Li

Text normalization and part-of-speech (POS) tagging for social media data have been investigated recently, however, prior work has treated them separately. In this paper, we propose a joint Viterbi decoding process to determine each token's POS tag and non-standard token's correct form at the same time. In order to evaluate our approach, we create two new data sets with POS tag labels and non-standard tokens' correct forms. This is the first data set with such annotation.