Article
Computer Science, Artificial Intelligence
Manal El Akrouchi, Houda Benbrahim, Ismail Kassou
Summary: In a highly competitive business environment, competitive intelligence is crucial for companies to monitor competitors and predict future opportunities and risks. Weak signal detection, particularly with the use of techniques like LDA, has become a prominent research field in response to this need for automation in detecting early warning signs.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Public, Environmental & Occupational Health
Linh Phuong Doan, Long Hoang Nguyen, Pascal Auquier, Laurent Boyer, Guillaume Fond, Hien Thu Nguyen, Carl A. Latkin, Giang Thu Vu, Brian J. Hall, Cyrus S. H. Ho, Roger C. M. Ho
Summary: This study found that research on social networks in the field of HIV/AIDS is developing rapidly, with social networks playing an important role in HIV prevention, treatment, and care. It is necessary to improve research capacity through regional collaborations to reduce the HIV burden in low- and middle-income countries.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Artificial Intelligence
Dejian Yu, Bo Xiang
Summary: Artificial Intelligence (AI) has significantly impacted various aspects of social life. This study analyzed 177,204 documents published from 1990 to 2021 in AI research and used the LDA model to extract 40 topics from the abstracts. The study identified 7 subfields in the AI field and aggregated the results to understand research characteristics from different perspectives. These findings are valuable for researchers and institutions in selecting research directions and for newcomers to comprehend the dynamics of the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sakshi, Vinay Kukreja
Summary: This study provides an organized review of the current literature and trends in mathematical expression recognition (MER). It identifies five major research areas and ten research trends in this field. The segmentation and classification procedures are found to be the leading research area, while contextual and graph-based recognition is the most popular trend. The study also discovers attention and deep networks as emerging trends that require further exploration from the MER research community.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Yazwand Palanichamy, Mehdi Kargar, Hossein Zolfagharinia
Summary: Understanding the trends, topics, and developments in environmental science and engineering (ESE) research is crucial for addressing environmental issues. This study used a topic modeling computational text analysis method to analyze the composition of topics and regional differences in 3572 articles from 2005 to 2019, uncovering general research trends and different focuses of research communities from various countries.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Business
Ivan Savin, Ingrid Ott, Chris Konop
Summary: By utilizing topic modeling techniques, this study analyzes the trends and topics in robotic patents, matching them to service robotics based on external reference texts. This approach not only confirms previous findings but also offers new insights into the content and development stages of application areas in service robotics.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Green & Sustainable Science & Technology
Hosang Jung, Boram Kim
Summary: The analysis found that the target field of asset management has expanded, while the main activities of asset management remain limited to several popular activities such as life cycle cost analysis and reliability analysis. Some implications and future research directions are also discussed.
Article
Business
Paola Bongini, Francesco Osborne, Alessia Pedrazzoli, Monica Rossolini
Summary: This study analyzes the content of white papers in security token offerings (STOs) based on blockchain technology and identifies nine topics through latent Dirichlet allocation (LDA) topic modeling. The study finds that energy and green issues and technology in the healthcare industry are significant topics related to campaign success.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Computer Science, Artificial Intelligence
Bishal Sainju, Chris Hartwell, John Edwards
Summary: Understanding employees' values, motivations, and factors of satisfaction is crucial for human resource management. By analyzing employee reviews using techniques like Structural Topic Modeling, companies can identify key aspects affecting employee satisfaction and turnover, and make informed decisions to enhance employee experience. Management and monetary benefits are found to be significant factors in employee satisfaction and turnover, with differences in emphasis across industries such as retail and technology sectors.
DECISION SUPPORT SYSTEMS
(2021)
Article
Business, Finance
Ezzedine Ghlamallah, Christos Alexakis, Michael Dowling, Anke Piepenbrink
Summary: This study provides a comprehensive structure to research on Islamic economics and finance through probabilistic topic modeling, identifying 11 topics that cover economic, finance, and morality issues. The analysis can be used to guide ongoing research agendas in this field and highlight the differences between Islamic and conventional approaches to economics and finance research.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2021)
Article
Energy & Fuels
Anna Pamula, Zbigniew Gontar, Beata Gontar, Tetiana Fesenko
Summary: This paper presents a comprehensive analysis of public procurement documents in the domain of university buildings, focusing on their transformation towards more efficient energy consumption. Latent Dirichlet Allocation (LDA) is used for topic modeling to understand the key areas of focus in the procurement documents from 2020 to 2022. The analysis reveals a shift in emphasis towards the adoption of energy-saving technologies and broader sustainability initiatives, while highlighting potential areas for improvement in procurement practices related to cooling and heating systems.
