Twitter Moral Stance Classification Using Long Short-Term Memory Networks

Pavan, Matheus Camasmie; Santos, Wesley Ramos dos; Paraboni, Ivandré

doi:10.1007/978-3-030-61377-8_45

Cited by 12 publications

(7 citation statements)

References 11 publications

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“…University of São Paulo (USP) and Federal University of Bahia (UFBA) (RQ4) stood out. USP figuring in three of the nine papers [dos Santos and Paraboni 2019, Pavan et al 2020, Gonc ¸alves and Cozman 2021. UFBA is involved in two, both with explicit and provocative social critical content [Ferreira et al 2021, Moura et al 2021].…”

Section: Resultsmentioning

confidence: 99%

“…Five of the nine papers follow a quantitative methodology. Two present pragmatic approach [Nunes et al 2013, Pavan et al 2020]. [Gonc ¸alves and Cozman 2021], unlike others, presents interpretive research with historical content.…”

Section: Resultsmentioning

confidence: 99%

“…The inclusion step considered nine publications presenting relevant and pertinent ethical aspects for qualitative synthesis [Moura et al 2021, Broder and Berton 2021, Ferreira et al 2021, Gonc ¸alves and Cozman 2021, Pavan et al 2020, Viana and Alcântara 2020, dos Santos and Paraboni 2019, Carvalho et al 2014, Nunes et al 2013. Four researchers extracted data in order to answer the questions in Table 1.…”

Section: Methodology and Research Methodsmentioning

confidence: 99%

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Ethics: What is the Research Scenario in the Brazilian Conference BRACIS?

Carvalho

Murakami

Suzano

et al. 2022

Anais Do XIX Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2022)

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Artificial Intelligence (AI) presents many ethical dilemmas, such as explainability, bias, military uses, surveillance capitalism, employment, and jobs. In the scientific context, AI can lead us to a crisis of reproducibility spread across several areas of knowledge and guide mathematicians to solve high complexity problems. Both companies and government forward their guidelines, recommendations, and materials combining Ethics and AI. In this paper, we investigate the involvement of the Brazilian academic-scientific community with moral or ethical aspects through its publications, covering the Brazilian Conference on Intelligent Systems (BRACIS) as the most prominent Brazilian AI conference. Through a Literature Systematic Review method, we answer the main research question: what is the panorama of the explicit occurrence of ethical aspects in the BRACIS, ENIAC, and STIL conference papers? The results indicate a low occurrence of ethical aspects and increasing behavior over the years. Ethical deliberation was fruitful, constructive, and critical among these few occurrences. Whether in the Brazilian or international context, there are spaces to be filled and open opportunities for exploration along this path.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodology and Research Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Ethics: What is the Research Scenario in the Brazilian Conference BRACIS?

Carvalho

Murakami

Suzano

et al. 2022

Anais Do XIX Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2022)

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“…For instance, 'A universal basic income would alleviate poverty' conveys a stance in favour of the target 'universal basic income'. The task is analogous to sentiment analysis, but stance and sentiment are not necessarily correlated (Aldayel and Magdy, 2021;Pavan et al, 2020). In our current setting, we focus on six stance prediction tasks based on targets that have been popular discussion topics on Brazil social media (Brazilian presidents, Covid-related measures, and local institutions.)…”

Section: Downstream Evaluation Tasksmentioning

confidence: 99%

BERTabaporu: Assessing a Genre-specific Language Model for Portuguese NLP

da Costa,

Pavan,

dos Santos

et al. 2023

Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Proce

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Transformer-based language models such as Bidirectional Encoder Representations from Transformers (BERT) are now mainstream in the NLP field, but extensions to languages other than English, to new domains and/or to more specific text genres are still in demand. In this paper we introduced BERTabaporu, a BERT language model that has been pre-trained on Twitter data in the Brazilian Portuguese language. The model is shown to outperform the best-known general-purpose model for this language in three Twitter-related NLP tasks, making a potentially useful resource for Portuguese NLP in general.

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“…As an alternative to the use of pre-trained language models, we also consider the use of a sequence classifier based on a static word embeddings representation using LSTMs. Methods of this kind have been shown to obtain encouraging results in a wide range of NLP tasks, from stance and sentiment analysis [Zhang and v Wang, 2018, Pavan et al, 2020 to author profiling [Silva and Paraboni, 2018b, Ashraf et al, 2020, Escobar-Grisales et al, 2021 and others. More specifically, we compute Word2vec [Mikolov et al, 2013] skip-gram word embeddings from each corpus 4 using a standard 300-dimension size and 8-word window.…”

Section: Modelsmentioning

confidence: 99%

Myers-Briggs personality classification from social media text using pre-trained language models

Santos¹,

Paraboni²

2022

jucs

Self Cite

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In Natural Language Processing, the use of pre-trained language models has been shown to obtain state-of-the-art results in many downstream tasks such as sentiment analysis, author identification and others. In this work, we address the use of these methods for personality classification from text. Focusing on the Myers-Briggs (MBTI) personality model, we describe a series of experiments in which the well-known Bidirectional Encoder Representations from Transformers (BERT) model is fine-tuned to perform MBTI classification. Our main findings suggest that the current approach significantly outperforms well-known text classification models based on bag-of-words and static word embeddings alike across multiple evaluation scenarios, and generally outperforms previous work in the field.

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Twitter Moral Stance Classification Using Long Short-Term Memory Networks

Cited by 12 publications

References 11 publications

Ethics: What is the Research Scenario in the Brazilian Conference BRACIS?

Ethics: What is the Research Scenario in the Brazilian Conference BRACIS?

BERTabaporu: Assessing a Genre-specific Language Model for Portuguese NLP

Myers-Briggs personality classification from social media text using pre-trained language models

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