The social spider optimization (SSO) algorithm is a population based algorithm proposed by Cuevas in
2013[17]. There are two components of a social spider colony.
They are social members and communal web. The social members are divided into male spiderss and femalespiders[8]. Female spider attracts or dislikes other spiders.Male spiders are divided into two types, dominant and non-dominant male spiders. Dominant male spiders will have better fitness than non-dominant spiders.Mating
operation allows the information exchange amongdominant
males and females. A dominant male mates with one or all
females within a specific range to produce offspring.
Each spider is associated with a position, a weight and
vibrations perceived from other spiders. Spider position
represents a solution within the search space. Every spider
receives a weight based on the fitness value of the solution
that is given by it. The communal web transmits
information among the colony members. This information
is encoded as small vibrations that are critical for the
collective coordination of all spiders in the solution
space.The weight and distance of the spider are the factors
that influence vibrations [8].Each single spider in the
swarm defines one solution for text document clustering. A
swarm defines a number of candidate solutions for text
document clustering