NDLI: Automatic content coding of English text

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Automatic content coding of English text

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Automatic content coding of English text

Content Provider	ACM Digital Library
Author	Tripodes, Peter G. Shure, Gerald H. Dolan, Peter Greenstein, Sherman Bodnaras, Maria
Abstract	PETE is a Programmed Experimental Theme Encoder designed to encode suitably restricted input English sentences into discrete themes, each consisting of: an actor, with its attributes; an action, initiated by that actor, with its attributes; and a target, with its attributes. PETE consists of a three-step encoding process: 1. Grammatical labels contained in a dictionary are affixed to all words in the input text. 2. A sequential code, i.e. a sequence of one or more basic codes, is then assigned to each word in the sentence; these sequential codes indicate the relationships between text constituents in their role(s) as actor, action, and target units. 3. A converter, operating on the sequential codes, recomposes the text constituents into one or more themes. PETE was initially designed to automate the functions performed by the human encoder in coding political text for machine processing by the Stanford Inquirer computer-based program of content analysis. PETE's performance in this role is described. The utility of PETE, in conjunction with appropriate content analytic dictionaries and retrieval systems, for social science research is suggested by its potential use in the content analysis of political event summary statements (WEIS). An appendix describes the detailed workings of PETE and its underlying grammatical theory.
Starting Page	426
Ending Page	427
Page Count	2
File Format	PDF
DOI	10.1145/1408800.1408816
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1974-01-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Social science applications Automated theme encoding Content analysis
Content Type	Text
Resource Type	Article

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