Article
Economics
Cathy Yi-Hsuan Chen, Wolfgang Karl Haerdle, Yegor Klochkov
Summary: This article introduces SONIC, a new high-dimensional network model, for integrating social media characteristics into an econometric framework. Theoretical study and simulations demonstrate that the matrix parameter can be estimated even when the sample size is smaller than the network size. The authors use natural language processing to quantify opinions dynamics among a select group of users on the StockTwits platform.
JOURNAL OF ECONOMETRICS
(2022)
Article
Computer Science, Information Systems
Zewen Wu, Jian Xu, Huaixiang Zhang, Qing Bao, Qing Sun, Changbeng Zhou
Summary: Searching for neighbors for a query node in a spatial network is a fundamental problem that has been explored extensively. This study introduces a new approach to tackle this problem by considering the neighbor searching problem at a community level. It is challenging to detect all qualified cohesive user communities in large spatial graphs, but the introduced algorithm successfully reduces the complexity of the task. Experimental results on real social networks confirm the superiority and effectiveness of the proposed solutions.
Review
Biochemistry & Molecular Biology
Monica Steffi Matchado, Michael Lauber, Sandra Reitmeier, Tim Kacprowski, Jan Baumbach, Dirk Haller, Markus List
Summary: The article provides an overview of state-of-the-art methods for inferring intra-kingdom interactions in microbial communities. It discusses common biases encountered in microbial profiles and mitigation strategies, as well as current limitations and the need for further method development.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Social Issues
Shengjie Hou, Xiang Zhang, Biyi Yi, Yi Tang
Summary: This paper conducts a content analysis of social media data regarding open source communities (OSCs) in China. Results show that while most people support the development of OSCs, there are objections that believe it will reduce China's innovation ability. The study suggests that the government should understand public attitudes and respond through social media, build more high-quality independent OSCs, establish a comprehensive evaluation and incentive system, and enhance copyright protection.
TECHNOLOGY IN SOCIETY
(2022)
Editorial Material
Computer Science, Theory & Methods
David Camacho, Ma Victoria Luzon, Erik Cambria
Summary: The exponential growth of social media and online social networks has impacted millions of people's daily lives and attracted interest from various research disciplines. This special issue focuses on Data Science and Artificial Intelligence techniques applied to social network analysis, presenting 12 selected papers out of a total of 65.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Psychology, Multidisciplinary
Qiusi Sun, Cuihua Shen
Summary: The study found that the likelihood of individual users reacting to trolls is influenced by various factors such as the valence of the trolling message, characteristics of the individual member, and patterns of past engagement with trolls from other community members.
COMPUTERS IN HUMAN BEHAVIOR
(2021)
Review
Computer Science, Artificial Intelligence
Sahar Yassine, Seifedine Kadry, Miguel-Angel Sicilia
Summary: Uncovering community structure has made significant advancements in explaining, analyzing, and forecasting behaviors and dynamics of networks in various fields. The adoption of online learning has raised questions about assessing learners' engagement, collaboration, and behaviors in new emerging learning communities.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
(2022)
Article
Physics, Multidisciplinary
Mengque Liu, Xia Zou, Jiyin Chen, Shuangge Ma
Summary: Online health communities provide important social support for people with health problems, including informational support, emotional support, and companionship. This study examines the differences in social support communication among people with different types of cancers and identifies differences in communication preferences and language use.
Article
Computer Science, Artificial Intelligence
Kangfei Zhao, Zhiwei Zhang, Yu Rong, Jeffrey Xu Yu, Junzhou Huang
Summary: This paper discusses the importance of finding critical users in social networks to maintain community cohesion and size. A neural network model called SCGCN is proposed to capture the hidden structure of the criticalness among node combinations that break the engagement of a specific social community. Experimental results show that SCGCN significantly improves the quality of the solution compared with the existing greedy algorithm.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Zeyin Chen, Xinyuan Lu, Heng Zhang
Summary: This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors. The study reveals that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated. The author cooperation network shows scale-free characteristics and the application of the QCA method is dominant in European and American countries.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Health Care Sciences & Services
Lamiece Hassan, Goran Nenadic, Mary Patricia Tully
Summary: This study analyzed all publicly available posts on the Twitter platform containing the hashtag #datasaveslives between September 1, 2016, and August 31, 2017. The research found that this hashtag-based social media campaign effectively encouraged a wide audience of stakeholders to disseminate positive examples of health research, supporting community building and bridging practices within and between interdisciplinary sectors.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Education & Educational Research
Yan Zhou, Nicolaas A. A. Bos, Agnes D. D. Diemers, Jasperina Brouwer
Summary: This study investigates the impact of students' formal networks on their informal peer relationships. The results show that students have more connections within the same learning community and fewer connections between different learning communities. Students with the same nationality are more likely to establish informal relationships. Longer duration in the same learning community increases the connections among students.