Article
Multidisciplinary Sciences
Leacky Muchene, Wende Safari
Summary: The study utilized a two-stage topic modeling approach, using Latent Dirichlet Allocation for per-document topic probability derivation in the first stage, and hierarchical clustering with Hellinger distance for final topic cluster discovery in the second stage. The analysis revealed dominant research themes at the University of Nairobi, including HIV and malaria research, agricultural and veterinary services research, as well as cross-cutting themes in humanities and social sciences, demonstrating the effectiveness of hierarchical clustering in organizing discovered latent topics into homogeneous clusters.
Article
Business
Edoardo Crocco, Elisa Giacosa, Dorra Yahiaoui, Francesca Culasso
Summary: This study investigates the implications of user-generated content on both reward-based and equity-based crowdfunding platforms, highlighting the importance of crowd inputs for open and user innovation. It also provides an overview of the key differences between reward-based and equity-based crowdfunding platforms in terms of crowd inputs. The study contributes to the innovation and crowdfunding literature by bridging gaps and providing empirical evidence for pre-existing exploratory research.
EUROPEAN JOURNAL OF INNOVATION MANAGEMENT
(2022)
Article
Multidisciplinary Sciences
Yeo Jin Jung, Youngmin Kim
Summary: In recent decades, there has been a significant growth in incorporating sustainability into marketing. This study examines the trends in sustainability and marketing by analyzing 2147 articles published between 2010 and 2020. The research shows a shift towards a focus on environmental and industrial technology in the field of sustainability and marketing.
Article
Economics
Christos Alexakis, Michael Dowling, Konstantinos Eleftheriou, Michael Polemis
Summary: The study demonstrates the benefits of machine learning in textual analysis and how probabilistic methods can be used to identify shared topics in documents. By analyzing 1160 articles on computational economics, the research reveals 18 overall topics, providing a new research structure for computational economists.
COMPUTATIONAL ECONOMICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Yuan-Wei Du, Ying-Ming Wang, Man Qin
COMPUTERS & INDUSTRIAL ENGINEERING
(2018)
Article
Oceanography
Man Qin, Xinru Wang, Yuanwei Du, Xiaole Wan
Summary: The study analyzed the scale, nature and function of national marine ranching in China from 2015 to 2019, identifying issues in the current layout and spatial variation characteristics. Factors such as resource difference, scientific and technological input, and economic development levels significantly influence the spatial distribution of marine ranching.
OCEAN & COASTAL MANAGEMENT
(2021)
Article
Environmental Studies
Man Qin, Qiaoan Tao, Yuanwei Du
Summary: Modern marine ranching construction is an important measure to achieve efficient output of marine environmental protection and fishery resources. This study analyzed the administrative and social processes of marine ranching policy implementation and developed a multientity operating framework for national marine ranching demonstration zones. By exploring key elements affecting project performance, the study identified key paths leading to high or low performance.
Article
Fisheries
Man Qin, Xinru Wang, Yuanwei Du
Summary: This study examined the risks of marine ranching and identified key risk factors to assist operators in making decisions to reduce risks.
Article
Environmental Studies
Man Qin, Mingxue Sun
Summary: Countries worldwide are seeking solutions to enhance the value of fishery production and improve environmental conditions, with marine ranching being an important means to develop the marine economy from a human perspective while balancing the needs of marine ecology. The development of marine ranching in China has been rapid, but there are challenges in achieving high ecological efficiency.
