Submission 697
Developing Advanced Tools for Cognitive–Affective Mapping: Possible Applications for Experimental Research
SymposiumTalk-01
Presented by: Julius Fenn
Cognitive–Affective Maps (CAMs) provide a structured method to capture how individuals organize concepts, associations, and emotional evaluations within a network-like representation. Although originally introduced as a mixed-methods tool, CAMs can be systematically embedded into experimental paradigms. Researchers may manipulate the initial network structure (e.g., predefined central or opposing concepts), the affective or informational context, or task constraints during map construction. The resulting CAMs serve as sensitive dependent variables that reflect cognitive–emotional processing and change.
We present Cognitive–Affective Map Extended Logic (C.A.M.E.L.), a software suite that enables such applications. Its data collection tool allows participants to construct or modify CAMs under standardized, fully configurable conditions. CAMs can contain graded emotional evaluations, weighted supporting or opposing connections, directional arrows, and typed semantic content, producing a complex data structure suitable for quantitative and qualitative analysis. The accompanying CAM-App supports preprocessing, semantic clustering, and network-level quantification (e.g., mean valence, density, neighborhood indicators) through transparent, protocol-based analysis pipelines. A web-based administrative panel facilitates study setup, configurations of parameters, and participant management.
This framework accommodates diverse experimental designs: CAMs as dependent variables in pre–post studies; CAMs as independent variables via predefined network; and adaptive paradigms in which real-time CAM analysis trigger subsequent tasks or feedback.
By integrating emotional evaluation, semantic associations, and graph structure into a different format, C.A.M.E.L. advances the study of cognitive–affective processes such as coherence formation, attitude change, and belief updating in the context of mental models.