<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Network technology influences and transforms the language use, environment, and cultural practices of ethnic minorities. This paper designs a text classification model for minority languages and cultures, utilizing BERT for word vector modeling, and introduces LSTM and attention mechanisms to capture distant semantic information, solve the gradient vanishing problem, and learn contextual details. The BiLSTM multi-head attention mechanism is then used to filter important semantic features of the input sequence, and finally, all extracted features are linked to complete the text classification and output the categories of minority language and culture texts. The model is applied to text datasets from ethnic minority forums and their news video datasets. It is found that the proportion of traditional ethnic minority vocabulary in forums decreased from 14.6% in 2004 to 10.7% in 2024. Conversely, the ratios of vocabulary related to consumption, marriage, employment, and education increased, with the ratio of marriage-related vocabulary rising from 0.33 to 0.94. This suggests that, despite the influence of Internet technology, traditional cultural concepts of marriage among ethnic minorities remain widely observed. This study provides a feasible solution for categorizing texts in minority languages and offers a unique reflection on the influence of the Internet on the cultural changes of minority languages.</p>
</abstract>

Network technology influences and transforms the language use, environment, and cultural practices of ethnic minorities. This paper designs a text classification model for minority languages and cultures, utilizing BERT for word vector modeling, and introduces LSTM and attention mechanisms to capture distant semantic information, solve the gradient vanishing problem, and learn contextual details. The BiLSTM multi-head attention mechanism is then used to filter important semantic features of the input sequence, and finally, all extracted features are linked to complete the text classification and output the categories of minority language and culture texts. The model is applied to text datasets from ethnic minority forums and their news video datasets. It is found that the proportion of traditional ethnic minority vocabulary in forums decreased from 14.6% in 2004 to 10.7% in 2024. Conversely, the ratios of vocabulary related to consumption, marriage, employment, and education increased, with the ratio of marriage-related vocabulary rising from 0.33 to 0.94. This suggests that, despite the influence of Internet technology, traditional cultural concepts of marriage among ethnic minorities remain widely observed. This study provides a feasible solution for categorizing texts in minority languages and offers a unique reflection on the influence of the Internet on the cultural changes of minority languages.

A Study of the Impact of Internet Technology on Minority Languages and Cultures

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"A Study of the Impact of Internet Technology on Minority Languages and Cultures"}

Network technology influences and transforms the language use, environment, and cultural practices of ethnic minorities. This paper designs a text...

A Study of the Impact of Internet Technology on Minority Languages and Cultures

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 29 mar 2024

Przyjęty: 23 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1949

Słowa kluczowe
Natural language processing, Text categorization, LSTM, Attention mechanism, Ethnic language culture

© 2024 Furui Jia, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Study of the Impact of Internet Technology on Minority Languages and Cultures

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 29 mar 2024

Przyjęty: 23 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1949

Słowa kluczoweNatural language processing, Text categorization, LSTM, Attention mechanism, Ethnic language culture

© 2024 Furui Jia, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Natural language processing, Text categorization, LSTM, Attention mechanism, Ethnic language culture