1. A method for visually identifying spam in a text-based dataset, comprising the steps of: calculating a correlation K ij between combinations of words; concatenating lemmas that have a correlation K ij above a predetermined level into an artificial word; recalculating a correlation K ij between combinations of words in an expanded dataset comprised of said text-based dataset and artificial words obtained by concatenation; repeating the steps above for N lemmas; and using a force directed graph to visually display the results obtained above, wherein each node in the graph has N outgoing partners, and the N co-words with the highest value of K ij above a minimum value are connected together.