Article
Environmental Studies
Man Qin, Caixuan Yue, Yuanwei Du
Article
Biodiversity Conservation
Yongcui Lan, Jinliang Wang, Qianwei Liu, Fang Liu, Lanfang Liu, Jie Li, Mengjia Luo
Summary: This study focuses on the five major plateau lake basins in central Yunnan, China, and constructs an ecological security pattern using the source-resistance surface-corridor-pinch point framework. The study simulates land use/cover change in the region and identifies early warning regions where future urban expansion poses a threat to current ecological source areas and corridors.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Pingping Huang, Feng Zhao, Bailing Zhou, Kuidong Xu
Summary: This study investigates the distribution of benthic microeukaryotes in the China Seas and finds that they can stride over the ecological barrier of 32 degrees N. The study also highlights the significant influence of depth, temperature, and latitude on communities in the China Seas.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Federico Morelli, Yanina Benedetti, Jesse Stanford, Leszek Jerzak, Piotr Tryjanowski, Paolo Perna, Riccardo Santolini
Summary: Species distribution models (SDMs) are numerical tools used for predicting species' spatial distribution. This study found that ecological characteristics, such as habitat specialization, play a role in improving the accuracy of SDMs.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Xiaoxuan Wu, Hang Liu, Wei Liu
Summary: Global climate change, urbanization, and economic development have increased the need for sustainable human development, urban ecological governance, and low-carbon energy transformation. This study analyzes the green ecological transition in Chengdu based on panel data from 2010 to 2020, exploring its spatiotemporal evolution and key factors. The results show an overall upward trend in Chengdu's green ecological development and positive spatial autocorrelation in certain districts.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Castaldi Simona, Formicola Nicola, Mastrocicco Micol, Morales Rodriguez Carmen, Morelli Raffaella, Prodorutti Daniele, Vannini Andrea, Zanzotti Roberto
Summary: Sustainable agricultural practices are increasingly important for global and national environmental policies and economy. This study compared the sustainability of grape production under integrated and organic management using multiple indicators. The results showed that organic management was more beneficial for most environmental aspects of the agroecosystem compared to integrated management, without affecting grape yield.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Gaia Vaglio Laurin, Alexander Cotrina-Sanchez, Luca Belelli-Marchesini, Enrico Tomelleri, Giovanna Battipaglia, Claudia Cocozza, Francesco Niccoli, Jerzy Piotr Kabala, Damiano Gianelle, Loris Vescovo, Luca Da Ros, Riccardo Valentini
Summary: Phenology monitoring is important for understanding forest functioning and climate impacts. This research compares the phenological behavior of European beech forests using Tree-Talker (TT+) and Sentinel 2 satellite data. The study finds differences in the information derived by the two sensor types, particularly in terms of season length, phenology changepoints, and leaf period variability. TT+ with its higher temporal resolution demonstrates precision in capturing the phenological changepoints, especially when satellite image availability is limited.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Huanhuan Pan, Ziqiang Du, Zhitao Wu, Hong Zhang, Keming Ma
Summary: The land use and cover changes resulting from coal mining activities and ecological restoration have had a significant impact on ecosystem services in mining areas. This study investigates the relationship between ecosystem services and land use intensity in coal mining areas, emphasizing the importance of understanding this interdependence for balanced human-land system development. The research examines the evolving relationship across different reclamation stages in Shanxi, China, using a coupling coordination degree model. The findings suggest the need for timely and judicious reclamation of coalfields, considering the land's bearing capacity.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Jingjuan He, Yijun Shi, Lihua Xu, Zhangwei Lu, Mao Feng
Summary: This study examines the spatial interplay between changes in the blue-green spatial distribution and modifications in land surface temperature grades in Shanghai. The findings reveal that the transformation of the blue-green spatial pattern differs between different sectors of the city, and the impact on the thermal environment varies spatially.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Yi Xu, Di Zhang, Junqiang Lin, Qidong Peng, Xiaohui Lei, Tiantian Jin, Jia Wang, Ruifang Yuan
Summary: This study analyzed the response relationship between phytoplankton growth and water environmental parameters in the Middle Route of the South-to-North Water Diversion Project in China using long-term monitoring data and machine learning models. The results revealed the differences between monitoring sites and identified the key parameters that affect phytoplankton growth.
ECOLOGICAL INDICATORS
(2024)