Article
Education & Educational Research
Olga Agatova, Alexander Popov, Suad Abdalkareem Alwaely
Summary: This paper examines the unique aspects of utilizing Big Data technology in education. The study suggests that the education sector is ambitiously adopting Big Data technology, both online and offline. The research findings indicate that students prefer using apps over cloud technology when dealing with Big Data.
INTERACTIVE LEARNING ENVIRONMENTS
(2022)
Article
Computer Science, Information Systems
Noaman M. Ali, Abdullah Alshahrani, Ahmed M. Alghamdi, Boris Novikov
Summary: Sentiment analysis on social media and e-markets has become an emerging trend. In this research, we propose a clustering-based aspect term extraction model that outperforms existing models according to the test results.
Article
Operations Research & Management Science
Taiga Saito, Shivam Gupta
Summary: This study investigates the applications of big data and social media factors in financial management, proposing three models for revenue management, interest rate modeling, and high-frequency trading equity market modeling. The research highlights the importance of including social media factors in stochastic optimization models for financial management, as social media plays a significant role in product promotion and sentiment sharing among market participants.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Information Systems
Reguieg Hicham, Benallal Mohamed Anis
Summary: Process mining is a business process management technique used to extract value from process execution logs. This study proposes a distributed implementation based on the Spark framework for efficient scalable process discovery in big data scenarios. Experimental results demonstrate that the proposed approach achieves significant speed-up and scalability when dealing with large datasets and varying cluster sizes.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Review
Geochemistry & Geophysics
S. J. Arrowsmith, D. T. Trugman, J. MacCarthy, K. J. Bergen, D. Lumley, M. B. Magnani
Summary: Big Data Seismology, based on observations of inherently undersampled ground motion, is revolutionizing the field of seismology through new opportunities in earthquake processes understanding and resolving Earth structure. This review explores the development of new data-dense sensor systems, computing improvements, and new techniques and algorithms, and discusses the challenges and opportunities presented by Big Data Seismology. Recent scientific advances enabled by dense seismic data sets are also examined, highlighting the potential for significant progress in the field.
REVIEWS OF GEOPHYSICS
(2022)
Article
Green & Sustainable Science & Technology
Vinoth Kumar Ponnusamy, Padmanathan Kasinathan, Rajvikram Madurai Elavarasan, Vinoth Ramanathan, Ranjith Kumar Anandan, Umashankar Subramaniam, Aritra Ghosh, Eklas Hossain
Summary: The role of energy in achieving the Sustainable Development Goals is crucial, with smart grid and big data analytics playing a significant role in enhancing energy management practices for sustainability.
Article
Computer Science, Information Systems
Danda B. Rawat, Ronald Doku, Moses Garuba
Summary: Knowledge is derived from having access to information, which has become a crucial issue in today's information age. The use of big data in cybersecurity to protect assets, as well as its high value as a target, highlights the importance of understanding the inner workings of systems producing data in the current technological landscape.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Management
Zhaowei She, Turgay Ayer, Daniel Montanera
Summary: This paper analyzes a market design problem in Medicare Advantage (MA), and shows that big data alone cannot cure risk selection in the MA capitation program. The paper proposes a simple mechanism to address the risk selection problem induced by cross subsidization in MA.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Computer Science, Theory & Methods
Renu Sabharwal, Shah Jahan Miah
Summary: In recent years, there has been a significant increase in the usage of Big Data Analytics (BDA) in the industry. Despite the recognized need for BDA capability in organizations, few studies have effectively communicated an understanding of BDA capabilities, limiting our theoretical knowledge of using BDA in the organizational domain. This research explores past literature on the classification of BDA and its capabilities, and proposes a novel empirical research model to improve the effectiveness and enhance the usage of BDA applications in various Organizations.
JOURNAL OF BIG DATA
(2021)
Article
Business
Sabri Boubaker, Zhenya Liu, Yuhao Mu
Summary: This paper uses big data to perform descriptive and predictive analytics in the Chinese A-shares Market. The results show that the Instrumented Principal Component Analysis model performs well in both description and forecasting. The study also compares the performance of different sets of characteristics and concludes that sentiment analysis is dominant while fundamental analysis is also important. These findings can provide valuable insights for policymakers and assist investors in making effective investment decisions.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Review
Information Science & Library Science
Stefano Bresciani, Francesco Ciampi, Francesco Meli, Alberto Ferraris
Summary: This paper is the first systematic literature review on the interconnections between big data and co-innovation. Three thematic clusters were identified, focusing on the role of big data in knowledge creation, driving co-innovation processes through customer engagement, and its impact on co-innovation within service ecosystems. The study also presents eleven research propositions for further theoretical developments and managerial implementations in the field of BD-driven co-innovation.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2021)
Editorial Material
Energy & Fuels
Tracy H. Schloemer
Summary: The assessment of efficient and stable perovskite solar cells is challenging due to the vast potential parameter space. In this study, researchers use high-throughput screening to identify stable perovskites and propose a bilayer polymer contact that extends device stability to 1,450 hours under high-temperature conditions.
Review
Environmental Sciences
Keumseok Koh, Ayaz Hyder, Yogita Karale, Maged N. Kamel Boulos
Summary: This study conducted a systematic narrative review to understand the usage of big geospatial sensing data, ancillary data, and spatial data infrastructures in public health studies. The study found that geospatial big data has been inconsistently used in existing studies, with a focus on the public health field. The research also highlighted the importance of interdisciplinary collaboration to fully utilize geospatial big data in future public health studies.
Article
Chemistry, Analytical
Isidoro Lopez, Nicolas Le Poul
Summary: This paper provides a theoretical basis on electrochemical processes conducted at low temperature, discussing the effects of temperature decrease on thermodynamics, kinetics, and electron transfer reactions. It also focuses on the changes in different electrochemical methods at low temperature and discusses theoretical aspects of cyclic voltammetry for multiple electron-transfer reactions.
JOURNAL OF ELECTROANALYTICAL CHEMISTRY
(2021)
Review
Biochemistry & Molecular Biology
Madeline Alizadeh, Natalia Sampaio Moura, Alyssa Schledwitz, Seema A. Patil, Jacques Ravel, Jean-Pierre Raufman
Summary: Studying individual data types in isolation is limited in providing comprehensive answers, but multi-omics approaches can generate and integrate multiple data types to offer a holistic understanding of biological and disease processes. Gastroenterology and hepatobiliary research benefit from these approaches due to the interconnectedness of the GI tract, brain, immune and endocrine systems, and GI microbiome. The use of big data in multi-omic, multi-site studies allows for better investigations into the connections between organ systems and more accurate evaluations of interventions.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
