Detecting Misleading Headlines Through the Automatic Recognition of Contradiction in Spanish

Sepúlveda-Torres, Robiert; Bonet-Jover, Alba; Saquete, Estela

doi:10.1109/access.2023.3295781

Cited by 2 publications

References 45 publications

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Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models

Deußer,

Leonhard,

Hillebrand

et al. 2023

2023 IEEE International Conference on Big Data (BigData)

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Correct identification and correction of contradictions and inconsistencies within financial reports constitute a fundamental component of the audit process. To streamline and automate this critical task, we introduce a novel approach leveraging large language models and an embedding-based paragraph clustering methodology. This paper assesses our approach across three distinct datasets, including two annotated datasets and one unannotated dataset, all within a zero-shot framework. Our findings reveal highly promising results that significantly enhance the effectiveness and efficiency of the auditing process, ultimately reducing the time required for a thorough and reliable financial report audit.

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Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models

Deußer,

Leonhard,

Hillebrand

et al. 2023

2023 IEEE International Conference on Big Data (BigData)

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Navigating the Disinformation Maze: A Bibliometric Analysis of Scholarly Efforts

Tătaru,

Domenteanu,

Delcea

et al. 2024

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The increasing prevalence of disinformation has become a global challenge, exacerbated by the rapid dissemination of information in online environments. The present study conducts a bibliometric analysis of scholarly efforts made over time in the research papers associated with the disinformation field. Thus, this paper aims to understand and help combat disinformation by focusing on methodologies, datasets, and key metadata. Through a bibliometric approach, the study identifies leading authors, affiliations, and journals and examines collaboration networks in the field of disinformation. This analysis highlights the significant growth in research on disinformation, particularly in response to events such as the 2016 U.S. election, Brexit, and the COVID-19 pandemic, with an overall growth rate of 15.14% in the entire analyzed period. The results of the analysis underscore the role of social media and artificial intelligence in the spread of disinformation, as well as the importance of fact-checking technologies. Findings reveal that the most prolific contributions come from universities in the United States of America (USA), the United Kingdom (UK), Spain, and other global institutions, with a notable increase in publications since 2018. Through thematic maps, a keyword analysis, and collaboration networks, this study provides a comprehensive overview of the evolving field of disinformation research, offering valuable insights for future investigations and policy development.

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Detecting Misleading Headlines Through the Automatic Recognition of Contradiction in Spanish

Cited by 2 publications

References 45 publications

Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models

Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models

Navigating the Disinformation Maze: A Bibliometric Analysis of Scholarly Efforts

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