The work presents a computer-aided method of content analysis applicable to verbatim transcripts of psychotherapy: the Automated Co-occurrence Analysis for Semantic Mapping (ACASM). ACASM is able to perform a context-sensitive strategy of analysis aimed at mapping the meanings of the text through a trans-theoretical procedure. The paper is devoted to the presentation of the method and testing its validity. To the latter end we have compared ACASM and independent blind human coders on two tasks of content analysis: (a) estimating the semantic similarity between two utterances; (b) the semantic classification of a set of utterances. Results highlight that: (a) ACASM’s estimates of semantic similarity are consistent with the corresponding estimates provided by coders; (b) coders’ agreement and coder-ACASM agreement on the task of semantic classification have the same magnitude. Results lead to the conclusion that the content analysis produced by ACASM is indistinguishable from that performed by human coders.

Automated method of content analysis. A device for psychotherapy process research / Salvatore, S.; Gennaro, A.; Auletta, A.; Tonti, M.; Nitti, M.. - In: PSYCHOTHERAPY RESEARCH. - ISSN 1050-3307. - 22:3(2012), pp. 256-273. [10.1080/10503307.2011.647930]

Automated method of content analysis. A device for psychotherapy process research

Salvatore S.;Gennaro A.;Auletta A.;
2012

Abstract

The work presents a computer-aided method of content analysis applicable to verbatim transcripts of psychotherapy: the Automated Co-occurrence Analysis for Semantic Mapping (ACASM). ACASM is able to perform a context-sensitive strategy of analysis aimed at mapping the meanings of the text through a trans-theoretical procedure. The paper is devoted to the presentation of the method and testing its validity. To the latter end we have compared ACASM and independent blind human coders on two tasks of content analysis: (a) estimating the semantic similarity between two utterances; (b) the semantic classification of a set of utterances. Results highlight that: (a) ACASM’s estimates of semantic similarity are consistent with the corresponding estimates provided by coders; (b) coders’ agreement and coder-ACASM agreement on the task of semantic classification have the same magnitude. Results lead to the conclusion that the content analysis produced by ACASM is indistinguishable from that performed by human coders.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1246927
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