MLNA – A Python package and app for MultiLingual Network Analysis

The Python package and associated app, MLNA (MultiLingual Network Analysis), make multilingual texts accessible to humanists, addressing the Eurocentrism in humanities research caused by scholars' limited knowledge of non-European languages. MLNA processes multilingual texts and visualizes networks of their entities. By manually assigning entities and adjusting graph features, users can gain an overview of the texts' contents. This enables researchers to narrow their multilingual text collection to texts with relevant entities or relationships, which can then be translated for close reading, saving a great amount of time. MLNA empowers scholars to engage with multilingual text documents, fostering a novel synthesis of close and distant reading, and contributing to greater inclusivity in text-based humanities research.

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Publication Details

Journal
SoftwareX
Published
2025-02-26
DOI
https://doi.org/10.1016/j.softx.2025.102104
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

MLNA – A Python package and app for MultiLingual Network Analysis

Golnaz Sarkar Farshi
SoftwareX
Natural Language Processing Techniques
article

MLNA – A Python package and app for MultiLingual Network Analysis

Golnaz Sarkar Farshi
article en

Abstract

The Python package and associated app, MLNA (MultiLingual Network Analysis), make multilingual texts accessible to humanists, addressing the Eurocentrism in humanities research caused by scholars' limited knowledge of non-European languages. MLNA processes multilingual texts and visualizes networks of their entities. By manually assigning entities and adjusting graph features, users can gain an overview of the texts' contents. This enables researchers to narrow their multilingual text collection to texts with relevant entities or relationships, which can then be translated for close reading, saving a great amount of time. MLNA empowers scholars to engage with multilingual text documents, fostering a novel synthesis of close and distant reading, and contributing to greater inclusivity in text-based humanities research.

SoftwareXVol. 30
Philipps University of Marburg (DE)
Openalex Percentile: Top 99%
Natural Language Processing Techniques
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