MEDICAL EDUCATION ONLINE
(2023)
Article
Energy & Fuels
Ancuta-Mihaela Aciu, Claudiu-Ionel Nicola, Marcel Nicola, Maria-Cristina Nitu
Summary: Power transformers are crucial in electrical systems, and monitoring their conditions has become increasingly important. Techniques such as dissolved gas analysis and furan compounds analysis are used to achieve a complete characterization of the oil-paper insulation conditions. A new approach based on the complementarity between analyzing dissolved gases and furan compounds in transformer oil has been proposed for identifying different faults, especially in cases of multiple faults.
Article
Engineering, Civil
Balazs Varga, Tamas Tettamanti
Summary: Road traffic simulation is becoming increasingly important due to the complexity and diversity of traffic. This paper proposes a novel mesoscopic traffic simulation framework that can be applied at any network level. The model can handle different types of road links and allows for analysis of traffic congestion and bottlenecks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Di Jin, Xiaobao Wang, Dongxiao He, Jianwu Dang, Weixiong Zhang
Summary: The study discusses the issues of community detection in real networks and proposes a new Bayesian probabilistic approach to address these challenges. By exploring the correlation between communities and topics, the new method aims to discover link communities and extract semantically meaningful community summaries simultaneously. Experimental results demonstrate the effectiveness of the new approach and its ability to provide rich explanations through multiple topical summaries per community if desired.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Physics, Multidisciplinary
Vesa Kuikka, Daniel Monsivais, Kimmo K. Kaski
Summary: The study utilized a model of influence spreading to analyze mobile phone call data and revealed the relationship between social relationship strength and network structure, as well as changes in social behavior among different age groups and genders. By analyzing influence centrality measures and betweenness centrality measures, characteristics of influence spreading under different scenarios were uncovered.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Review
Computer Science, Information Systems
Jaqueline Faria de Oliveira, Humberto Torres Marques-Neto, Marton Karsai
Summary: The study shows that people are more likely to adopt retweets than hashtags in online social networks. The adoption behavior is influenced by topics and aggregation levels, and new influencing neighbors can effectively trigger adoptions.
SOCIAL NETWORK ANALYSIS AND MINING
(2022)
Article
Multidisciplinary Sciences
Michele Tizzoni, Elaine O. Nsoesie, Laetitia Gauvin, Marton Karsai, Nicola Perra, Shweta Bansal
Summary: This study provides a set of practical and methodological recommendations to address socioeconomic vulnerabilities in epidemic models.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Julia Koltai, Orsolya Vasarhelyi, Gergely Rost, Marton Karsai
Summary: This study records contact matrices through online and phone surveys to understand the changing social mixing patterns. Using census data and representative samples, researchers develop a reconstruction method to obtain more accurate contact matrices and provide crucial data for epidemic models.
SCIENTIFIC REPORTS
(2022)
Article
Mathematics, Interdisciplinary Applications
Rafiazka Millanida Hilman, Gerardo Iniguez, Marton Karsai
Summary: Urban areas are places where people with diverse socioeconomic backgrounds gather, and their mobility patterns are influenced by their socioeconomic status. People tend to visit places that match their socioeconomic class, which contributes to socioeconomic stratification and urban segregation. The study found that there are clear signs of stratification in the mobility patterns of the twenty largest cities in the United States, with people mostly visiting places within their own socioeconomic class.
Review
Health Care Sciences & Services
Liam Cresswell, Lisette Espin-Noboa, Malia S. Q. Murphy, Serine Ramlawi, Mark C. Walker, Marton Karsai, Daniel J. Corsi
Summary: This study aims to analyze the volume and tone of English language tweets related to cannabis use during pregnancy from 2012 to 2021, and construct a qualitative profile of supportive and opposing posters. The findings of this study will help public health agencies and healthcare providers evaluate the information patients may receive and counteract misinformation, thus assisting expecting families in making informed choices.
