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Journal articles on the topic 'Topic evolution networks'

Author: Grafiati

Published: 25 May 2024

Last updated: 28 July 2025

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1

Liang, Wei, Zixian Lu, Qun Jin, Yonghua Xiong, and Min Wu. "Modeling and Analyzing of Research Topic Evolution Associated with Social Networks of Researchers." International Journal of Distributed Systems and Technologies 7, no. 3 (2016): 42–62. http://dx.doi.org/10.4018/ijdst.2016070103.

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Research trends keep evolving along the time with certain trackable patterns. Mining academic literature and discovering the latent research trends evolution is an interesting and important problem. Few of previous studies focusing on academic topic evolution modeling have addressed the temporal topic evolution patterns. In addition, researchers' profile and their social networks are valuable complementary to the research trends tracking. In this study, to analyze the underlying research trends evolution along with the scientific collaborations of researchers, a novel temporal research trends

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Jensen, Scott, Xiaozhong Liu, Yingying Yu, and Staša Milojevic. "Generation of topic evolution trees from heterogeneous bibliographic networks." Journal of Informetrics 10, no. 2 (2016): 606–21. http://dx.doi.org/10.1016/j.joi.2016.04.002.

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Jung, Sukhwan, and Aviv Segev. "Analyzing the generalizability of the network-based topic emergence identification method." Semantic Web 13, no. 3 (2022): 423–39. http://dx.doi.org/10.3233/sw-212951.

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Topic evolution helps the understanding of current research topics and their histories by automatically modeling and detecting the set of shared research fields in academic publications as topics. This paper provides a generalized analysis of the topic evolution method for predicting the emergence of new topics, which can operate on any dataset where the topics are defined as the relationships of their neighborhoods in the past by extrapolating to the future topics. Twenty sample topic networks were built with various fields-of-study keywords as seeds, covering domains such as business, materi

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Liu, Yanni, Dongsheng Liu, and Yuwei Chen. "Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City." Complexity 2020 (June 4, 2020): 1–13. http://dx.doi.org/10.1155/2020/9789431.

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With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides

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Wang, Xiang Yang. "Hot Topic Detection in News Blog." Applied Mechanics and Materials 513-517 (February 2014): 1114–18. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1114.

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Topic detection in news blogs needs to carefully arrange the information and analyze the characteristics of topics. However, there are some difficulties for hot topic detection in blogs. On one hand, information overload and dynamic change of web pages are obstacles of information arrangement. On the other hand, there are different hotness evaluation norms for web topics. The proposed method first analyzes the characteristics of the news blog and recognizes the factors which can influence the evolution of a topic. Then a word network is constructed, and candidate topics are extracted from the

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Lee, Won Sang. "Analyzing the Evolution of Interdisciplinary Areas." Journal of Global Information Management 30, no. 1 (2022): 1–23. http://dx.doi.org/10.4018/jgim.304062.

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Recently, various new areas of research have been of great interest to researchers. As these areas are highly based on academic and industrial needs, it is necessary to examine the change and evolution in research. This study proposed a framework for identifying emerging areas and their evolution. The proposed framework suggests that latent Dirichlet allocation is applied to identify emerging topics and their networks in such interdisciplinary areas. The simulation for empirical network analysis was then applied to the identified topic networks to terminate continuous evolution. The proposed f

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Chen, Mo. "Research on Key Technology of Web Hierarchical Topic Detection and Evolution Based on Behaviour Tracking Analysis." International Journal of Computers Communications & Control 14, no. 3 (2019): 311–28. http://dx.doi.org/10.15837/ijccc.2019.3.3534.

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In the development background of today’s big data era, the research direction of Web hierarchical topic detection and evolution characterized by the semistructured or unstructured data has caught wide attention for academicians. This paper proposes an idea of Web hierarchical topic detection and evolution based on behaviour tracking analysis taking the network big data as the research object, and expounds main implementation methods, which include the instance analysis of the usage mode, the instance analysis of the seed, the set analysis of similar instance supporting the topics, the set anal

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Chen, Huarong, Yadong Wu, Huaquan Tang, et al. "Visual Analysis Method for Traffic Trajectory with Dynamic Topic Movement Patterns Based on the Improved Markov Decision Process." Electronics 13, no. 3 (2024): 467. http://dx.doi.org/10.3390/electronics13030467.

