Paper: Opinion Mining in Newspaper Articles by Entropy-Based Word Connections

ACL ID D13-1188
Title Opinion Mining in Newspaper Articles by Entropy-Based Word Connections
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

A very valuable piece of information in news- paper articles is the tonality of extracted state- ments. For the analysis of tonality of newspa- per articles either a big human effort is needed, when it is carried out by media analysts, or an automated approach which has to be as accu- rate as possible for a Media Response Anal- ysis (MRA). To this end, we will compare several state-of-the-art approaches for Opin- ion Mining in newspaper articles in this pa- per. Furthermore, we will introduce a new technique to extract entropy-based word con- nections which identifies the word combina- tions which create a tonality. In the evalua- tion, we use two different corpora consisting of news articles, by which we show that the new approach achieves better results than the four state-of-the-art met...