JMIR RESEARCH PROTOCOLS
(2022)
Article
Multidisciplinary Sciences
Kareem A. Wahid, Brennan Olson, Rishab Jain, Aaron J. Grossberg, Dina El-Habashy, Cem Dede, Vivian Salama, Moamen Abobakr, Abdallah S. R. Mohamed, Renjie He, Joel Jaskari, Jaakko Sahlsten, Kimmo Kaski, Clifton D. Fuller, Mohamed A. Naser
Summary: This data descriptor presents a dataset of head and neck cancer patients, including manually segmented CT images of skeletal muscle and adipose tissue, as well as additional clinical demographic data relevant to body composition analysis. These data are valuable for studying sarcopenia and body composition analysis in patients with head and neck cancer.
Article
Computer Science, Artificial Intelligence
Vesa Kuikka, Henrik Aalto, Matias Ijas, Kimmo K. Kaski
Summary: Efficient algorithms are needed to model interactions on complex networks. This paper discusses different transmission and spreading processes and their interrelations, and presents two pseudo-algorithms. The first algorithm describes social interactions, while the second algorithm is for specific forms of information transmission and epidemic spreading.
Article
Physics, Multidisciplinary
Jan E. Snellman, Rafael A. Barrio, Kimmo K. Kaski, Maarit J. Kaepylae
Summary: In this study, a dynamic agent-based model is presented to investigate the interplay between the socio-economy and SEIRS-type epidemic spreading over a geographical area. The results reveal that the compliance of the population with government recommendations has the most drastic effect on the epidemic spreading.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Applied
Laetitia Gauvin, Mathieu Genois, Marton Karsai, Mikko Kivelae, Taro Takaguchi, Eugenio Valdano, Christian L. Vestergaard
Summary: This article discusses the importance and challenges of using randomized reference models (RRMs) in analyzing network systems and proposes a unified framework for understanding and utilizing these models.
Article
Oncology
Jaakko Sahlsten, Kareem A. Wahid, Enrico Glerean, Joel Jaskari, Mohamed A. Naser, Renjie He, Benjamin H. Kann, Antti Makitie, Clifton D. Fuller, Kimmo Kaski
Summary: This study systematically investigated the impact of available defacing algorithms on head and neck cancer (HNC) organs at risk (OARs). Most defacing methods were not able to produce usable images, while mask_face, fsl_deface, and pydeface failed to remove the face for a significant percentage of subjects. The results suggest that the original data has a significant impact on the performance of the HNC OAR auto-segmentation model.
FRONTIERS IN ONCOLOGY
(2023)
Article
Computer Science, Information Systems
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Sarkka, Leo Karkkainen, Kustaa Hietala, Kimmo K. Kaski
Summary: Automatic classification of diabetic retinopathy using deep neural networks has been widely studied, but uncertainty estimation is still a challenge. This study presents novel results for 9 Bayesian neural networks (BNNs) by systematically investigating clinical and benchmark datasets with different classification schemes. A new uncertainty measure based on entropy is derived from the connection with classifier risk. The findings show that the proposed uncertainty measure improves performance on benchmark datasets, while its effect on the clinical dataset depends on the classification scheme.
Article
Oncology
Nicolette Taku, Kareem A. Wahid, Lisanne V. van Dijk, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Clifton D. Fuller, Mohamed A. Naser
Summary: This single-center study demonstrates the successful automation of lymph node segmentation for patients with HPV-OPC using a deep learning convolutional neural network (DL-CNN). Further studies are needed to validate its role in the larger radiation oncology treatment planning workflow.
CLINICAL AND TRANSLATIONAL RADIATION ONCOLOGY
(2022)
Article
Physics, Fluids & Plasmas
Arash Badie-Modiri, Abbas K. Rizi, Marton Karsai, Mikko Kivela
Summary: The event graph representation of temporal networks can be mapped to a directed percolation problem. Our analysis showed that the critical percolation exponents characterizing the temporal network are not sensitive to network heterogeneities and can recover known scaling exponents.
Article
Physics, Multidisciplinary
Arash Badie-Modiri, Abbas K. Rizi, Marton Karsai, Mikko Kivela
Summary: Connectivity and reachability on temporal networks have been important areas of study in complex systems. This paper addresses the problem of describing temporal network reachability using percolation theory and shows that limited-waiting-time reachability displays a directed percolation phase transition in connectivity. This result allows for the estimation of critical percolation properties of spreading processes on temporal networks and has practical implications for real temporal networks.
PHYSICAL REVIEW RESEARCH
(2022)