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The visual analysis of trajectory topics is helpful for mining potential trajectory patterns, but the traditional visual analysis method ignores the evolution of the temporal coherence of the topic. In this paper, a novel visual analysis method for dynamic topic analysis of traffic trajectory is proposed, which is used to explore and analyze the traffic trajectory topic and evolution. Firstly, the spatial information is integrated into trajectory words, calculating the dynamic trajectory topic model based on dynamic analysis modeling and, consequently, correlating the evolution of the trajecto

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Ali, Faizan, Eunhye (Olivia) Park, Junehee Kwon, and Bongsug (Kevin) Chae. "30 years of contemporary hospitality management." International Journal of Contemporary Hospitality Management 31, no. 7 (2019): 2641–65. http://dx.doi.org/10.1108/ijchm-10-2018-0832.

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Purpose This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing. Design/methodology/approach In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), a

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Zhang, Lan, Yuxuan Hu, Weihua Li, Quan Bai, and Parma Nand. "LLM-AIDSim: LLM-Enhanced Agent-Based Influence Diffusion Simulation in Social Networks." Systems 13, no. 1 (2025): 29. https://doi.org/10.3390/systems13010029.

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This paper introduces an LLM-Enhanced Agent-Based Influence Diffusion Simulation (LLM-AIDSim) framework that integrates large language models (LLMs) into agent-based modelling to simulate influence diffusion in social networks. The proposed framework enhances traditional influence diffusion models by allowing agents to generate language-level responses, providing deeper insights into user agent interactions. Our framework addresses the limitations of probabilistic models by simulating realistic, context-aware user behaviours in response to public statements. Using real-world news topics, we de

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Xu, Xiaoyan, Wei Lv, Beibei Zhang, Shuaipeng Zhou, Wei Wei, and Yusen Li. "A Novel Emerging Topic Identification and Evolution Discovery Method on Time-Evolving and Heterogeneous Online Social Networks." Complexity 2021 (August 26, 2021): 1–14. http://dx.doi.org/10.1155/2021/8859225.

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With the fast development of web 2.0, information generation and propagation among online users become deeply interweaved. How to effectively and immediately discover the new emerging topic and further how to uncover its evolution law are still wide open and urgently needed by both research and practical fields. This paper proposed a novel early emerging topic detection and its evolution law identification framework based on dynamic community detection method on time-evolving and scalable heterogeneous social networks. The framework is composed of three major steps. Firstly, a time-evolving an

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Liu, Huailan, Zhiwang Chen, Jie Tang, Yuan Zhou, and Sheng Liu. "Mapping the technology evolution path: a novel model for dynamic topic detection and tracking." Scientometrics 125, no. 3 (2020): 2043–90. http://dx.doi.org/10.1007/s11192-020-03700-5.

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AbstractIdentifying the evolution path of a research field is essential to scientific and technological innovation. There have been many attempts to identify the technology evolution path based on the topic model or social networks analysis, but many of them had deficiencies in methodology. First, many studies have only considered a single type of information (text or citation information) in scientific literature, which may lead to incomplete technology path mapping. Second, the number of topics in each period cannot be determined automatically, making dynamic topic tracking difficult. Third,

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Gomez, Manuel J., José A. Ruipérez-Valiente, and Félix J. García Clemente. "Exploring Technology- and Sensor-Driven Trends in Education: A Natural-Language-Processing-Enhanced Bibliometrics Study." Sensors 23, no. 23 (2023): 9303. http://dx.doi.org/10.3390/s23239303.

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Over the last decade, there has been a large amount of research on technology-enhanced learning (TEL), including the exploration of sensor-based technologies. This research area has seen significant contributions from various conferences, including the European Conference on Technology-Enhanced Learning (EC-TEL). In this research, we present a comprehensive analysis that aims to identify and understand the evolving topics in the TEL area and their implications in defining the future of education. To achieve this, we use a novel methodology that combines a text-analytics-driven topic analysis a

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Cai, Meng, Han Luo, and Ying Cui. "A Study on the Topic-Sentiment Evolution and Diffusion in Time Series of Public Opinion Derived from Emergencies." Complexity 2021 (December 2, 2021): 1–23. http://dx.doi.org/10.1155/2021/2069010.

