Insights Discovery through Hidden Sentiment in Big Data: Evidence from Saudi Arabia’s Financial Sector

Park, Young-Eun; Javed, Yasir

doi:10.13106/jafeb.2020.vol7.no6.457

Cited by 4 publications

(4 citation statements)

References 26 publications

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“…Still, some studies were empirical papers focused on one business type [11] [35] or one business size [36] [13], applying a detection model with successful results. However, the application of big data and ML in the Saudi business research domain was focused on marketing [38] and finance [39] but never on accounting. On the other hand, accounting professionals have been using ML models, especially in some audit procedures has been employed in accounting firms.…”

Section: E the Case Of Saudi Arabiamentioning

confidence: 99%

CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies

Bineid,

Beloff,

White

et al. 2023

Annals of Computer Science and Information Systems

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Global financial scandals have demonstrated the harmful impact of creative accounting, a practice where managers creatively manipulate financial reports to conceal a company's actual performance and influence stakeholders' decision-making. Studies showed that Saudi-listed companies use it in preparing financial statements. Despite posing a significant risk to the Saudi financial market, detecting it using ordinary auditing procedures remains challenging. Big data analytics has provided practical applications in auditing, and recently, the employment of Deep Learning in fraud detection has delivered remarkably accurate results. Still, limited research has considered it in detecting creative accounting. This study proposes a novel framework using a hybrid learning approach. It suggests training on a simulated dataset of financial statements prepared (i.e., deliberately manipulated) based on financial statements available in the literature for supervised learning. It is then tested on real-world financial reports from the Saudi Open Data and Saudi Statistics. Our framework contributes to the literature with a new governing approach to limit creative accounting and improve financial reporting quality.

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Section: E the Case Of Saudi Arabiamentioning

confidence: 99%

CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies

Bineid,

Beloff,

White

et al. 2023

Annals of Computer Science and Information Systems

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“…Due to the popularity of opinion-rich resources, scholars across various disciplines such as politics (Chen et al, 2010;Yano & Smith, 2010), marketing (Liu et al, 2007), public opinion (O'Connor et al, 2010, and business (Hegde et al, 2015;Park & Javed, 2020) have worked out different approaches and methods for examining people's opinions and sentiments automatically to help in making a decision and revisiting current policies. These approaches and methods are commonly grouped under the generic term of 'social media analytics' which focuses on the way social media contents are used to offer a qualitative analysis of particular issues across various domains (Figure 2).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

A Computational-Augmented Critical Discourse Analysis of Tweets on the Saudi General Entertainment Authority Activities

Altohami¹,

Omar²

2022

WJEL

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This study used both computational tools in the form of a machine learning predictive model (Support Vector Machine) and a critical discourse analysis model (Van Dijk’s ideological square model) (Van Dijk, 1993, 2008, 2009) to fulfill three objectives: (1) clustering the Saudis’ Twitter-based opinions and sentiments regarding the entertaining and recreational activities run by the Saudi General Entertainment Authority (GEA); (2) offering empirical evidence on how computational linguistic methods could be implemented for offering a reliable conceptual framing of such opinionated big data; and (3) outlining the central themes generating ideologically motivated polarity in Saudi public opinion and the macrostrategies through which this polarity is textually instantiated and actualized. Toward fulfilling these objectives, we designed a purpose-built corpus of 9378 tweets based on five trending hashtags, covering the period between 2020 and 2022. Findings affirmed the efficacy of synergizing the Support Vector Machine model and the ideological square model in clustering and interpreting the target tweets. Based on the output discourse features and thematization of the tweets, two main groups with different ideologically motivated perspectives were identified. This ideological polarity was achieved through the use of two macrostrategies: positive self-presentation and negative other-presentation. These findings may prompt policymakers to reconsider current (mis)practices in order to achieve long-term sustainable development goals.

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“…This study tries to test the relationship between social and financial performance, in Saudi companies toward the objectives of Saudi vision 2030. With this objective, we cite the contributions of Peng et al (2009), Dhiab and Dkhili (2019), Park andJaved (2020), andVachon (2010).…”

Section: Literature Reviewmentioning

confidence: 99%

The relationship between social and financial performance with the objectives of the kingdom vision (2030)

Dkhili¹,

Dhiab²

2021

Int. j. adv. appl. sci.

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The objective of this paper is the study of the link between social and financial performance and the objectives of the Kingdom's Vision 2030. The methodological tool of this contribution tries to measure the effect of social and financial performance and the objectives of the Kingdom's Vision 2030. The main purpose of the research is focused on the empirical approach justified by the use of a linear model. The paper presents the results of an empirical analysis that showed a positive effect of social and financial performance on the objectives of the Kingdom's Vision 2030. The results found suggest that size, risk, and sector do not moderate the relationship between social responsibility and financial performance. The results showed a positive impact between social and financial performance with the objectives of the Kingdom Vision (2030) and implied that social and financial performance has a positive and significant relationship with the Kingdom Vision (2030). The results of the research can be useful for companies to promote the social and financial performance for a good realization of the Kingdom Vision (2030) and provide information to take the necessary policy suggestions to maintain the social performance and limit the average of financial performance.

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Insights Discovery through Hidden Sentiment in Big Data: Evidence from Saudi Arabia’s Financial Sector

Cited by 4 publications

References 26 publications

CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies

CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies

A Computational-Augmented Critical Discourse Analysis of Tweets on the Saudi General Entertainment Authority Activities

The relationship between social and financial performance with the objectives of the kingdom vision (2030)

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