Predicting the Semantic Orientation of Adjectives

Predicting the Semantic Orientation of Adjectives Vasileios Hatzivassiloglou and Kathleen R. McKeown Department of Computer Science 450 Computer Science Building Columbia University New York, N.Y. 10027, USA {vh, kathy)©cs, columbia, edu Abstract We identify and validate from a large cor- pus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev- ing 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many ad- jectives, a clustering algorithm separates the adjectives into groups of different orien- tations, and finally, adjectives are labeled positive or negative. Evaluations on real data and simulation experiments indicate high levels of performance: classification precision is more than 90% for adjectives that occur in a modest number of conjunc- tions in the corpus. 1 Introduction The semantic orientation or polarity of a word indi- cates the direction the word deviates from the norm for its semantic group or lezical field (Lehrer, 1974). It also constrains the word's usage in the language (Lyons, 1977), due to its evaluative characteristics (Battistella, 1990). For example, some nearly syn- onymous words differ in orientation because one im- plies desirability and the other does not (e.g., sim- ple versus simplisfic). In linguistic constructs such as conjunctions, which impose constraints on the se- mantic orientation of their arguments (Anscombre and Ducrot, 1983; Elhadad and McKeown, 1990), the choices of arguments and connective are mutu- ally constrained, as illustrated by: The tax proposal was simple and well-received } simplistic but well-received *simplistic and well-received by the public. In addition, almost all antonyms have different se- mantic orientations3 If we know that two words relate to the same property (for example, members of the same scalar group such as hot and cold) but have different orientations, we can usually infer that they are antonyms. Given that semantically similar words can be identified automatically on the basis of distributional properties and linguistic cues (Brown et al., 1992; Pereira et al., 1993; Hatzivassiloglou and McKeown, 1993), identifying the semantic orienta- tion of words would allow a system to further refine the retrieved semantic similarity relationships, ex- tracting antonyms. Unfortunately, dictionaries and similar sources (theusari, WordNet (Miller et al., 1990)) do not in- clude semantic orientation information. 2 Explicit links between antonyms and synonyms may also be lacking, particularly when they depend on the do- main of discourse; for example, the opposition bear- bull appears only in stock market reports, where the two words take specialized meanings. In this paper, we present and evaluate a method that automatically retrieves semantic orientation in- formation using indirect information collected from a large corpus. Because the method relies on the cor- pus, it extracts domain-dependent information and automatically adapts to a new domain when the cor- pus is changed. Our method achieves high preci- sion (more than 90%), and, while our focus to date has been on adjectives, it can be directly …

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