Adjectives as indicators of subjectivity in documents

Abstract

The goal of this research is to automatically predict human judgments of document qualities such as subjectivity, verbosity and depth. In this paper, we explore the behavior of adjectives as indicators of subjectivity in documents. Specifically, we test whether a subset of automatically derived subjective adjectives (Wiebe, 2000b), selected a priori, behaves differently than other adjectives. 3,200 documents were ranked by 100 subjects as being high or low in nine document qualities (Tang, Ng, Strzalkowski, & Kantor, 2003). We report a statistically significant correlation between the occurrence of adjectives in documents and human judgments of subjectivity. More importantly, we find that the subset of subjective adjectives is more strongly correlated with subjectivity than adjectives in general. These results can be used to identify document qualities for use in information retrieval and question‐answering systems.

A Simple Approach to Classify Fictional and Non-Fictional Genres

“…A long line of research undeniably argues that adjective and adverbs are strong indicators of affective language and serve as an important feature in text classification tasks viz., automatic genre identification (Rittman et al, 2004;Rittman, 2007;Rittman and Wacholder, 2008;Cao and Fang, 2009).In this regard, Rittman and Wacholder (2008) propound that both these grammatical classes have sentimental connotations and capture human personality along with their expression of judgments. For our classifer, rather than the number of adjectives, it is the relative balance of adjectives and adverbs that determine the identity of a particular genre.…”

“…In this regard, Stamatatos and colleagues have shown that most frequent words in the training corpus as well as in the entire English language are one of the good features for detecting the genre type (Stamatatos et al, 2000). With respect to syntactic and semantics properties of the text, previous studies have used various parts of speech counts in terms of number of types and tokens (Rittman et al, 2004;Rittman, 2007;Rittman and Wacholder, 2008;Cao and Fang, 2009). Researchers have tried to investigate the efficacy of counts vs. ratio features and their impact on the classification model performance.…”

Intrinsic Quality Assessment of Arguments

“…Subjectivity Since we hypothesized subjectivity to be important, we here combine multiple frequency distributions: (a) singular and plural 1st, 2nd, and 3rd person pronouns, (b) indicators of positivity, negativity, and hedging (e.g., "certainly") based on Rittman et al (2004), (c) 83 different emojis, (d) fully lower-case, upper-case, and other words, and (e) character types, such as letter, digit, and whitespace.…”

Is 1 noun worth 2 adjectives? Measuring relative feature utility

“…Part-of-speech tags, attached to a specific term, provides valuable information that can help disambiguate terms, allowing a system to determine which meaning of a term is represented by the term's presence (E. A. Fox, Nutter, Ahlswede, Evens, & Markowitz, 1988;Justeson & Katz, 1995;Losee, 2001;Rittman et al, 2004;Wilks & Stevenson, 1998). When the term bank occurs in a document and a query, having the term labeled as a noun in the query and meaning a river bank and labeled as a verb in the document meaning to bank a plane, the POS tagging allows the non-match to exclude documents with the term whose sense doesn't match the query sense.…”