We report results of stylometric differences in blogging for gender and age group variation. The results are based on two mutually independent features. The first feature is the use of slang words which is a new concept proposed by us for Stylometric study of bloggers. Slang is a non-dictionary word that has evolved with time due to its frequent and popular usage. For the second feature, we have analysed the variation in average length of sentences across various age groups and gender. These two features are then augmented with previous study results reported in literature for stylometric analysis of age and gender. The combined feature list enhances the accuracy by a remarkable extent in predicting age and gender. These experiments were done on a 20,000 blog corpus. Experimental results show that these features work well in detection of bloggers’ demography. However, gender determination is more accurate than age group detection over a data spread across all ages but the accuracy of age prediction increases if we sample data with remarkable age difference.