Michaela Kolbe, Margarete Boos, Alexandra Stein and Micha Strack
SYNSEG—Eine Methode zur syntaxgeleiteten Segmentierung von Kodiereinheiten für die Analyse von Gruppenprozessen. = SYNSEG—A method for syntax-based segmentation of coding units for the analysis of group processes
Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO)
Observing group processes allows for obtaining insights into what successful groups do differently than less successful groups. In doing so, observational data is typically transcribed or integrated into coding software, coding units are identified, and coding systems are applied to code these units with regard to the respective content. While there are systems available for transcribing and coding observational group data, the segmentation of coding units is mostly left to the codersʼ intuition. Standardized and tested procedures for identifying coding units are not available for group research, limiting the reliability of coding group data. We introduce a method which aims at systematically identifying and segmenting coding units to enhance coding reliability. SYNSEG—syntax-based segmentation of coding units—suggests ten rules to segment coding units based on German grammar. To test for reliability, two coders applied SYNSEG for segmenting a 60-minute group discussion. A normalised Levensthein Distance of nD = 0,19 indicated satisfying coder agreement. We discuss the relevance and applicability of SYNSEG in applied group research. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
Accession Number: 2016-62747-005. Translated Title: SYNSEG—A method for syntax-based segmentation of coding units for the analysis of group processes. Other Journal Title: Gruppendynamik; Gruppendynamik und Organisationsberatung. Partial author list: First Author & Affiliation: Kolbe, Michaela; Universitatsspital Zurich, Zurich, Switzerland. Other Publishers: VS Verlag für Sozialwissenschaften/ GWV Fachverlage GmbH. Release Date: 20170309. Publication Type: Journal (0100), Peer Reviewed Journal (0110). Format Covered: Electronic. Document Type: Journal Article. Language: German. Major Descriptor: Group Dynamics; Organizations; Syntax; Coding Scheme. Classification: Organizational Behavior (3660). Population: Human (10). Age Group: Adulthood (18 yrs & older) (300). Page Count: 10. Issue Publication Date: Dec, 2016. Publication History: First Posted Date: Nov 30, 2016. Copyright Statement: Springer Fachmedien Wiesbaden. 2016.