In the future, we will work on leveraging parallel sentences and word alignments for other tasks in sentiment analysis, such as building multilingual sentiment lexicons.

termining polarity classes of the parallel sentences .

Particularly, for each pair of parallel sentences U: E U, we generate the words as follows.

class label for unlabeled parallel sentences ) is computed according to the following equations.

The unlabeled parallel sentences

This model use English labeled data and Chinese labeled data to obtain initial parameters for two maximum entropy classifiers (for English documents and Chinese documents), and then conduct EM-iterations to update the parameters to gradually improve the agreement of the two monolingual classifiers on the unlabeled parallel sentences .

When we have 10,000 parallel sentences , the accuracy of CLMM on the two data sets quickly increases to 68.77% and 68.91%, respectively.

They assume parallel sentences in the corpus should have the same sentiment polarity.

The approach uses a small amount of manually annotated article-pairs to train a document-level CRF model for parallel sentence extraction.

This is due to two phenomena: one is that the parallel sentences sometimes contain different amounts of information and one language might use more detail than the other.

We presented a direct semi-CRF tagging model for labeling foreign sentences in parallel sentence pairs, which outperformed projection by more than 10 F—measure points for Bulgarian and Korean.

Here we combine elements of both Wikipedia metadata-based approaches and projection-based approaches, making use of parallel sentences extracted from Wikipedia.