Social Algorithm Definition
The word social is currently in fashion, we have social networks, social software, social bookmarking and now social algorithm. Social media is activity, social software is the tools that make social media possible, but what is a social algorithm?
Next, an attempt is made to define what a social algorithm is.
Social media.
Let’s see the examples. Popular social networking sites include Flickr, YouTube, MySpace, Friendster, Wikipedia, Facebook, del.icio.us, 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.).
SocialSoftware.
Social software are the tools that make it possible for people to network. These range from email, mailing lists, RSS, IRC, instant messaging, Napster to P2P, blogs, wikis, AJAX, Web 2, etc. Its characteristic is that the network must be interactive and 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 Ward Cunningham, the father of the Wiki, started them, but they were considered just for geeks then, and have only become widely accepted in recent years. Some programs are documented using wikis, and companies and educational institutions have started using them.
algorithms
So what is a social algorithm? An algorithm is like a recipe or a computer program with step-by-step instructions to execute 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 don’t need to be, as shown in cooking recipes, logical unification algorithm, string matching, facial recognition, etc.
Agent based.
Social algorithms differ from general algorithms in that they involve agents, and the algorithm is the result of the interaction of the agents. The ant colony algorithm is an example, with ants as agents, and is used to solve some problem, such as the shortest path or the traveling salesman 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 weighing 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 publications.
is given by
PR(A) = (1-d) + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))
where
PR(A) is the PageRank of page A,
PR(Ti) is the PageRank of the pages Ti that link to page A,
C(Ti) is the number of outgoing links on page Ti and
d is a damping factor that can be set between 0 and 1.
Since PageRank defines how sites rank in a search, it affects a lot of things and ultimately a lot of people who make money from the sites. Therefore, the people, who are the agents here, try to modify the parameters of your 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 also evolving.
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.
Digg.com is a social bookmarking site, the original suggestion gets 1 digg, and people can dig back if they like the suggestion, or dig it up if they don’t. The number of excavations indicates the popularity of the suggestion. This system will favor groups of people who collaborate to seek suggestions from each other.
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 current algorithm by 10%.
There are no human players or avatars.
Going back to the definition of a social algorithm as an algorithm based on multiple agents, where the agents are people, we believe that this definition should be extended to include cases where people are replaced by animals or software substitutes. I would consider a simulation of the Digg algorithm, or a simulation of market trading 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 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 of 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 can be iterated and played on 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 of life, including the economy, relationships, and property, is defined by algorithms.