Sentiment Analysis in the News

Recent years have brought a significant growth in the volume of research in sentiment analysis, mostly on highly subjective text types (movie or product reviews). The main difference these texts have with news articles is that their target is clearly defined and unique across the text. Following different annotation efforts and the analysis of the issues encountered, we realised that news opinion mining is different from that of other text types. We identified three subtasks that need to be addressed: 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. Furthermore, we distinguish three different possible views on newspaper articles

• Type: Conference
• Year: 2010
• Where: LREC
• Authors: Alexandra Balahur, Ralf Steinberger, Mijail Alexandrov Kabadjov, Vanni Zavarella, Erik Van der Goot, Matina Halkia, Bruno Pouliquen, Jenya Belyaeva
• Keywords: Education, LREC 2010, Sentiment Analysis, Subjective Text Types, Text Types