Argamon, S.; Whitelaw, C.; Chase, P.; Hota, S.R.; Garg, N.; Levitan, S.: Stylistic text classification using functional lexical features (2007)
0.00
3.4178712E-4 = product of:
0.0051268064 = sum of:
0.0051268064 = product of:
0.010253613 = sum of:
0.010253613 = weight(_text_:information in 280) [ClassicSimilarity], result of:
0.010253613 = score(doc=280,freq=6.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.20156369 = fieldWeight in 280, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=280)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Abstract
- Most text analysis and retrieval work to date has focused on the topic of a text; that is, what it is about. However, a text also contains much useful information in its style, or how it is written. This includes information about its author, its purpose, feelings it is meant to evoke, and more. This article develops a new type of lexical feature for use in stylistic text classification, based on taxonomies of various semantic functions of certain choice words or phrases. We demonstrate the usefulness of such features for the stylistic text classification tasks of determining author identity and nationality, the gender of literary characters, a text's sentiment (positive/ negative evaluation), and the rhetorical character of scientific journal articles. We further show how the use of functional features aids in gaining insight about stylistic differences among different kinds of texts.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.6, S.802-822
