Sektionen

Suche

Institut für Psychologie

Albert-Ludwigs-Universität Freiburg

Sektionen

Suche

Sie sind hier: Startseite › Abteilungen und Arbeitsgruppen › Allgemeine Psychologie › Research › CAM Research

Artikelaktionen

Drucken

Startseite

Schnellzugriff

CAM-Research - Information, Publications

Introduction

As a complement to classical questionnaire-based survey methods, we develop and use Cognitive-Affective Mapping (CAM), a new data acquisition method combining both qualitative and quantititative approaches.

CAM_example_sendtner2021

Example of CAM: In the following example CAM, participants compared cars and public transport (see Sendtner, 2021)

This illustrative example map was created using the software Valence (Rhea et al., 2020, see below) and depicts beliefs and attitudes towards the motivation of individuals to use cars or public transport (see Sendtner, 2021). The rectangles, ovals and hexagons are called nodes. Each node represents a concept. A concept is ‘a representation of an important cognitive element, such as a goal, action, event, person, organization, or general idea’ (Thagard, 2010: 79). Each concept is depicted with its associated affective valence, i.e., whether the person drawing the map associates positive, negative, neutral or ambivalent valences with the concept. Positive concepts are represented by green ovals, negative concepts by red hexagons. Yellow rectangles represent neutral concepts. If both positive and negative feelings are associated with a concept, they are represented as a purple superimposed hexagon and oval. For positive and negative concepts, there are three different intensity levels of the resp. affective valence (transformed on a three-level scale from +1 to +3; or -1 to -3, resp.). The intensity of the valence is represented by the thickness of the outline of the node.

The individual nodes can be connected with each other by means of lines. In accordance with the technical terms used in network theory, these connecting lines are called edges. Solid edges indicate a positive relationship between two concepts: the concepts support or reinforce each other. Dashed edges, on the other hand, indicate that two concepts inhibit or oppose each other. The strength of the supporting or inhibiting effect of an edge can vary from +1 to +3, which is represented by the thickness of the edge. Deviating from the original conventions, our editing systems enable further differentiation of the edges. Subjects can indicate whether two concepts influence each other unidirectionally or reciprocally. An edge can be marked with an arrowhead if the subject believes that concept x influences concept y. If the subject draws a line without arrowhead, he or she expresses that the concepts influence each other reciprocally. Furthermore, participants can annotate concepts and edges. This is especially important in application contexts where the CAM method has to unfold its communicative potential. (modified excerpt from Livanec et al., 2022)

Draw your own CAM

To draw your own CAM there are two software solutions:

C.A.M. extended logic (version 1.9), which is based on Valence
Valence

Implementations

Feel free to test! For a glimpse at some documentation, see papers below. More is underway.

CAM data collection:
- C.A.M. extended logic (version 1.9)
  - Fenn, J., Gouret, F., Gorki, M., Hüttner, P., Reuter, L., Gros, W., & Kiesel, A. (2023). Cognitive-Affective Maps extended logic (Version 1.9) [Computer software]. https://github.com/Camel-app/DataCollection
- Valence (software tool for creating cognitive affective maps)
  Rhea, C., Reuter, L., Tecza, A., & Mansell, J. (2021, June 28). CAM Network Analysis. https://doi.org/10.17605/OSF.IO/PXNVZ
  - Rhea, C., Reuter, L., & Piereder, J. (2020). Valence Software Release. https://doi.org/10.17605/OSF.IO/9TZA2
CAM analysis
- CAM-App (version 2.2)
  - Fenn, J., Gouret, F., Gorki, M., Hüttner, P., Reuter, L., Gros, W., & Kiesel, A. (2023). CAM-App (Version 2.2) [Computer software]. https://github.com/Camel-app/DataAnalysis

Published Articles (chronological order)

Fenn, J., Helm, J. F., Höfele, P., Kulbe, L., Ernst, A., & Kiesel, A. (2023). Identifying key-psychological factors influencing the acceptance of yet emerging technologies–A multi-method-approach to inform climate policy. PLOS Climate, 2(6). https://doi.org/10.1371/journal.pclm.0000207

Höfele, P., Reuter, L., Estadieu, L., Livanec, S., Stumpf, M. & Kiesel, A. (2022). Connecting the methods of Psychology and Philosophy: Applying Cognitive affective maps (CAMs) for identifying ethical principles underlying the evaluation of bioinspired technologies. Philosophical Psychology. https://doi.org/10.1080/09515089.2022.2113770

Livanec, S., Stumpf, M., Reuter, L., Fenn, J. & Kiesel, A. (2022). Who’s gonna use this? Psychological acceptance prediction of emerging technologies and transdisciplinary considerations in the Anthropocene. The Anthropocene Review. https://doi.org/10.1177/20530196221078924

Mansell, J., Reuter, L., Rhea, C., & Kiesel, A. (2021). A Novel Network Approach to Capture Cognition and Affect: COVID-19 Experiences in Canada and Germany. Frontiers in psychology, 12. https://doi.org/10.3389/fpsyg.2021.663627

Reuter, L., Fenn, J., Bilo, T. A., Schulz, M., Weyland, A. L., Kiesel, A., & Thomaschke, R. (2021). Leisure walks modulate the cognitive and affective representation of the corona pandemic: Employing Cognitive‐Affective Maps within a randomized experimental design. Applied Psychology: Health and Well‐Being. https://doi.org/10.1111/aphw.12283

Reuter, L., Mansell, J., Rhea, C. & Kiesel, A. (2021). Direct Assessment of Individual Connotation and Experience: An Introduction to Cognitive-Affective Mapping. Politics and the Life Sciences, 1-21. https://doi.org/10.1017/pls.2021.31

Book Chapter

Nothdurft, U., Kreil, A., Kiesel, A. & Thomaschke, R. (2021). Die kognitiv-affektive Kartierung des Begriffs „Muße“. In M. Fludernik & T. Jürgasch, T. (Hrsg.), Semantiken der Muße aus interdisziplinären Perspektiven (pp. 127-159). Tübingen: Mohr Siebeck.

Doctoral Theses

2022

Reuter, L. (2022). Bridging Over the Troubled Waters of Quantitative and Qualitative Methods: Exploring Cognitive-Affective Maps in Empirical Research. Doctoral thesis. Freiburg: Faculty of Economics and Behavioral Sciences, Albert-Ludwigs-Universität Freiburg.

Bachelor and Master Theses

2018

Kreil, A. (2018). Cognitive-Affective Mapping within the context of staircase and elevator use. Evaluating a new method in empirical psychological research. Masterthesis.Freiburg: Institut für Psychologie der Albert-Ludwigs-Universität.

Theory and Foundations

Thagard, P. (2010). EMPATHICA: A computer support system with visual representations for
cognitive-affective mapping. In: K. McGregor (ed), Proceedings of the workshop on visual
reasoning and representation (pp. 79–81). Menlo Park, CA: AAAI Press.

Collection of literature on Cognitive-Affective Maps by Paul Thagard

Sektionen

CAM-Research - Information, Publications

2022

2022

2021

2020

2018

Start Footer

Benutzerspezifische Werkzeuge