# Sentiment Analysis In Language

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Preparation of data - including basic preprocessing steps like removing the markup tags and content which is not-textual, as well as unnecessary data, such as dates of the texts and names of the authors. \item Text analysis - the analysis of text linguistic features, usually during this step POS tagging and negation tagging are conducted. \item Sentiment classification itself and results of this classification. \end{enumerate}
Concerning the sentence-level, \citet{27} formulate the sentence-level sentiment classification task as a \lq\lq sequence labelling problem\rq\rq. The data used by their model are sentence-segmented documents divided into sentences annotated with sentence-level sentiment labels (positive, negative or neutral). \\