Application of Text Analytics to Analyze Emotions in the Speeches

Dzieciątko, Mariusz

doi:10.1007/978-3-319-91211-0_46

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…The research of Dzieciatko [17] and Rheault et al [48] have applied sentiment analysis to entire corpora at the highest granularity, i.e. their analysis of the Polish and UK parliaments aggregates sentiment scores of all speeches.…”

Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Miok,

Hidalgo Tenorio,

Osenova

et al. 2024

IDA

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Parliamentary and legislative debate transcripts provide an informative insight into elected politicians’ opinions, positions, and policy preferences. They are interesting for political and social sciences as well as linguistics and natural language processing (NLP) research. While exiting research studied individual parliaments, we apply advanced NLP methods to a joint and comparative analysis of six national parliaments (Bulgarian, Czech, French, Slovene, Spanish, and United Kingdom) between 2017 and 2020. We analyze emotions and sentiment in the transcripts from the ParlaMint dataset collection, and assess if the age, gender, and political orientation of speakers can be detected from their speeches. The results show some commonalities and many surprising differences among the analyzed countries.

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Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Miok,

Hidalgo Tenorio,

Osenova

et al. 2024

IDA

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“…Truncated-SVD is a matrix decomposition technique used for tasks such as dimensionality reduction, feature extraction, and data compression. It helps in understanding the underlying structure in data, identifying patterns and correlations, thereby achieving data dimensionality reduction or extracting important features [52]. LLM is commonly used to estimate parameters of probability distributions to maximize the likelihood of observed data.…”

Section: Text Mining For Tower Crane Accidentsmentioning

confidence: 99%

Enhancing Human Reliability Prediction in Smart Tower Crane Interfaces: A Refined Approach Using Simplified Plant Analysis Risk–Human Reliability Assessment and the Decision Making Trial and Evaluation Laboratory–Analytic Network Process

Si,

Niu

2024

Buildings

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With the advent of Industry 4.0, the prevalence of tower cranes equipped with hook visualization is increasing. However, the introduction of new interface management tasks has led to novel patterns of human errors for operators. The Simplified Plant Analysis Risk–Human Reliability Assessment (SPAR-H) method has emerged as a relevant approach for the prediction of human reliability in smart construction tower crane operations. However, the current SPAR-H method is only partially applicable and does not fully meet the requirements of this study. Initially, a text mining approach (TF-IDF-TruncatedSVD-ComplementNB) was employed to identify operator error-specific terms in tower crane operations. These terms were then correlated with the eight Performance Shaping Factors (PSFs) of the SPAR-H method, and corresponding failure modes and potential causes were determined from the literature. This ensured a more objective selection of influencing factors and PSFs during the stratification process, which was validated through questionnaire surveys. Furthermore, standards for SPAR-H PSF levels were established based on the characteristics of tower crane operators. Given the inherent complexity of relationships among SPAR-H PSFs, the DEMATEL-ANP method was applied. This involved analyzing logical interactions and causal relationships between first-level and second-level indicators of PSFs, obtaining weights, and integrating these with the SPAR-H method to determine human reliability. Finally, an analysis and validation were conducted using a case study of an accident involving a smart construction tower crane, confirming the subsequent reliability of operator actions. The result of the accident case study yielded a reliability measure of 4.2 × 10−5. These findings indicate that the evaluation process of this method aligns with scenarios encountered in smart construction tower crane operations.

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“…In most cases, sentiment analysis involves document, sentence, and aspect-level analysis. Dziecia˛tko (2018) and Rheault et al (2016) apply sentiment analysis to entire corpora at the highest granularity. Their analysis of the Polish and UK parliaments aggregates sentiment scores of all speeches.…”

Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis

Miok¹,

Tenorio²,

Osenova³

et al. 2022

Preprint

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Parliamentary and legislative debate transcripts provide an exciting insight into elected politicians' opinions, positions, and policy preferences. They are interesting for political and social sciences as well as linguistics and natural language processing (NLP). Exiting research covers discussions within individual parliaments. In contrast, we apply advanced NLP methods to a joint and comparative analysis of six national parliaments (Bulgarian, Czech, French, Slovene, Spanish, and United Kingdom) between 2017 and 2020, whose transcripts are a part of the ParlaMint dataset collection. Using a uniform methodology, we analyze topics discussed, emotions, and sentiment. We assess if the age, gender, and political orientation of speakers can be detected from speeches. The results show some commonalities and many surprising differences among the analyzed countries.

show abstract

Application of Text Analytics to Analyze Emotions in the Speeches

Cited by 7 publications

References 11 publications

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Enhancing Human Reliability Prediction in Smart Tower Crane Interfaces: A Refined Approach Using Simplified Plant Analysis Risk–Human Reliability Assessment and the Decision Making Trial and Evaluation Laboratory–Analytic Network Process

Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis

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