Application of Benford’s law in Data Analysis

Li, Feifei; Han, Sunyoung; Zhang, Hongyv; Ding, Jiaojiao; Zhang, Jianhua; Wu, Jianzhai

doi:10.1088/1742-6596/1168/3/032133

Cited by 13 publications

(5 citation statements)

References 11 publications

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“…The applications of Benford's law are diverse and can be found in various fields, including the following: Data quality assessment: Benford's law serves as a tool to assess the integrity and quality of data, ensuring its accuracy and identifying possible errors or anomalies that may require further investigation or correction [17,18]. 5.…”

Section: Benford's Lawmentioning

confidence: 99%

Benford’s Law and Perceptual Features for Face Image Quality Assessment

Varga

2023

Signals

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The rapid growth in multimedia, storage systems, and digital computers has resulted in huge repositories of multimedia content and large image datasets in recent years. For instance, biometric databases, which can be used to identify individuals based on fingerprints, facial features, or iris patterns, have gained a lot of attention both from academia and industry. Specifically, face image quality assessment (FIQA) has become a very important part of face recognition systems, since the performance of such systems strongly depends on the quality of input data, such as blur, focus, compression, pose, or illumination. The main contribution of this paper is an analysis of Benford’s law-inspired first digit distribution and perceptual features for FIQA. To be more specific, I investigate the first digit distributions in different domains, such as wavelet or singular values, as quality-aware features for FIQA. My analysis revealed that first digit distributions with perceptual features are able to reach a high performance in the task of FIQA.

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Section: Benford's Lawmentioning

confidence: 99%

Benford’s Law and Perceptual Features for Face Image Quality Assessment

Varga

2023

Signals

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“…According to BL the probability of the first digit being 1 is 30.1%, first digit being 2 is 17.6% and so on as shown in Table 1. Table 1 show both and first and second digit Benford's distribution, as gathered from [1], [2] and [16]. The probability of first digit is calculated using the formula:…”

Section: Benford's Lawmentioning

confidence: 99%

Application of Benford’s Law to Detect if COVID-19 Data is under Reported or Manipulated

Pahuja¹

2021

New Frontiers in Communication and Intelligent Systems

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Tackling of COVID-19 has been the prime concern for all the countries because of the virus’ deadly tenure across the globe. But an attempt to curb the virus requires an effective analysis of its spread. Falsified data is suspected by experts on account of policy-making, political strategies and fear handling. Benford’s law, which is an effective and widely used technique to detect fraud and fabrication, is employed and applied to data made available publicly, by the authorities, in an attempt to see if the data adheres to the Benford’s Law and if it is correctly reported or not. Benford’s law works well on exponential data and is compared to the initial growth data of the countries, but in case of control interventions an epidemic growth model is applied to the data and then goodness-of-fit test is conducted to see if Benford’s Law is satisfied for the selected three countries. Also, the level and rate of control is calculated to determine the deceleration in growth for each country.

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“…Keywords: agriculture, first digit test, first two-digit test, data validation, agricultural policy 2020), scientific cooperation network (Tošić & Vičič, 2021), epidemiology (Manrique-Hernandez et al, 2017;Parreño, 2023), COVID-19 (Balashov et al, 2021), supply chain management (Kraus & Valverde, 2014), and data analysis (Li et al, 2019), where it has been employed to detect irregularities, identify fraudulent activities, and assess the integrity of numerical datasets (Eckhartt & Ruxton, 2023).…”

Section: Introductionmentioning

confidence: 99%

Analyzing crop production statistics of the Philippines using the newcomb-benford law

Parreño

2023

Multidiscip. Sci. J.

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The agricultural sector plays a crucial role in the Philippines, contributing significantly to its food security and economic growth. However, the sector faces various challenges that hinder its productivity and growth. To address these challenges and promote sustainable agricultural practices, accurate and reliable crop production statistics are essential for informed decision-making and resource allocation. The Newcomb-Benford Law (NBL) provides a statistical distribution pattern for leading digits in numerical datasets, offering insights into data reliability. In this research study, we applied the NBL to analyze crop production statistics for major crops (rice, corn, coconut, sugarcane, banana, cassava, and pineapple) in the Philippines. We assessed the conformity of the datasets to NBL expectations and identified significant deviations, indicating potential data accuracy issues, collection method discrepancies, or reporting irregularities. Although these deviations do not conclusively suggest fraud, they underscore the need for meticulous data validation. The first two-digit test further strengthened the findings, providing a comprehensive understanding of dataset conformity. Transparent data collection and validation processes are crucial for trustworthy agricultural statistics, supporting effective policy-making and resource allocation. Future research should investigate the root causes of the deviations, explore data processing errors, and implement stringent data validation procedures. Additionally, expanding the analysis to include other crops and conducting comparative studies between regions and time periods would enhance data integrity and contribute to sustainable agricultural practices and food security in the Philippines.

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Application of Benford’s law in Data Analysis

Cited by 13 publications

References 11 publications

Benford’s Law and Perceptual Features for Face Image Quality Assessment

Benford’s Law and Perceptual Features for Face Image Quality Assessment

Application of Benford’s Law to Detect if COVID-19 Data is under Reported or Manipulated

Analyzing crop production statistics of the Philippines using the newcomb-benford law

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