Feature selection is used in many application areas relevant to expert and intelligent systems, such as machine learning, data mining, cheminformatics and natural language processing. In this study we propose methods for feature selection and features analysis based on Support Vector Machines (SVM) with linear kernels. We explore how these techniques can be used to obtain some interesting information for further exploration of text data. The results provide satisfactory observations which may lead to progress in feature selection field.