Research Article


DOI :10.26650/acin.815945   IUP :10.26650/acin.815945    Full Text (PDF)

Measuring Financial Form Readability of Technology Companies with Text Mining Techniques

M. Fevzi EsenTutku Tuncalı Yaman

In financial markets, companies are required to disclose a comprehensive review of their business operations and financial positions via filing forms. For these forms to be understood by investors, it is necessary to use plain language without complexity. Readability indexes are used to determine the syntactic length and complexity of the texts, and they are closely related to fields such as applied linguistics, text analysis, and natural language processing. These indexes are one of the text mining functions, which aims to obtain meaningful information from texts as a primary data source. In this study, we calculated the readability scores of a total of 23,103 public disclosure forms of 144 technology companies on the New York Stock Exchange (NYSE) between 2010 - 2019. The scores were evaluated by comparing alternative readability indexes. As a result of the study, it was determined that readability indexes, except for file size, provide similar results, and it was concluded that public disclosure forms are “very difficult” to understand and require higher educational levels than a graduate education. It was also shown that the forms of medium and large-sized technology companies have lower readability levels than other technology companies.

DOI :10.26650/acin.815945   IUP :10.26650/acin.815945    Full Text (PDF)

Teknoloji Alanında Faaliyet Gösteren Şirketlerin Finansal Form Okunabilirliğinin Metin Madenciliği Teknikleriyle Ölçülmesi

M. Fevzi EsenTutku Tuncalı Yaman

Finansal piyasalarda işlem gören şirketlerin yükümlülükleri kapsamında bulunan ve işletme operasyonları ile işletmelerin finansal durumlarına ilişkin kapsamlı bilgi sağlayan kamuya açıklama formlarının (Disclosure forms) yatırımcılar tarafından anlaşılabilmesi için, karmaşık olmayan yalın bir dil kullanılması gerekmektedir. Metinlerin söz dizimsel uzunluğu ve karmaşıklığının tespitinde kullanılan okunabilirlik indeksleri, uygulamalı dilbilim, metin ve söylem analizi ile doğal dil işleme gibi alanlarla yakından ilişkili olup, veri kaynağı olarak metin üzerinden anlamlı bilgi edinilmesini amaçlayan metin madenciliği fonksiyonlarından biridir. Bu çalışmada, 2010 – 2019 yılları arasında New York Borsası’nda (NYSE) işlem gören ve teknoloji alanında faaliyet gösteren 144 şirkete ilişkin farklı türlerde toplam 23.103 adet kamuya açıklama formu kullanılarak, her bir form türüne ilişkin okunabilirlik skorları hesaplanmıştır. Alternatif okunabilirlik indeksleriyle elde edilen skorlar karşılaştırılarak şirket ölçeklerine göre ortalama skorlar da değerlendirilmiştir. Çalışma sonucunda, dosya boyutu haricindeki indekslerin birbirine yakın sonuçlar verdiği tespit edilmiş olup, incelenen kamuya açıklama formlarının, lisansüstü eğitime sahip yatırımcıların seviyesinden de yüksek skorda, “çok zor” okunabilirlik düzeyinde olduğu; orta ve büyük ölçekteki teknoloji şirketlerince raporlanan formların ise daha düşük okunabilirlik düzeyine sahip olduğu sonucuna ulaşılmıştır.


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APA

Esen, M.F., & Tuncalı Yaman, T. (2020). Measuring Financial Form Readability of Technology Companies with Text Mining Techniques. Acta Infologica, 4(2), 77-97. https://doi.org/10.26650/acin.815945


AMA

Esen M F, Tuncalı Yaman T. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques. Acta Infologica. 2020;4(2):77-97. https://doi.org/10.26650/acin.815945


ABNT

Esen, M.F.; Tuncalı Yaman, T. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques. Acta Infologica, [Publisher Location], v. 4, n. 2, p. 77-97, 2020.


Chicago: Author-Date Style

Esen, M. Fevzi, and Tutku Tuncalı Yaman. 2020. “Measuring Financial Form Readability of Technology Companies with Text Mining Techniques.” Acta Infologica 4, no. 2: 77-97. https://doi.org/10.26650/acin.815945


Chicago: Humanities Style

Esen, M. Fevzi, and Tutku Tuncalı Yaman. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques.” Acta Infologica 4, no. 2 (Jun. 2021): 77-97. https://doi.org/10.26650/acin.815945


Harvard: Australian Style

Esen, MF & Tuncalı Yaman, T 2020, 'Measuring Financial Form Readability of Technology Companies with Text Mining Techniques', Acta Infologica, vol. 4, no. 2, pp. 77-97, viewed 18 Jun. 2021, https://doi.org/10.26650/acin.815945


Harvard: Author-Date Style

Esen, M.F. and Tuncalı Yaman, T. (2020) ‘Measuring Financial Form Readability of Technology Companies with Text Mining Techniques’, Acta Infologica, 4(2), pp. 77-97. https://doi.org/10.26650/acin.815945 (18 Jun. 2021).


MLA

Esen, M. Fevzi, and Tutku Tuncalı Yaman. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques.” Acta Infologica, vol. 4, no. 2, 2020, pp. 77-97. [Database Container], https://doi.org/10.26650/acin.815945


Vancouver

Esen MF, Tuncalı Yaman T. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques. Acta Infologica [Internet]. 18 Jun. 2021 [cited 18 Jun. 2021];4(2):77-97. Available from: https://doi.org/10.26650/acin.815945 doi: 10.26650/acin.815945


ISNAD

Esen, M.Fevzi - Tuncalı Yaman, Tutku. Measuring Financial Form Readability of Technology Companies with Text Mining Techniques”. Acta Infologica 4/2 (Jun. 2021): 77-97. https://doi.org/10.26650/acin.815945



TIMELINE


Submitted24.10.2020
Accepted16.12.2020
Published Online31.12.2020

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