Finding evidence of fraudster companies in the CEO’s letter to shareholders with sentiment analysis

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• dc.contributor.author Bel Rafecas, Núria
• dc.contributor.author Bracons, Gabriel
• dc.contributor.author Anderberg, Sophia
• dc.date.accessioned 2022-02-09T13:23:02Z
• dc.date.available 2022-02-09T13:23:02Z
• dc.date.issued 2021
• dc.description.abstract The goal of our research was to assess whether the observation about deceptive texts having a lower positive tone than truthful ones in terms of sentiment could become operative and be used for building a classifier in the particular case of fraudster’s letters written in Spanish. The data were the letters that CEOs address to company shareholders in their annual financial reports, and the task was to identify the letters of companies that committed financial misconduct or fraud. This case was challenging for two reasons: first, most of the research worked with spontaneous written or spoken texts, while these letters did not; second, most of the research in this area worked on English texts, while we validated the linguistic cues found as evidence of deception for Spanish texts. The results of our research confirm that an SVM trained with a bag-of-words model of frequent adjectives can achieve 81% accuracy because these adjectives bring the information about which positive or negative tone and which word combinations in a text turn out to be a characteristic of fraudster’s texts.
• dc.description.sponsorship This research was partially funded by the Spanish Plan Estatal de Investigación Científica y Técnica y de Innovación 2017–2020, PID2019-104512GB-I00
• dc.format.mimetype application/pdf
• dc.identifier.citation Bel N, Bracons G, Anderberg S. Finding evidence of fraudster companies in the CEO’s letter to shareholders with sentiment analysis. Information. 2021;12(8):307. DOI: 10.3390/info12080307
• dc.identifier.doi http://dx.doi.org/10.3390/info12080307
• dc.identifier.issn 2078-2489
• dc.identifier.uri http://hdl.handle.net/10230/52448
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Information. 2021;12(8):307.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-104512GB-I00
• dc.rights © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Fraud identification
• dc.subject.keyword Text classification
• dc.subject.keyword Deceptive text
• dc.subject.keyword Sentiment analysis
• dc.subject.keyword SVM
• dc.title Finding evidence of fraudster companies in the CEO’s letter to shareholders with sentiment analysis
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion