CLQMDec 14, 2023

Using eye tracking to investigate what native Chinese speakers notice about linguistic landscape images

arXiv:2312.08906v41 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

This work addresses a gap in sociolinguistic research by applying eye tracking to investigate visual attention patterns in linguistic landscapes, though it is incremental as it extends existing methods to a new domain.

The study used eye tracking to measure how native Chinese speakers visually attend to linguistic versus general landscape images, finding that linguistic landscapes received significantly longer and more frequent fixations, attributed to their higher information density.

Linguistic landscape is an important field in sociolinguistic research. Eye tracking technology is a common technology in psychological research. There are few cases of using eye movement to study linguistic landscape. This paper uses eye tracking technology to study the actual fixation of the linguistic landscape and finds that in the two dimensions of fixation time and fixation times, the fixation of native Chinese speakers to the linguistic landscape is higher than that of the general landscape. This paper argues that this phenomenon is due to the higher information density of linguistic landscapes. At the same time, the article also discusses other possible reasons for this phenomenon.

Code Implementations1 repo
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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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