Differences in data pre-processing (tokenization/lemmatization), selection (train/test splits), feature representation (unigram/bigram), pivot selection (MI/frequency), and the binary classification algorithms used to train the final classifier make it difficult to directly compare results published in prior work.
we re-run the original algorithms on the same processed dataset under the same conditions such that any differences reported in Figure 1  ularization coefficients are set to their optimal values on the validation dataset.