The smallest and most commonly used words in English are pronouns, articles, and other function words. Almost invisible to the reader or writer, function words can reveal ways people think and approach topics. A computerized text analysis of over 50,000 college admissions essays from more than 25,000 entering students found a coherent dimension of language use based on eight standard function word categories. The dimension, which reflected the degree students used categorical versus dynamic language, was analyzed to track college grades over students' four years of college. Higher grades were associated with greater article and preposition use, indicating categorical language (i.e., references to complexly organized objects and concepts). Lower grades were associated with greater use of auxiliary verbs, pronouns, adverbs, conjunctions, and negations, indicating more dynamic language (i.e., personal narratives). The links between the categorical-dynamic index (CDI) and academic performance hint at the cognitive styles rewarded by higher education institutions.

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Formal semantics is the study of linguistic meaning using precise mathematical characterizations; this chapter introduces formal semantics to scholars and students of natural-language processing. We give simple logical representations of English sentences, and show how meanings are composed in a grammar. We then consider two more advanced issues that arise in processing texts, anaphora and temporality, using Discourse Representation Theory (DRT). Finally we discuss the relationship between deep logic-based methods for semantic analysis and shallower distributional methods that have been used in much recent NLP work, introducing some limitations of distributional methods, and hence motivating deeper or hybrid approaches.