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ALIGN: Analyzing linguistic interactions with generalizable techNiques-A Python library.

Nicholas D Duran¹, Alexandra Paxton², Riccardo Fusaroli³

¹School of Social and Behavioral Sciences.

Psychological Methods

|March 1, 2019

Summary

This summary is machine-generated.

This study introduces ALIGN, an open-source Python package for analyzing linguistic alignment (LA) in conversations. ALIGN standardizes LA measurement, facilitating research on its role in understanding and rapport.

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Area of Science:

Computational Linguistics
Psycholinguistics
Social Psychology

Background:

Linguistic alignment (LA) involves conversational partners mirroring each other's language use.
LA is theorized to enhance mutual understanding and interpersonal connection.
Current research on LA is hindered by diverse, non-standardized analytical methods.

Purpose of the Study:

To address the methodological fragmentation in linguistic alignment research.
To introduce ALIGN, an open-source Python package for consistent LA measurement.
To provide a standardized protocol for analyzing LA in conversational data.

Main Methods:

Development of ALIGN, an open-source Python package for quantifying linguistic alignment.
Creation of comprehensive tutorials for ALIGN usage, hosted on GitHub.
Application of the ALIGN protocol to the Devil's Advocate dialogue corpus.

Main Results:

ALIGN offers a generalizable technique for measuring linguistic alignment across different conversational contexts.
The package and its tutorials enable reproducible and comparable analyses of LA.
Demonstrated the utility of ALIGN in addressing theoretical questions about dialogue dynamics.

Conclusions:

ALIGN provides a crucial tool for advancing the systematic study of linguistic alignment.
Standardized methods are essential for integrating findings and understanding the impact of LA.
Future work should focus on further developing LA analysis techniques and corpora.