner’s Dilemma sets up a game for 2 prisoners, but it can be iterated and played in a population, which is then turned into a social algorithm.

If you’ve ever played Second Life, you know how complicated social algorithms can be. In the virtual world, all life, including the economy, relationships, and property, is defined by algorithms.

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