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With the development of the Internet, social media has become an important platform for people to deal with emergencies and share information. When a public health emergency occurs, the public can understand the topics of the event and perceive the sentiments of others through social media, thus building a cooperative communication network. In this study, we took the public health emergency as the main research object and the natural disaster, accident, and social security event as the secondary research object and further revealed the law of the formation and evolution of public opinion throu

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Brunilde Sanso, Lorela Cano, and Antonio Capone. "On the evolution of infrastructure sharing in mobile networks: A survey." ITU Journal on Future and Evolving Technologies 1, no. 1 (2020): 141–57. http://dx.doi.org/10.52953/nbqh9604.

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Infrastructure sharing for mobile networks has been a prolific research topic for more than three decades now. The key driver for Mobile Network Operators to share their network infrastructure is cost reduction. Spectrum sharing is often studied alongside infrastructure sharing although on its own it is a vast research topic outside the scope of this survey. Instead, in this survey we aim to provide a complete picture of infrastructure sharing both over time and in terms of research branches that have stemmed from it such as performance evaluation, resource management etc. We also put an empha

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Wang, Jiwu, and Hongbo Sun. "An evolution simulation framework for ecological structure of crowd networks." International Journal of Crowd Science 4, no. 1 (2019): 87–100. http://dx.doi.org/10.1108/ijcs-09-2019-0022.

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Purpose This paper aims to obtain optimal specialization mode and level for complex network or system structures. In the e-commerce system, this paper studies the changes of each transaction subject in the process of ecological structure based on the income level of each transaction subject. Design/methodology/approach This paper aims to research the change of transaction efficiency evolution process of intermediaries. With the improvement of transaction efficiency, intermediaries interact with other transaction subjects at given modes in e-commerce systems. This paper analyzes the relationshi

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Galvis Quintero, Alexander. "Acceso dinámico al espectro: estado actual, tendencias y retos." Entre Ciencia e Ingeniería, no. 4 (December 20, 2008): 38–57. https://doi.org/10.31908/19098367.779.

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This paper is about the development and progress of technologies that improve the use of electromagnetic spectrum, focusing on several useful techniques for dynamic spectrum access in future wireless networks. Some of the most important projects are mentioned; later the significant orientations that are used for the solution of emerging problems are briefly described. Other topics as the challenges currently faced by researchers in the field, and the trends on evolution of wireless networks to be able to meet the requirements that have been imposed are treating. The main objectives of this pap

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YANG, HAN-XIN, WEN-XU WANG, YING-CHENG LAI, and CELSO GREBOGI. "THE EMERGENCE AND EVOLUTION OF COOPERATION ON COMPLEX NETWORKS." International Journal of Bifurcation and Chaos 22, no. 09 (2012): 1250228. http://dx.doi.org/10.1142/s0218127412502288.

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The emergence and evolution of cooperation in complex natural, social and economical systems is an interdisciplinary topic of recent interest. This paper focuses on the cooperation on complex networks using the approach of evolutionary games. In particular, the phenomenon of diversity-optimized cooperation is briefly reviewed and the effect of network clustering on cooperation is treated in detail. For the latter, a general type of public goods games is used with the result that, for fixed average degree and degree distributions in the underlying network, a high clustering coefficient can prom

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Martins, Tânia, Alexandra Braga, Marisa R. Ferreira, and Vítor Braga. "Diving into Social Innovation: A Bibliometric Analysis." Administrative Sciences 12, no. 2 (2022): 56. http://dx.doi.org/10.3390/admsci12020056.

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This paper aims to map and analyze the scientific production of social innovation, resulting in a contribution to the literature review and guidelines for future research. A bibliometric analysis was conducted to explore the trends on the topic. The primary objectives are (1) to identify how the literature defines the concept of social innovation and to track its evolution; (2) to measure productivity and identify key authors and scientific journals with the highest impact in the field and the association networks between their respective institutions and countries of origin; (3) to analyze an

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Min, Chao, Qingyu Chen, Erjia Yan, Yi Bu, and Jianjun Sun. "Citation cascade and the evolution of topic relevance." Journal of the Association for Information Science and Technology 72, no. 1 (2020): 110–27. http://dx.doi.org/10.1002/asi.24370.

