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Báo cáo khoa học: "Extracting Semantic Orientations of Words using Spin Model"

We propose a method for extracting semantic orientations of words: desirable or undesirable. Regarding semantic orientations as spins of electrons, we use the mean field approximation to compute the approximate probability function of the system instead of the intractable actual probability function. We also propose a criterion for parameter selection on the basis of magnetization. Given only a small number of seed words, the proposed method extracts semantic orientations with high accuracy in the experiments on English lexicon. The result is comparable to the best value ever reported. . | Extracting Semantic Orientations of Words using Spin Model Hiroya Takamura Takashi Inui Manabu Okumura Precision and Intelligence Laboratory Tokyo Institute of Technology 4259 Nagatsuta Midori-ku Yokohama 226-8503 Japan takamura oku @pi.titech.ac.jp tinui@lr.pi.titech.ac.jp Abstract We propose a method for extracting semantic orientations of words desirable or undesirable. Regarding semantic orientations as spins of electrons we use the mean field approximation to compute the approximate probability function of the system instead of the intractable actual probability function. We also propose a criterion for parameter selection on the basis of magnetization. Given only a small number of seed words the proposed method extracts semantic orientations with high accuracy in the experiments on English lexicon. The result is comparable to the best value ever reported. 1 Introduction Identification of emotions including opinions and attitudes in text is an important task which has a variety of possible applications. For example we can efficiently collect opinions on a new product from the internet if opinions in bulletin boards are automatically identified. We will also be able to grasp people s attitudes in questionnaire without actually reading all the responds. An important resource in realizing such identification tasks is a list of words with semantic orientation positive or negative desirable or undesirable . Frequent appearance of positive words in a document implies that the writer of the document would have a positive attitude on the topic. The goal of this paper is to propose a method for automatically creating such a word list from glosses i.e. definition or explanation sentences in a dictionary as well as from a thesaurus and a corpus. For this purpose we use spin model which is a model for a set of electrons with spins. Just as each electron has a direction of spin up or down each word has a semantic orientation positive or negative . We therefore regard words