Using Python for Text Analysis in Accounting Research

2020 ◽  
Vol 14 (3–4) ◽  
pp. 128-359
Author(s):  
Vic Anand ◽  
Khrystyna Bochkay ◽  
Roman Chychyla ◽  
Andrew Leone
Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Michael J. Egnoto ◽  
Darrin J. Griffin

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.


Author(s):  
Natalie Shapira ◽  
Gal Lazarus ◽  
Yoav Goldberg ◽  
Eva Gilboa-Schechtman ◽  
Rivka Tuval-Mashiach ◽  
...  

1977 ◽  
Vol 16 (03) ◽  
pp. 144-153 ◽  
Author(s):  
E. Vaccari ◽  
W. Delaney ◽  
A. Chiesa

A software system for the automatic free-text analysis and retrieval of radiological reports is presented. Such software involves: (1) automatic translation of the specific natural language in a formalized metalanguage in order to transform the radiological report in a »normalized report« analyzable by computer; (2) content processing of the normalized report to select desired information. The approach used to accomplish point (1) is described in detail referring to a specific application.


1991 ◽  
Vol 30 (04) ◽  
pp. 275-283 ◽  
Author(s):  
P. M. Pietrzyk

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.


2017 ◽  
pp. 75-80
Author(s):  
Orazio Vagnozzi

The existence of a gap between accounting research and accounting practice has been extensively described in literature. In order to be able to publish a research in a high-ranked accounting journal, it seems that methodological issues are more important than those related to the relevance of the topics covered. To improve research and accounting practice and to avoid the risk of accounting research becoming selfreferential, every effort should be made to bridge the current gap between research and accounting practice. To this end, the development of mutual knowledge of the agenda of researchers and practitioners on the one hand, and participation in joint projects on the other, could represent possible future solutions to be pursued.


2017 ◽  
pp. 67-74
Author(s):  
Giovanni Andrea Toselli

This paper represents a contribution from the point of view of a practitioner who strongly believes that it is essential to continue to invest in accounting research. The cooperation between chief financial officers, auditors and academic institutions is central not only for improving the process of accounting regulations but also for relaunching, at the same time, the industrial system (and not only it), by creating a strong feeling of trust in general economic and financial communication, thus fostering higher level of accountability.


2017 ◽  
pp. 29-42
Author(s):  
Aldo Pavan ◽  
Isabella Fadda

Accounting research has a speculative and normative tradition. Starting at the beginning of the 1970s, empirical methodologies gained prominence and the boundaries of accounting disciplines have become uncertain. Quantitative and qualitative methods tend to overwhelm the accounting and business objects; often they are only suitable to deal with past and narrow phenomena. Empirical methodologies need reference theories, coming from other disciplines and particularly economics and sociology. In this context, it is questioned if accounting research does exist anymore and if it is relevant to the business world. Some scholars have begun to wonder whether it would be appropriate to revalue normative approaches in order to conduct a type of research which is useful to the society and allows the preservation of specific accounting knowledge. A necessity emerges to come back to the prominence of business and accounting issues over methodologies and sociological theories. Research should be directed to tackle wide and current phenomena, not just the narrow and past ones. Speculative thinking has to be reassessed and empirical findings should be used to strengthen it as starting premises. Explaining phenomena is not enough; empirical research has to go beyond its findings; the emphasis should be shifted to the drawing of policy recommendations.


Author(s):  
Elena A. Fedorova ◽  
Diana V. Zaripova ◽  
Igor S. Demin

This work confirmed the hypotheses about the influence of the mood index on Twitter on the pricing of art objects and the difference between the experts' estimations and the final price of the auction. The hypotheses were tested with the use of a sample of 83 paintings selected on the basis of ratings of ARTNET's online resource about the most expensive works of art ever sold in the last 10–15 years. The sample consisted of 25 artists, for each of them was made an index of moods on Twitter. This index was created by a sentimental analysis of each tweet about the artist on the hashtag for a period of 2 to 4 months between the announcements of sales in the open sources and the direct sale of the work with the use of the two dictionaries AFINN and NRC.


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