Analysis of Financial Speculators’ Herd Behaviour Impact on the Instability of Commodity Prices. Evidence from Weekly WTI Crude Oil Market Data Using Uncertainty Theory (2018–2024)... by Tebache Djamal, Chetbani Saida

“…Methodology: The authors approach relies on introducing uncertainty theory and VNM1 expected utility, rather than relying on ARDL modelling and dummy variables over the period 2018–2024, using weakly data provided by the CFTC. Results: Our findings indicate the significant effect of variables, buying and selling positions of financial speculators and the war in Ukraine, namely increasing mimetic behavior of traders’ and financial speculators’ impact on prices. …”
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Exposure to political violence and health risk behaviors of Palestinian youth by Rita T. Karam, Wenjing Huang, Umaiyeh Khammash, Peter Glick, Mohammed Shaheen, Ryan Andrew Brown, Sebastian Linnemayr, Salwa Massad

“…Methods We employed structural equation modeling using a 2014 nationally representative data from the Palestinian Youth Health Risk Study to examine the factors associated with engagement of youth ages 18–24 (N = 1449) in risky behaviors. …”
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Influencing factors of maternal online health information-seeking behavior by Huajie Xu, Yanping Zhou, Xiaotong Wang

“…Using SPSS software to empirically analyze the influence of different influencing factors on maternal online health information searching behavior.ResultsPerceived usefulness mediated between the Internet information quality and online health information-seeking behavior, accounting for 59.46% of the variance. …”
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Predicting User Purchases From Clickstream Data: A Comparative Analysis of Clickstream Data Representations and Machine Learning Models by A. Aylin Tokuc, Tamer Dag

“…Unlike prior research, which typically focuses on single representations, our approach combines aggregated session-level summaries with granular, sequential user actions to capture both long-term and short-term behavioral patterns. Through comprehensive experimentation, we compared multiple machine learning models, including LightGBM, decision trees, gradient boosting, SVC, and logistic regression, using real-world e-commerce clickstream data. …”
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The Influence of Consumer Behavior And Interest on The Purchase Decision of Second-Hand Clothing in Lubuk Pakam City by Rifki Maulana, Reni Ria Armayani Hasibuan, Juliana Nasution

“…The data analysis used is multiple linear regressions. …”
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IndetermSoft Set for Digital Marketing Effectiveness Evaluation Driven by Big Data Based on Consumer Behavior by Tao Shen, Chunmei Mao

“…This study proposes the multi-criteria decision-making (MCDM) methodology for Digital Marketing Effectiveness Evaluation Driven by Big Data Based on Consumer Behavior. This study uses two MCDM methods such as the Entropy method to compute the criteria weights and the MARCOS method to rank the alternatives. …”
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A study on in-depth perception of customer behavior in digital business halls based on multimodal data integration by Wei Cui, Bo Chen, Wei Ge

“…Using naive Bayes classification method, customer behavior is classified into three categories based on the characteristics of multimodal data: basic information, behavioral information, and service information. …”
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Implementation of the Unified Theory of Acceptance and Use of Technology (UTAUT) 3 on the Sharia Bank Customer Behavior in Using Mobile Banking by Nurfia Sintia Daulay, Arbanur Rasyid, Utari Evy Cahyani, Rizki Mulia Lubis

“…This study examines the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, and personal innovation on behavioral intention and user behavior. Using a quantitative approach, 200 respondents were selected through random sampling, and data were analyzed with Structural Equation Modeling-Partial Least Squares (SEM-PLS) via WarpPLS 7.0. …”
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Comparing the accuracy of machine learning methods for classifying wild red deer behavior based on accelerometer data by Benjamin Bar-Gera, Pia Anderwald, Alina L. Evans, Thomas Rempfler, Claudio Signer

“…Combined with classification models, data collected by accelerometers on a collar can be used to determine an animal’s behaviors. …”
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Behavioral Economics in EU: Meat, ESG, Macroeconomics by Panagiotis Karountzos, Nikolaos T. Giannakopoulos, Damianos P. Sakas, Kanellos Toudas

