Mind Paths

What is the perceived relation between words?
This is still a complex issue for semantic specialists. The Mind Paths experiment uses a video-game in order to create a semantic map where volunteers define the distances between words. Semantic analysis is a major challenge for science and innovation as it's a complex task requiring advanced models and experts validations.

Start selecting which words lead from one fixed starting word to the goal word to create a visual map of distance between words. The results of this research will be important for the scientific as well as the business world with lots of applications being based on semantic analysis.

Background

Since the work by Quillian in the late ‘60s, the view of semantic memory as a networked structure has provided a valuable collection of scientific results. As the scientific community has learned what such network looks like (its structural features), the interest is shifting towards understanding how this structure is used (the dynamics on it). Of course, processes on semantic networks can be (and have been) simulated via "synthetic" dynamics, such as random walks (see Borge-Holthoefer, J. and Arenas, A. (2010) "Categorizing words through semantic memory navigation", EPJB, 74(2), 265). But we have few empirical evidence of how humans actually navigate their "semantic landscape".

This is where Citizen Science comes in. Capitalizing on a previous, small-scale experiment (see Beckage, N. et al. (2009) "Route choice in individuals-semantic network navigation", Proc. 34th An. Conf. Cognitive Science Society, 108), Mind Paths —promoted from the Cosnet Lab— intends to collect data from subjects around the world regarding their strategies to navigate the semantic landscape. In Mind Paths, for a given Source and a Target, volunteers are asked to build a path of intermediate words that connect them.

In the long run, the obtained data (which is publicly available, as that is the philosophy underlying the concept of Citizen Science) will help scholars to understand what sort of heuristics we exploit to efficiently manage our intricate structure of concepts.