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Sentiment classification is significant in everyday life of everyone, in political activities, activities of commodity production, commercial activitives...Finding a solution of classifying emotion has high accuracies and time of classifying being acceptable is challenge for scientists.
There are many different kinds of emotion classification. Today emotion classification is a new research field and hot field. Because there are web contents, people, organizations... more and more which have interested in learning opinion of other people, so they need some automated tools for the emotion analysis and think summaries... One of the main tasks in classification is to identify emotional contents of documents, such as webs, blogs, magazines, comments... may hold negative feelings (negative), positive feelings (positive) or neutral. Negative emotions are emotions which are brought negative factors such as hate, bad, blame, failure, dislike...Positive feelings are emotions which are brought positive factors such as good, like,...Neutral emotions are kind of feelings which do not bring negative factors and positive factors.
In this study, we have classified sentiment of text in Vietnamese by Naive Bayes in Cloudera environment.
Although our testing dataset is relatively small, our model can conduct to classify sentiment for big Vietnamese dataset (millions of Vietnamese texts) in cloudera environment and in parallel environments (including many computers are connected in many different clusters) in general.
The rest of the paper is organized as follows: Section 2 discusses the related works about naïve bayes,.. In Section 3, the data set for classifying sentences in Vietnamese language is presented. Section 4 represents the methodology of our proposed method. The experiment method and experiment results are represented in Section 5. Section 6 is the conclusion of the proposed method.

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