Cognitive Linguistics & Quantitative Text Analysis Laboratory

Linguistics is a field that aims to extract characteristics from language data actually used by people and to describe and explain the underlying mechanisms and patterns through models. However, it is not realistic to investigate every individual speaker one by one. Therefore, linguists analyze corpora―collections of language data that serve as samples―to clarify observable tendencies in language use. In our laboratory, we analyze differences in language use across age groups and communities, as well as differences in linguistic expression associated with psychological states, from both qualitative and quantitative perspectives. The corpora used in our research are constructed through methods such as text collection via Python-based API requests, small-scale questionnaire surveys involving people in familiar contexts, and large-scale surveys conducted in collaboration with survey companies. The resulting language and psychological data are processed mechanically using programming and software tools, and are analyzed and modeled using statistical methods. The results are then interpreted from linguistic and psychological perspectives in order to explain differences in language use and human cognition. Students in our laboratory are typically interested in modeling how differences in mental states and cognition are reflected in linguistic expression, or how linguistic expression influences society. For details of our main research themes, please refer to the section “Laboratory Close-Up” below.

College of Engineering Mechanical Engineering Advanced Mechanical Engineering / Graduate School of Engineering and Science（Master's Program） Mechanical Engineering Course / Graduate School of Engineering and Science（Doctor's Program） Functional Control Systems Course

Faculty Name

SHINTANI, Mayu

Keyword

textmining,color terms,Cognitive Linguistics,Motivation,psychometric measurements,Educational Technology,Quantitative text analysis

Laboratory location

No.4 Building OMIYA Campus 4F 4402-2

This lab is for this SDG activity:

Cognitive Linguistics
Quantitative Text Analysis
Linguistic Statistics
Educational Technology
Creation, measurement and evaluation of psychometric scales
Linguistic analysis using Python

Deepen our understanding of the world's diversity through language. Provide better education by assessing people's psychological status and the language they use to express it.

Predictive models of code-switching occurrence using psychological traits and individual attributes as explanatory variables
Text mining analysis of English learners’ perceptions toward generative AI
Constructing psychometric scales to measure the psychology of L2 English learners
surveys of communication skills among engineering students and professionals
Investigations of the uncanny valley phenomenon based on linguistic data and psychological states

Laboratory close-up

- Field: This laboratory is positioned at the intersection of quantitative (science and engineeringgbased) and qualitative (humanities-based) approaches. Using statistical analysis and mathematical modeling, we conduct research on language, communication, and human cognition. This laboratory is well suited for students who are interested in language research from an engineering perspective, who would like to apply statistical knowledge to linguistic studies, or who want to analyze language data using programming. - Recent student research topics: Prediction of code-switching occurrence in Japanese usage among Chinese international students; prediction of song popularity (hit vs. non-hit) using J-Pop lyrics and other features; analysis of behaviors related to “oshi-katsu” (fan activities) with a focus on generational and individual differences; analysis and modeling of the uncanny valley phenomenon based on the Semantic Differential (SD) method; among others. - Graduate and undergraduate research seminars: Seminars are held at the Toyosu Campus. Activities include reading textbooks and academic papers, as well as hands-on data analysis exercises using Python and statistical software. Students with no prior experience in programming or statistical analysis are guided step by step. - For those considering graduate study: Students who wish to receive supervision at Shibaura Institute of Technology’s graduate programs (Master’s and Doctoral) are encouraged to contact us in advance. Contact: shintani[atatatat]shibaura-it. ac. jp (please replace “[atatat]” with “@” and adjust punctuation as needed) - International students: The laboratory accepts international students who hold a Japanese student visa (with prior experience). If you are interested, please consult in advance via the TAO system or by direct contact.