SAAIP 2012 - 2nd Workshop on Sentiment Analysis where AI meets Psychology

In recent times, research activities in the areas of Opinion, Sentiment and/or Emotion in natural language texts and other media are gaining ground under the umbrella of subjectivity analysis and affect computing. The reason may be the huge amount of available text data in the Social Web in the forms of news, reviews, blogs, chats and even twitter. Though Sentiment analysis from natural language text is a multifaceted and multidisciplinary problem, in general, the term “sentiment” is used in reference to the automatic analysis of evaluative text. Research efforts are being carried out for identification of positive or negative polarity of evaluative text and for development of devices that recognize human affect, display and model emotions from textual contents. Techniques from Artificial Intelligence play important roles in these tasks.
The main four aspects of the sentiment analysis problem are Object identification, Feature extraction, Orientation classification and Integration. The existing reported solutions or available systems are still far from being perfect or fail to meet the satisfaction level of the end users. The main issue may be that there are many conceptual rules that govern sentiment and there are even more clues (possibly unlimited) that can convey these concepts from realization to verbalization of a human being. Human psychology may provide the unrevealed clues and govern the sentiment realization. The important issues that need attention include how various psychological phenomena can be explained in computational terms and which AI concepts and computer modeling methodologies will prove most useful from the psychologist's point of view.
In addition to Question Answering or Information Retrieval systems, Topic-sentiment analysis is being applied as a new research method for mass opinion estimation (e.g., reliability, validity, sample bias), psychiatric treatment, corporate reputation measurement, political orientation categorization, stock market prediction, customer preference or public opinion study and so on.