Cross-Topic Opinion Mining for Real-Time Human-Computer Interaction

With the recent growth and expansion of the Web 2 0, there has been an important development of new textual genres, such as blogs posts or forum entries, etc. that are employed to share opinions about a topic of interest. To the best of our knowledge, previous approaches focused on corpus annotation mostly concentrated on subjectivity versus objectivity classification and did not annotate emotions on a fine-grained scale. The scheme we propose in this article allows for both coarse and fine-grained annotation boundaries, as well as to distinguish among polarities and a large set of emotion classes We used the annotated elements to train our real-time opinion mining system, which we subsequently employ for the classification of new sentences on a closely related topic - "recycling" We obtain promising results in all the test scenarios, proving, on the one hand, that the corpus is a valid and useful resource, and, on the other hand, that our method used for opinion mining, is adequate