Sentence-Level Polarity Detection in a Computer Corpus

The paper presents a preliminary research on possible relations between the syntactic structure and the polarity of a Czech sentence by means of the so-called sentiment analysis of a computer corpus. The main goal of sentiment analysis is the detection of a positive or negative polarity, or neutrality of a sentence (or, more broadly, a text). Most often this process takes place by looking for the polarity items, i.e. words or phrases inherently bearing positive or negative values. These words (phrases) are collected in the subjectivity lexicons and implemented into a computer corpus. However, when using sentences as the basic units to which sentiment analysis is applied, it is always important to look at their semantic and morphological analysis, since polarity items may be influenced by their morphological context. It is expected that some syntactic (and hypersyntactic) relations are useful for the identification of sentence polarity, such as negation, discourse relations or the level of embeddedness of the polarity item in the structure. Thus, we will propose such an analysis for a convenient source of data, the richly annotated Prague Dependency Treebank.