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Yu, Tianyuan, Liang Bai, Jinlin Guo, and Zheng Yang. "Construct a Bipartite Signed Network in YouTube." International Journal of Multimedia Data Engineering and Management 6, no. 4 (2015): 56–77. http://dx.doi.org/10.4018/ijmdem.2015100104.

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Nowadays, the video-sharing websites are becoming more and more popular, which leads to latent social networks among videos and users. In this work, results are integrated with the data collected from YouTube, one of the largest user-driven online video repositories, and are supported by Chinese sentiment analysis which excels the state of art. Along with it, the authors construct two types of bipartite signed networks, video network (VN) and topic participant network (TPN), where nodes denote videos or users while weights of edges represent the correlation between the nodes. Several indices a

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Ribeiro, Henrique César Melo, Rosany Corrêa, Roselane Moita Pierot, and Lilian Guimarães do Nascimento Leal. "20 Years of the Kyoto Protocol: Profile and Behavior in Brazilian Academia From the Perspective of Social Network Analysis." Revista de Gestão Social e Ambiental 18, no. 11 (2024): e09937. http://dx.doi.org/10.24857/rgsa.v18n11-190.

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Objective: To investigate the profile and behavior of scientific production of articles published in Brazilian journals on the topic of the Kyoto Protocol in light of social network analysis. Theoretical Framework: The Kyoto Protocol is an international agreement that provides for the reduction of greenhouse gas emissions through flexible mechanisms, and is therefore considered an important environmental commitment made by many countries. Method: The Scientific Periodicals Electronic Library (SPELL) and the social network analysis research technique were used as the database for the search for

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Wei, Ling, Haiyun Xu, Zhenmeng Wang, Kun Dong, Chao Wang, and Shu Fang. "Topic Detection Based on Weak Tie Analysis: A Case Study of LIS Research." Journal of Data and Information Science 1, no. 4 (2017): 81–101. http://dx.doi.org/10.20309/jdis.201626.

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AbstractPurposeBased on the weak tie theory, this paper proposes a series of connection indicators of weak tie subnets and weak tie nodes to detect research topics, recognize their connections, and understand their evolution.Design/methodology/approachFirst, keywords are extracted from article titles and preprocessed. Second, high-frequency keywords are selected to generate weak tie co-occurrence networks. By removing the internal lines of clustered sub-topic networks, we focus on the analysis of weak tie subnets’ composition and functions and the weak tie nodes’ roles.FindingsThe research top

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Hu, Xinxin, Haotian Chen, Hongchang Chen, Xing Li, Junjie Zhang, and Shuxin Liu. "Mining Mobile Network Fraudsters with Augmented Graph Neural Networks." Entropy 25, no. 1 (2023): 150. http://dx.doi.org/10.3390/e25010150.

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With the rapid evolution of mobile communication networks, the number of subscribers and their communication practices is increasing dramatically worldwide. However, fraudsters are also sniffing out the benefits. Detecting fraudsters from the massive volume of call detail records (CDR) in mobile communication networks has become an important yet challenging topic. Fortunately, Graph neural network (GNN) brings new possibilities for telecom fraud detection. However, the presence of the graph imbalance and GNN oversmoothing problems makes fraudster detection unsatisfactory. To address these prob

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Lun, Weicheng, Qun Li, Zhi Zhu, and Can Zhang. "Routing Strategies for Isochronal-Evolution Random Matching Network." Entropy 25, no. 2 (2023): 363. http://dx.doi.org/10.3390/e25020363.

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In order to abstract away a network model from some real-world networks, such as navigation satellite networks and mobile call networks, we proposed an Isochronal-Evolution Random Matching Network (IERMN) model. An IERMN is a dynamic network that evolves isochronally and has a collection of edges that are pairwise disjoint at any point in time. We then investigated the traffic dynamics in IERMNs whose main research topic is packet transmission. When a vertex of an IERMN plans a path for a packet, it is permitted to delay the sending of the packet to make the path shorter. We designed a routing

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Bonn, Mark A., Meehee Cho, and Hyemi Um. "The evolution of wine research." International Journal of Contemporary Hospitality Management 30, no. 1 (2018): 286–312. http://dx.doi.org/10.1108/ijchm-09-2016-0521.