“…This study examines the impact of macroeconomic and ESG (Environmental, Social, and Governance) factors on meat consumption in EU countries through a behavioral economics framework. Using panel data from 27 EU countries (2000–2021), the analysis applies Fixed Effects (FE), Random Effects (RE), and Generalized Estimating Equations (GEE) models to identify key drivers of meat consumption. …”
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A Systematic Review on the Use of Big Data in Tourism by Jafar Ahangaran, Abbas Sadeghnia

“…One significant aspect is the analysis of consumer behavior, market dynamics, supply and delivery processes, and customer communication using data obtained from the digitization process (Youssef, 2021). …”
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Behavioral Motivation and Influencing Factors of Graduate Students Using AIGC Tool: An Empirical Analysis Based on Questionnaire Survey by Yijia WAN, Liping GU

“…[Results/ [Conclusions] Functional value, use value and emotional value in the tool aspect, individual innovation in individual aspect and social influence in environmental aspect have significant positive effects on graduate students' willingness to use AIGC tools, and indirectly affect their use behavior. …”
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Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study by Chuqin Li, Alexis Jordan, Yaorong Ge, Albert Park

“…ConclusionsWe were able to observe people’s eating habits using social media data to investigate the effects of COVID-19 on dietary behaviors. …”
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Analysis of College Students’ Consumption Behavior Data Based on Fractional-Order Firefly Optimization Clustering Algorithm by Xiang Meng, Qi He, Yanhua Dong, Hongyu Sun

“…Data mining-based student consumption behavior analysis is an important part of smart campus construction, which could find students’ eating patterns and consumption levels. …”
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Designing transit routes based on vehicle routing behavior determined through location-based services data by Yuhan Tang, Abdullah Alhadlaq, Alben Rome Bagabaldo, Marta C. Gonzalez

“…This rich dataset is combined with GTFS data to analyze vehicle routing behavior and identify transit supply gaps. …”
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Movement behaviors and cardiorespiratory fitness – a cross-sectional compositional data analysis among German adults by Alexander Roosz, Martin Bahls, Sabina Ulbricht, Antje Ullrich, Anne Obst, Beate Stubbe, Ralf Ewert, Sabine Kaczmarek, Till Ittermann, Marcus Dörr, Lisa Voigt

“…Linear regression models applying compositional data analysis were used to examine associations of proportions of movement behaviors (exposure) with parameters derived during cardiopulmonary exercise testing (outcome) normalized for body weight and stratified by sex. …”
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From digital traces to public vaccination behaviors: leveraging large language models for big data classification by Yoo Jung Oh, Muhammad Ehab Rasul, Emily McKinley, Christopher Calabrese

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Method for Preprocessing Video Data for Training Deep-Learning Models for Identifying Behavioral Events in Bio-Objects by Marina Barulina, Alexander Andreev, Ilya Kovalenko, Ilya Barmin, Eduard Titov, Danil Kirillov

“…This article proposes a method for preprocessing data to identify the behavior of a bio-object, a clear example of which is experiments on laboratory animals with the collection of video data. …”
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RESEARCH TECHNIQUE OF UNMANNED AERIAL VEHICLE DYNAMIC BEHAVIOR IN GROUND CONDITIONS WITH ACCOUNT OF FLIGHT EXPERIMENT DATA by V. N. Akimov, D. N. Ivanov, S. G. Parafes'

“…The authors of this article propose a research technique of unmanned aerial vehicle (UAV) dynamic behavior in ground conditions with account of flight experiment data. …”
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Clustering analysis of vehicle traveling and parking behavior based on license plate recognition data: Suzhou case by Kexin Wang, Xiang Wang, Xiangxi Liu, Yutong Wang

“…With the advent of big data technology and intelligent transportation systems, accurately identifying traffic demands and profiling traveler behavior has become practical. …”
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