Rethinking Sentiment Analysis in the News: from Theory to Practice and back

Most sentiment analysis work has been carried out on highly subjective text types where the target is clearly defined and unique across the text (movie or product reviews). However, when applying sentiment analysis to the news domain, it is necessary to clearly define the scope of the task, in a more specific manner than it has been done in the field so far. The main tasks we identified for news opinion mining are: definition of the target; separation of the good and bad news content from the good and bad sentiment expressed on the target; and analysis of clearly marked opinion that is expressed explicitly, not needing interpretation or the use of world knowledge. It is furthermore important to distinguish three different possible views on newspaper articles – author, reader and text. These have to be addressed differently at the time of analysing sentiment, especially the case of author intention and reader interpretation, where specific profiles must be defined if the proper sentiment is to be extracted.