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Purpose Wine as a research topic continues to address a plethora of diverse contexts. In consideration of this scope and abundance of wine literature, this study aims to provide guidance for future meaningful contributions to this existing body of wine knowledge through a comprehensive scholarly review. Design/methodology/approach A total of 22 wine business, hospitality and tourism journals were selected and used to identify 739 refereed articles addressing wine-related topics over a 26-year period from 1990 to 2015. This was segmented using five wine research time frames, which were then sep

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Han, Xiaoyao. "Evolution of research topics in LIS between 1996 and 2019: an analysis based on latent Dirichlet allocation topic model." Scientometrics 125, no. 3 (2020): 2561–95. http://dx.doi.org/10.1007/s11192-020-03721-0.

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AbstractThis study investigated the evolution of library and information science (LIS) by analyzing research topics in LIS journal articles. The analysis is divided into five periods covering the years 1996–2019. Latent Dirichlet allocation modeling was used to identify underlying topics based on 14,035 documents. An improved data-selection method was devised in order to generate a dynamic journal list that included influential journals for each period. Results indicate that (a) library science has become less prevalent over time, as there are no top topic clusters relevant to library issues s

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Maria, Mariana Reis, Rosangela Ballini, and Roney Fraga Souza. "Evolution of Green Finance: A Bibliometric Analysis through Complex Networks and Machine Learning." Sustainability 15, no. 2 (2023): 967. http://dx.doi.org/10.3390/su15020967.

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A fundamental structural transformation that must occur to break global temperature rise and advance sustainable development is the green transition to a low-carbon system. However, dismantling the carbon lock-in situation requires substantial investment in green finance. Historically, investments have been concentrated in carbon-intensive technologies. Nonetheless, green finance has blossomed in recent years, and efforts to organise this literature have emerged, but a deeper understanding of this growing field is needed. For this goal, this paper aims to delineate this literature’s existing g

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Bottinelli, Arianna, Marco Gherardi, and Marc Barthelemy. "Efficiency and shrinking in evolving networks." Journal of The Royal Society Interface 16, no. 154 (2019): 20190101. http://dx.doi.org/10.1098/rsif.2019.0101.

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Characterizing the spatio-temporal evolution of networks is a central topic in many disciplines. While network expansion has been studied thoroughly, less is known about how empirical networks behave when shrinking. For transportation networks, this is especially relevant on account of their connection with the socio-economical substrate, and we focus here on the evolution of the French railway network from its birth in 1840 to 2000, in relation to the country’s demographic dynamics. The network evolved in parallel with technology (e.g. faster trains) and under strong constraints, such as pres

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Wu, Jibing, Lianfei Yu, Qun Zhang, et al. "Multityped Community Discovery in Time-Evolving Heterogeneous Information Networks Based on Tensor Decomposition." Complexity 2018 (2018): 1–16. http://dx.doi.org/10.1155/2018/9653404.

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The heterogeneous information networks are omnipresent in real-world applications, which consist of multiple types of objects with various rich semantic meaningful links among them. Community discovery is an effective method to extract the hidden structures in networks. Usually, heterogeneous information networks are time-evolving, whose objects and links are dynamic and varying gradually. In such time-evolving heterogeneous information networks, community discovery is a challenging topic and quite more difficult than that in traditional static homogeneous information networks. In contrast to

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Kang, Hyo-Jin, Jieun Han, and Gyu Hyun Kwon. "Determining the Intellectual Structure and Academic Trends of Smart Home Health Care Research: Coword and Topic Analyses." Journal of Medical Internet Research 23, no. 1 (2021): e19625. http://dx.doi.org/10.2196/19625.

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Background With the rapid development of information and communication technologies, smart homes are being investigated as effective solutions for home health care. The increasing academic attention on smart home health care has primarily been on the development and application of smart home technologies. However, comprehensive studies examining the general landscape of diverse research areas for smart home health care are still lacking. Objective This study aims to determine the intellectual structure of smart home health care in a time series by conducting a coword analysis and topic analysi

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Kovács, László, Katalin Orosz, and Peter Pollner. "Growing Networks – Modelling the Growth of Word Association Networks for Hungarian and English." Investigationes Linguisticae, no. 45 (December 30, 2021): 67–82. http://dx.doi.org/10.14746/il.2021.45.5.

