One of the central problems in multilingual sentiment analysis is a significant lack of resources. Thus, sentiment analysis in multiple languages is often presented by transferring knowledge from resource-rich to resource-poor languages, because there are no resources available in other languages. The majority of multilingual sentiment analysis systems use English lexical resources such as SentiWordNet.
Another approach is to use a machine translation system to translate texts in other languages into English: the text is translated from the original language into English, and then English-language resources such as SentiWordNet are employed. Translation systems have various problems, such as sparseness and noise in the data. Often the translation system is not able to translate necessary parts of a text, which can cause serious problems, possibly reducing well-formed sentences to fragments.
For more information regarding the Multilingual Sentiment Analysis, refer to the following link: https://ssix-project.eu/multilingual-sentiment-analysis/
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