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Multilingual Financial Narrative Processing: Analysing Annual Reports in English, Spanish and Portuguese

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)

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Multilingual Financial Narrative Processing : Analysing Annual Reports in English, Spanish and Portuguese. / El Haj, Mahmoud; Rayson, Paul Edward; Young, Steven Eric; Alves, Paulo; Herrero Zorita, Carlos.

Multilingual Text Analysis: Challenges, Models, and Approaches. ed. / Marina Litvak; Natalia Vanetik. World Scientific Publishing, 2019.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)

Harvard

El Haj, M, Rayson, PE, Young, SE, Alves, P & Herrero Zorita, C 2019, Multilingual Financial Narrative Processing: Analysing Annual Reports in English, Spanish and Portuguese. in M Litvak & N Vanetik (eds), Multilingual Text Analysis: Challenges, Models, and Approaches. World Scientific Publishing. https://doi.org/10.1142/11116

APA

El Haj, M., Rayson, P. E., Young, S. E., Alves, P., & Herrero Zorita, C. (2019). Multilingual Financial Narrative Processing: Analysing Annual Reports in English, Spanish and Portuguese. In M. Litvak, & N. Vanetik (Eds.), Multilingual Text Analysis: Challenges, Models, and Approaches World Scientific Publishing. https://doi.org/10.1142/11116

Vancouver

El Haj M, Rayson PE, Young SE, Alves P, Herrero Zorita C. Multilingual Financial Narrative Processing: Analysing Annual Reports in English, Spanish and Portuguese. In Litvak M, Vanetik N, editors, Multilingual Text Analysis: Challenges, Models, and Approaches. World Scientific Publishing. 2019 https://doi.org/10.1142/11116

Author

El Haj, Mahmoud ; Rayson, Paul Edward ; Young, Steven Eric ; Alves, Paulo ; Herrero Zorita, Carlos. / Multilingual Financial Narrative Processing : Analysing Annual Reports in English, Spanish and Portuguese. Multilingual Text Analysis: Challenges, Models, and Approaches. editor / Marina Litvak ; Natalia Vanetik. World Scientific Publishing, 2019.

Bibtex

@inbook{7c6d38d2e7684b9c89f847037bab18e0,
title = "Multilingual Financial Narrative Processing: Analysing Annual Reports in English, Spanish and Portuguese",
abstract = "This chapter describes and evaluates the use of Information Extraction and Natural Language Processing methods for extraction and analysis of financial annual reports in three languages: English, Spanish and Portuguese. The work described retains information on document structure which is needed to enable a clear distinction between narrative and financial statement components of annual reports and between individual sections within the narratives component. Extraction accuracy varies between languages with English exceeding 95 {\%}. We apply the extraction methods on a comprehensive sample of annual reports published by UK, Spanish and Portuguese non-financial firms between 2003 and 2014.",
author = "{El Haj}, Mahmoud and Rayson, {Paul Edward} and Young, {Steven Eric} and Paulo Alves and {Herrero Zorita}, Carlos",
year = "2019",
month = "2",
doi = "10.1142/11116",
language = "English",
isbn = "9789813274877",
editor = "Marina Litvak and Natalia Vanetik",
booktitle = "Multilingual Text Analysis",
publisher = "World Scientific Publishing",

}

RIS

TY - CHAP

T1 - Multilingual Financial Narrative Processing

T2 - Analysing Annual Reports in English, Spanish and Portuguese

AU - El Haj, Mahmoud

AU - Rayson, Paul Edward

AU - Young, Steven Eric

AU - Alves, Paulo

AU - Herrero Zorita, Carlos

PY - 2019/2

Y1 - 2019/2

N2 - This chapter describes and evaluates the use of Information Extraction and Natural Language Processing methods for extraction and analysis of financial annual reports in three languages: English, Spanish and Portuguese. The work described retains information on document structure which is needed to enable a clear distinction between narrative and financial statement components of annual reports and between individual sections within the narratives component. Extraction accuracy varies between languages with English exceeding 95 %. We apply the extraction methods on a comprehensive sample of annual reports published by UK, Spanish and Portuguese non-financial firms between 2003 and 2014.

AB - This chapter describes and evaluates the use of Information Extraction and Natural Language Processing methods for extraction and analysis of financial annual reports in three languages: English, Spanish and Portuguese. The work described retains information on document structure which is needed to enable a clear distinction between narrative and financial statement components of annual reports and between individual sections within the narratives component. Extraction accuracy varies between languages with English exceeding 95 %. We apply the extraction methods on a comprehensive sample of annual reports published by UK, Spanish and Portuguese non-financial firms between 2003 and 2014.

U2 - 10.1142/11116

DO - 10.1142/11116

M3 - Chapter (peer-reviewed)

SN - 9789813274877

BT - Multilingual Text Analysis

A2 - Litvak, Marina

A2 - Vanetik, Natalia

PB - World Scientific Publishing

ER -