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In the new era of information and communication technology, the representation of information is of increasing importance. Knowing how words are connected to each other in the mind and what processes facilitate the creation of connections could result in better optimized applications, e.g. in computer aided education or in search engines. This paper models the growth process of a word association database with an algorithm. We present the network structure of word associations for an agglutinative language and compare it with the network of English word associations. Using the real-world

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Wang, Ping, Yonghong Huang, Fei Tang, Hongtao Liu, and Yangyang Lu. "Overlapping Community Detection Based on Node Importance and Adjacency Information." Security and Communication Networks 2021 (December 31, 2021): 1–17. http://dx.doi.org/10.1155/2021/8690662.

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Detecting the community structure and predicting the change of community structure is an important research topic in social network research. Focusing on the importance of nodes and the importance of their neighbors and the adjacency information, this article proposes a new evaluation method of node importance. The proposed overlapping community detection algorithm (ILE) uses the random walk to select the initial community and adopts the adaptive function to expand the community. It finally optimizes the community to obtain the overlapping community. For the overlapping communities, this artic

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Das, Rosalina, Jessica Diaz, Sheela Dominguez, and Barry Issenberg. "514 Using text mining approaches to identify research trends – an exploratory analysis of Miami Clinical and Translational Science Institute publications from 2013-2021." Journal of Clinical and Translational Science 6, s1 (2022): 105. http://dx.doi.org/10.1017/cts.2022.308.

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OBJECTIVES/GOALS: The goal of this project was to perform an exploratory analysis of the research themes of scientific publications from the Miami Clinical and Translational Science Institute using text mining techniques and using bibliometric characterization and network analysis to further assess research trends. METHODS/STUDY POPULATION: Publications were identified from the Web of Science database using Miami CTSI grant numbers as search criteria for the period 2013-2021 and KL2 scholar publications. Following data pre-processing, topic modeling was performed using the Latent Dirichlet All

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Floria, Sabina-Adriana, and Florin Leon. "A novel information diffusion model based on psychosocial factors with automatic parameter learning." Computer Science and Information Systems, no. 00 (2020): 50. http://dx.doi.org/10.2298/csis200415050f.

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Online social networks are the main choice of people to maintain their social relationships and share information or opinions. Estimating the actions of a user is not trivial because an individual can act spontaneously or be influenced by external factors. In this paper we propose a novel model for imitating the evolution of the information diffusion in a network as well as possible. Each individual is modeled as a node with two factors (psychological and sociological) that control its probabilistic transmission of information. The psychological factor refers to the node?s preference for the t

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Zhao, Weize, Lukasz Walasek, and Gordon D. A. Brown. "The Evolution of Polarization in Online Conversation: Twitter Users’ Opinions about the COVID-19 Pandemic Become More Politicized over Time." Human Behavior and Emerging Technologies 2023 (July 5, 2023): 1–14. http://dx.doi.org/10.1155/2023/9094933.

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Political polarization on social media has been extensively studied. However, most research has examined polarization about topics that have preexisting associations with ideology, while few studies have tracked the onset of polarization about novel topics or the evolution of polarization over a prolonged period. The occurrence of COVID-19 provides a unique opportunity to study whether social media discourse about a novel event becomes increasingly polarized along ideological lines over time. This paper analyzes trends in Twitter polarization in relation to COVID-19 and other geopolitical even

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Shamsuddin, Siti Nurasyikin, Noriszura Ismail, and Nur Firyal Roslan. "What We Know about Research on Life Insurance Lapse: A Bibliometric Analysis." Risks 10, no. 5 (2022): 97. http://dx.doi.org/10.3390/risks10050097.

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A lapsed policy is an insurance policy that has become inactive due to non-payment of premiums. The word “lapse” is an insurance topic that constantly evolves, proven by the recent increase in publications on this topic. The study explores the life insurance lapse decision through a comprehensive bibliometric analysis throughout the years, concentrating on publication trends; co-authorship networks among countries, authors, and scientific journals; and the field’s evolution. The research is based on the Scopus database. Ultimately, 178 documents were retrieved and analysed, demonstrating incre

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Vidal-Franco, Ignacio, Jacobo Guiu-Souto, and Alberto P. Muñuzuri. "Social media enhances languages differentiation: a mathematical description." Royal Society Open Science 4, no. 5 (2017): 170094. http://dx.doi.org/10.1098/rsos.170094.

