Social Algorithm Definition
The word social is currently in vogue, we have social networks, social software, social bookmarking and now social algorithm. Social media is the 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 networks.
Let’s see the examples. Famous social networking sites include Flickr, YouTube, MySpace, Friendster, Wikipedia, Facebook, del.icio.us and Second Life virtual game world. 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 Software.
Social software is the tools that make it possible for people to network. These range from email, mailing lists, RSS, IRC, instant messaging, Napster as 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 newer. Wikis have been around since Ward Cunningham, the father of Wiki, started them, but then they were considered only for geeks, and have become widely accepted only in the last few years. Some programs are documented through wikis, and businesses and educational institutions have begun to use them.
algorithms
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. 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 decisive factor for Google to win the battle of the web. The PageRank algorithm ranks websites using many criteria, including the number of inbound links, each with a weight that is the referring site’s PageRank (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 well sites rank in a search, it affects a lot of things and ultimately a lot of people who earn income from the sites. Therefore, 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. Algorithm abuse has occurred, in one case someone builds websites based on (almost) links with no content, but manages to get high PageRank. These 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 digs 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 current algorithm by 10%.
There are no human players or avatars.
Returning to the definition of a social algorithm as a multi-agent based algorithm, where the agents are people, we believe that this definition should be expanded to include cases where people are substituted by animals or software surrogates. I would consider a simulation of the Digg algorithm, or a simulation of market operations using intelligent agents as social algorithms. So is the ant colony algorithm, which substitutes people for animals. 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 algorithm of evolution 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 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 of life, including economics, relationships, and property, is defined by algorithms.