(aside image)

GICA - Grounded Intersubjective Concept Analysis

GICA - a new method

We have recently introduced a novel method to analyze and make visible differences among people regarding how they conceptualize the world. The Grounded Intersubjective Concept Analysis (GICA) method first employs either a conceptual survey or a text mining step to elicit particular ways in which terms and associated concepts are used among individuals. The subsequent analysis and visualization reveals potential underlying groupings of people, objects and contexts.

The GICA method extends the basic idea of the traditional term-document matrix analysis to include a third dimension of different individuals. This leads to a formation of a third-order tensor of Subjects x Objects x Contexts. Through flattening, these Subject-Object-Context (SOC) tensors can be analyzed using various computational methods.


In human communication, it is the occasional clear failure that allows us to see that understanding language is often difficult. In making the connection between a word and its typical and appropriate use, we humans rely on a long learning process. The process is made possible and guided by our genetic make-up, but its success essentially requires extensive immersion to a culture and contexts of using words and expressions. To the extent that these contexts are shared among individual language speakers, we are then able to understand each other.

When our learning contexts differ, however, differences in understanding the concepts themselves arise and subsequent communication failures begin to take place. Two main failure types can be detected. The first type is false agreement, where on the surface it looks as if we agree, but in fact our conceptual difference hides the underlying difference in opinions or world views. The second type of problem caused by undiscovered meaning differences is false disagreement. If we are raised (linguistically speaking) in different sub-cultures, we might come to share ideas and views, but might have learned to use different expressions to describe them.



Earlier related work