The number of social media platforms has increased significantly, as well as the number of active users. More than 18.2 million text messages are transmitted every minute on these platforms. Given the amount of data available, Natural Language Processing (NLP) techniques have been used by several researchers to analyze this large amount of unstructured data. Thus, it is essential to understand social media analysis's main trends and challenges. From this perspective, this study presents a systematic mapping of NLP for social media analysis considering papers published in five well-established academic Brazilian events: BRACIS, BraSNAM, ENIAC, STIL, and PROPOR. The study aims to identify the main tools and techniques used, tasks performed, data sources, and evaluation measures. For this purpose, 186 studies were analyzed and carefully selected among the 654 papers published in these events in the three years (2020 to 2022). The results show a glimpse of the current scenario on the subject and point out areas that can be improved in future research with techniques for tasks such as text classification, sentiment analysis, and named-entity recognition. Therefore, this work can be helpful for academics interested in exploring the potential NLP for social media analysis and having a clear view of gaps, challenges, and research opportunities in this area. Nevertheless, it should guide the productive sector in this knowledge transfer, reducing the gap between the state of the art and practice, consequently increasing the competitiveness and innovation of social media analysis tools.
The article was driven by a systematic mapping of publications in the proceedings of Brazilian scientific events that deal with text mining and social media analysis, specifically in the area of Natural Language Processing (NLP):
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Brazilian Conference on Intelligent Systems (BRACIS)
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Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)
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Encontro Nacional de Inteligência Artificial e Computacional (ENIAC)
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International Conference on Computational Processing of the Portuguese Language (PROPOR)
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Symposium in Information and Human Language Technology (STIL)
Source Selected articles Year BRACIS 43 2020 - 2022 BraSNAM 33 2020 - 2022 ENIAC 49 2020 - 2022 PROPOR 30 2020 - 2022 STIL 31 2021
- Preprocessing: The database conversion from .xlsx to .csv, standardization, and attribute cleaning.
- Exploratory Analysis: Exploratory analysis of data and generation of graphs.
- Wordcloud: Word cloud generation from data sources.
- Datasets: Folder containing the databases comprising the mapped attributes.
- Results: Folder containing the analysis results.
 Gabriele de S. Araújo |
 Jéssica Brenda P. Leite |
 Marcelino S. da Silva |
 Antonio F. L. Jacob Junior |
 Fábio M. F. Lobato |
@inproceedings{araujo2023natural,
title={Natural Language Processing and Social Media: a systematic mapping on Brazilian leading events},
author={Ara{\'u}jo, Gabriele de S and Leite, J{\'e}ssica Brenda P and da Silva, Marcelino S and Junior, Antonio FL Jacob and Lobato, F{\'a}bio MF},
booktitle={Anais do XX Encontro Nacional de Intelig{\^e}ncia Artificial e Computacional},
pages={741--755},
year={2023},
organization={SBC}
}