The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our Fuzzy Believer system presented in this paper is to extract and analyze statements of opinion from newspaper articles. Beliefs are modeled using the fuzzy set theory, applied after Natural Language Processing-based information e...

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean. We model this "non-belief in the Law of Large Numbers" by assuming that a person believes that proportions in any given sample might be determined by a rate different than the true rate. In prediction, a non-believer expects the distribution of signals will have fa...

The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our artificial believer system1 we present in this paper is to extract and analyze opinionated statements from newspaper articles. Beliefs are modeled with a fuzzy-theoretic approach applied after NLP-based information extraction. A...