A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM

Gabriel A. León-Paredes; Luis A. Alba-Narváez; Santiago M. Torres-Cordero; Christian M. Buestan-Villa

doi:10.1007/978-3-031-93103-1_21

A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM

Gabriel A. León-Paredes
, Luis A. Alba-Narváez
, Santiago M. Torres-Cordero
, Christian M. Buestan-Villa

Research Group in Cloud Computing Smart Cities & High Performance Computing (GIHP4C)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Social media platforms, particularly TikTok, have become an integral part of daily life for millions globally, generating vast amounts of user-generated content. For businesses and content creators, understanding the sentiments behind these user comments is crucial for gauging public perception and refining their commercial or marketing strategies. However, the unique nature of comments on TikTok, characterized by their brevity, informal language, slang, and emojis, presents significant challenges for sentiment analysis. We developed a sentiment analysis system to address these challenges using advanced Natural Language Processing (NLP) and Deep Learning (DL) techniques. The system’s architecture, combining a frontend built with Angular and Tailwind CSS and a backend powered by FastAPI and a fine-tuned RoBERTa-based model, allows for real-time analysis of large datasets. Our model, trained with PyTorch CUDA, achieved a high accuracy of 87.2%, with a precision of 90%, a recall of 83.6%, and an F1-score of 86.7%.

Original language	English
Title of host publication	Information Technology and Systems - ICITS 2025
Editors	Alvaro Rocha, Carlos Ferrás, Hiram Calvo
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	210-219
Number of pages	10
ISBN (Print)	9783031931024
DOIs	https://doi.org/10.1007/978-3-031-93103-1_21
State	Published - 2025
Event	International Conference on Information Technology and Systems, ICITS 2025 - Mexico City, Mexico Duration: 22 Jan 2025 → 25 Jan 2025

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1449 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Information Technology and Systems, ICITS 2025
Country/Territory	Mexico
City	Mexico City
Period	22/01/25 → 25/01/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Deep Learning
Multilingual Natural Language Processing
Parallel Computing
PyTorch
Sentiment Analysis
Social Media Analysis

CACES Knowledge Areas

316A Software and Applications Development and Analysis

Access to Document

10.1007/978-3-031-93103-1_21

Cite this

León-Paredes, G. A., Alba-Narváez, L. A., Torres-Cordero, S. M., & Buestan-Villa, C. M. (2025). A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM. In A. Rocha, C. Ferrás, & H. Calvo (Eds.), Information Technology and Systems - ICITS 2025 (pp. 210-219). (Lecture Notes in Networks and Systems; Vol. 1449 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-93103-1_21

León-Paredes, Gabriel A. ; Alba-Narváez, Luis A. ; Torres-Cordero, Santiago M. et al. / A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM. Information Technology and Systems - ICITS 2025. editor / Alvaro Rocha ; Carlos Ferrás ; Hiram Calvo. Springer Science and Business Media Deutschland GmbH, 2025. pp. 210-219 (Lecture Notes in Networks and Systems).

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title = "A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM",

abstract = "Social media platforms, particularly TikTok, have become an integral part of daily life for millions globally, generating vast amounts of user-generated content. For businesses and content creators, understanding the sentiments behind these user comments is crucial for gauging public perception and refining their commercial or marketing strategies. However, the unique nature of comments on TikTok, characterized by their brevity, informal language, slang, and emojis, presents significant challenges for sentiment analysis. We developed a sentiment analysis system to address these challenges using advanced Natural Language Processing (NLP) and Deep Learning (DL) techniques. The system{\textquoteright}s architecture, combining a frontend built with Angular and Tailwind CSS and a backend powered by FastAPI and a fine-tuned RoBERTa-based model, allows for real-time analysis of large datasets. Our model, trained with PyTorch CUDA, achieved a high accuracy of 87.2\%, with a precision of 90\%, a recall of 83.6\%, and an F1-score of 86.7\%.",

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León-Paredes, GA, Alba-Narváez, LA, Torres-Cordero, SM & Buestan-Villa, CM 2025, A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM. in A Rocha, C Ferrás & H Calvo (eds), Information Technology and Systems - ICITS 2025. Lecture Notes in Networks and Systems, vol. 1449 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 210-219, International Conference on Information Technology and Systems, ICITS 2025, Mexico City, Mexico, 22/01/25. https://doi.org/10.1007/978-3-031-93103-1_21

A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM. / León-Paredes, Gabriel A.; Alba-Narváez, Luis A.; Torres-Cordero, Santiago M. et al.
Information Technology and Systems - ICITS 2025. ed. / Alvaro Rocha; Carlos Ferrás; Hiram Calvo. Springer Science and Business Media Deutschland GmbH, 2025. p. 210-219 (Lecture Notes in Networks and Systems; Vol. 1449 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Buestan-Villa, Christian M.

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León-Paredes GA, Alba-Narváez LA, Torres-Cordero SM, Buestan-Villa CM. A Multilingual Sentiment Analysis System for TikTok Comments in Spanish Using RoBERTa and LSTM. In Rocha A, Ferrás C, Calvo H, editors, Information Technology and Systems - ICITS 2025. Springer Science and Business Media Deutschland GmbH. 2025. p. 210-219. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-93103-1_21