Word Association Profiles and their Use for Automated Scoring of Essays

Beata Beigman Klebanov and Michael Flor

The 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013)
Sofia, Bulgaria, August 4-9, 2013

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Abstract

We describe a new representation of the content vocabulary of a text we call "word association profile" that captures the proportions of highly associated, mildly associated, unassociated, and dis-associated pairs of words that co-exist in the given text. We illustrate the shape of the distirbution and observe variation with genre and target audience. We present a study of the relationship between quality of writing and word association profile. For a set of essays written by college graduates on a number of general topics, we show that the higher scoring essays tend to have higher percentages of both highly associated and dis-associated pairs, and lower percentages of mildly associated pairs of words. Finally, we use word association profiles to improve a system for automated scoring of essays.

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