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Article analysis:

The article provides an in-depth discussion on the sentiment classification method for Chinese web commentary information by combining pattern matching techniques and machine learning methods. The article is well-structured and provides detailed explanations on the different granularity of emotional orientation analysis such as tendentious analysis in words, sentences and documents. It also presents various methods such as related righteousness field, semantic tree level, modularity optimization etc., to analyze the emotional orientation of words, sentences and documents.

The trustworthiness and reliability of this article can be assessed by looking at its sources of information. The author has provided references from credible sources such as CNNIC (China Internet Network Information Center), GI (General Inquirer), WordNet etc., which adds to the credibility of the article. Furthermore, the author has provided equations to explain his points which makes it easier for readers to understand his arguments better.

However there are some potential biases that need to be considered when assessing this article’s trustworthiness and reliability. Firstly, there is no mention of any counterarguments or alternative views which could have been explored further in order to provide a more balanced view on the topic discussed in this paper. Secondly, there is no mention of any possible risks associated with using this sentiment classification method which should have been noted in order to provide a more comprehensive overview on this topic. Lastly, there is no discussion on how reliable these methods are when applied in real-world scenarios which could have been explored further in order to provide a more complete understanding on this topic.