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Understanding and predicting the evolution of competing languages is a topic of high interest in a world with more than 6000 languages competing in a highly connected environment. We consider a reasonable mathematical model describing a situation of competition between two languages and analyse the effect of the speakers' connectivity (i.e. social networks). Surprisingly, instead of homogenizing the system, a high degree of connectivity helps to introduce differentiation for the appropriate parameters.

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Chen, Xiaolin, Qixing Qu, Chengxi Wei, and Shudong Chen. "Cross-Domain Transfer Learning Prediction of COVID-19 Popular Topics Based on Knowledge Graph." Future Internet 14, no. 4 (2022): 103. http://dx.doi.org/10.3390/fi14040103.

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The significance of research on public opinion monitoring of social network emergencies is becoming increasingly important. As a platform for users to communicate and share information online, social networks are often the source of public opinion about emergencies. Considering the relevance and transmissibility of the same event in different social networks, this paper takes the COVID-19 outbreak as the background and selects the platforms Weibo and TikTok as the research objects. In this paper, first, we use the transfer learning model to apply the knowledge obtained in the source domain of

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Maskat, Ruhaila, Shazlyn Milleana Shaharudin, Deden Witarsyah, and Hairulnizam Mahdin. "A Survey on Forms of Visualization and Tools Used in Topic Modelling." JOIV : International Journal on Informatics Visualization 7, no. 2 (2023): 517. http://dx.doi.org/10.30630/joiv.7.2.1313.

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In this paper, we surveyed recent publications on topic modeling and analyzed the forms of visualizations and tools used. Expectedly, this information will help Natural Language Processing (NLP) researchers to make better decisions about which types of visualization are appropriate for them and which tools can help them. This could also spark further development of existing visualizations or the emergence of new visualizations if a gap is present. Topic modeling is an NLP technique used to identify topics hidden in a collection of documents. Visualizing these topics permits a faster understand

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Katsurai, Marie, and Shunsuke Ono. "TrendNets: mapping emerging research trends from dynamic co-word networks via sparse representation." Scientometrics 121, no. 3 (2019): 1583–98. http://dx.doi.org/10.1007/s11192-019-03241-6.

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Abstract Mapping the knowledge structure from word co-occurrences in a collection of academic papers has been widely used to provide insight into the topic evolution in an arbitrary research field. In a traditional approach, the paper collection is first divided into temporal subsets, and then a co-word network is independently depicted in a 2D map to characterize each period’s trend. To effectively map emerging research trends from such a time-series of co-word networks, this paper presents TrendNets, a novel visualization methodology that highlights the rapid changes in edge weights over tim

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Alarcón Sánchez, Karla María, and José Luis Soriano Sandoval. "Evolution of multivariate analysis methods in the field of management sciences." RAN. Revistas Academia y Negocios 10, no. 2 (2024): 239–50. http://dx.doi.org/10.29393/ran10-15emml20015.

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Purpose: The evolution of multivariate analysis methods in the field of management sciences is presented, identifying both the current state and future trends that enable further development in business and administration studies.Methodology: A systematic literature review was conducted on the topic, and the key aspects of the predominant analysis methods are discussed.Results: the predominant methods are Regression Analysis, Structural Equation Modeling and Artificial Intelligence (AI). The results validate previous studies and highlight future trends.Implications: The study explores future t

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Mikheev, Alexey V. "Technological forecasting related to the energy sector: a scientometric overview." E3S Web of Conferences 209 (2020): 02022. http://dx.doi.org/10.1051/e3sconf/202020902022.

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Scientometric review of trends and key points of technological forecasting related to the energy sector is carried out in this study. Using co-keyword, co-citation techniques to analyze a set of research and review articles indexed in the Scopus database, clustered networks were built to understand content relationships and research topic evolution within the 2000-2019 period. This study provides an overview of future-oriented research efforts and trends in the energy technology knowledge domain.

