Data Science in Social Politics with Particular Emphasis on Sentiment Analysis

Aramburo, Raúl Felipe Parra; Moreira, Miguel Ângelo Lellis; Fávero, Luiz Paulo Lopes; Costa, Igor Pınheıro de Araújo; Santos, Marcos dos

doi:10.1016/j.procs.2022.11.194

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Other1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Comprehensive review and comparative analysis of transformer models in sentiment analysis

Bashiri,

Naderi

2024

Knowl Inf Syst

View full text Add to dashboard Cite

Comprehensive review and comparative analysis of transformer models in sentiment analysis

Bashiri,

Naderi

2024

Knowl Inf Syst

View full text Add to dashboard Cite

Perceptions of Electric Vehicle Adoption Through Natural Language Processing and Machine Learning

Gutierrez Araiza,

Luna,

Santiago

et al. 2024

2024 IEEE International Systems Conference (SysCon)

View full text Add to dashboard Cite

Exploring the Drawbacks of Using Artificial Intelligence in Studies on Architecture:NLP and Highly Contextual Postmodern Architectural Discourse

Chrzanowska

2024

Builder

View full text Add to dashboard Cite

This research investigates the artificial intelligence aided architectural discursive sentiment analysis within the texts of the representants of architectural culture of the sixties and the seventies. The subject of inquiry for this study is to examine the nature and validity of sentiment analysis, using Natural Language Processing tools, on postmodernist architectural discourse. This paper searches to identify the possible drawbacks of using the NLP tool. The results show that the sentiment analysis of postmodernist texts using opinion mining techniques must be interpreted with the utmost caution. Especially in the case of unstraightforward, highly contextualized, and modernist reactive, often ironic or sarcastic, postmodern discourse. Two main reasons for that were found in this study. First, architectural postmodernists use many polarized words which might end in inconclusive results when opinion mining techniques are in use. Second, the postmodernist texts might themselves lack important contextual cues for appropriate classification of sentiment by NLP. Discrepancies and internal contradictions are characteristic for the postmodernist style of writing. and artificial intelligence still does not fully decode it.

show abstract

Data Science in Social Politics with Particular Emphasis on Sentiment Analysis

Cited by 3 publications

References 16 publications

Comprehensive review and comparative analysis of transformer models in sentiment analysis

Comprehensive review and comparative analysis of transformer models in sentiment analysis

Perceptions of Electric Vehicle Adoption Through Natural Language Processing and Machine Learning

Exploring the Drawbacks of Using Artificial Intelligence in Studies on Architecture:NLP and Highly Contextual Postmodern Architectural Discourse

Contact Info

Product

Resources

About