Social touch plays an important role not only in human communication but also in human-robot interaction. We here report results from an ongoing study on affective human-robot interaction. In our previous research, touch type is shown to be informative for communicated emotion. Here, a soft matrix array sensor is used to capture the tactile interaction between human and robot and a method based on PCA and kNN is applied in the experiment to classify different touch types, constituting a pre-stage to recognizing emotional tactile interaction. Results show an average recognition rate for classified touch type of 71%, with a large variability between different types of touch. Results are discussed in relation to affective HRI and social robotics.