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Thanh Vu, Simon Nam, Mads Stege, Peter Issam El-Habr, Jesper Bang, and Nicola Dragoni. "A Survey on Botnets: Incentives, Evolution, Detection and Current Trends." Future Internet 13, no. 8 (2021): 198. http://dx.doi.org/10.3390/fi13080198.

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Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. Botnets have shown a capacity to perform substantial damage through distributed denial-of-service attacks, information theft, spam and malware propagation. In this paper, a systematic literature review on botnets is presented to the reader in order to obtain an understanding of the incentives, evolution, detection, mitigation and current trends within the field of botnet research in pervasive computing. The literature review focuses parti

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Abuín-Porras, Vanesa, Clara Martinez-Perez, Carlos Romero-Morales, et al. "Citation Network Study on the Use of New Technologies in Neurorehabilitation." International Journal of Environmental Research and Public Health 19, no. 1 (2021): 26. http://dx.doi.org/10.3390/ijerph19010026.

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New technologies in neurorehabilitation is a wide concept that intends to find solutions for individual and collective needs through technical systems. Analysis through citation networks is used to search scientific literature related to a specific topic. On the one hand, the main countries, institutions, and authors researching this topic have been identified, as well as their evolution over time. On the other hand, the links between the authors, the countries, and the topics under research have been analyzed. The publications analysis was performed through the Web of Science database using t

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Shen, Jinlu, Xiangyu Zhou, Wei Wu, Liang Wang, and Zhenying Chen. "Worldwide Overview and Country Differences in Metaverse Research: A Bibliometric Analysis." Sustainability 15, no. 4 (2023): 3541. http://dx.doi.org/10.3390/su15043541.

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As a research topic integrating various subjects and technologies, Metaverse research has been a global concern in recent years. This study explores the hotspots and frontiers of academic research on the Metaverse based on a bibliometric analysis from 2012 to 2021. A keyword retrieval dataset related to Metaverse research was constructed based on expert consultation and manual reading of the literature, retrieving articles and conference papers from the Scopus database. Critical points in Metaverse research are represented in terms of research scale, keyword co-occurrence networks, keyword cit

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Zhou, Hou-kui, Hui-min Yu, and Roland Hu. "Topic discovery and evolution in scientific literature based on content and citations." Frontiers of Information Technology & Electronic Engineering 18, no. 10 (2017): 1511–24. http://dx.doi.org/10.1631/fitee.1601125.

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Wan, Huaiyu, Yutao Zhang, Jing Zhang, and Jie Tang. "AMiner: Search and Mining of Academic Social Networks." Data Intelligence 1, no. 1 (2019): 58–76. http://dx.doi.org/10.1162/dint_a_00006.

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AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topi

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Lu, Changyun, Longjiao Zhu, Yushi Xie, et al. "Advancing genetics of agriculture and biomolecules: A BERTopic-based analysis of research evolution in leading agricultural universities." Molecular & Cellular Biomechanics 22, no. 3 (2025): 901. https://doi.org/10.62617/mcb901.

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This study investigates the evolution of research at leading agricultural universities, with a particular focusing on genetics of agriculture and biomolecules as central themes. The objective is to identify trends, knowledge evolution pathways, and the relationship between scientific innovation and technological application. Utilizing the BERTopic model, a word-embedding-based topic extraction approach, the study analyzed data from cited articles and citing patents sourced from Web of Science and Lens databases. Key methodologies included advanced text preprocessing, topic clustering using Uni

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Kannan, Yamini, and Dharika Kapil. "Implementing Machine Learning Algorithms for Predictive Network Maintenance in 5G and Beyond Networks." International Journal of Wireless & Mobile Networks 16, no. 1/2 (2024): 01–11. http://dx.doi.org/10.5121/ijwmn.2024.16201.

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With the evolution of fifth generation (5G) network technologies, network maintenance strategies have become increasingly complex, necessitating the use of predictive analysis enabled by Machine Learning (ML) algorithms. This paper emphasizes exploring how ML algorithms can further enhance predictive maintenance in 5G and future networks. It reviews the current literature on this interdisciplinary topic, identifying key ML models such as Decision Trees, Neural Networks, and Support Vector Machines, and discussing their benefits and limitations. Special attention is given to the methodologies i

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