The Agile Cliché: Using Flexible Stereotypes as Building Blocks in the Construction of an Affective Lexicon

Our affective perspective on a word is heavily influenced by the context in which it is used and by the features it is typically perceived to exhibit in that context. A nuanced model of lexical affect thus requires a feature-rich representation of each word’s potential to mean different things in different contexts. To this end, we present here a two-level model of lexical affect. At the first level, words are represented as bundles of the typical properties and behaviors they are commonly shown to exhibit in everyday language. To construct these bundles, we present a semi-automatic approach to harvesting stereotypical properties and behaviors from the Web. At the second level, these properties and behaviors are related to each other in a graph structure that captures how likely one is to reinforce the meaning of another. We present an effective means of constructing such a graph from a combination of text n-grams and queries to the open Web. We calculate positive and negative potentials for each property in the graph, and show how these potentials can be used in turn to calculate an overall affective value for the higher-level terms for which they are considered stereotypical.