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Journal articles on the topic 'Topic change'

Author: Grafiati

Published: 4 June 2021

Last updated: 27 July 2025

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1

Andalasia, Ulfa Putri, Azwandi Azwandi, and Irma Diani. "THE PATTERN OF TOPIC CHANGE IN INDONESIAN AND SINGAPOREAN CONVERSATION." JOALL (Journal of Applied Linguistics & Literature) 4, no. 1 (2019): 27–42. http://dx.doi.org/10.33369/joall.v4i1.6584.

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This research was analyze and discuss the pattern in conversation. Applied pattern of conversation is unpredictable, it is drawn the section and topics which used by participants. The objectives are drawn pattern of topic change, find out clues and describe aspect that influenced pattern of topic change in conversation. The method of this research was qualitative research, the data collected by recording and transcribing. The participants are Singaporean and Indonesian, the data are conversation both director and secretary. Data analyzed through ethnography methodology in communication and con

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Lee, Hyung-Keun, Dong-woo Lee, Hye-Soo Cho, and Dong-Min Kwak. "Analysis of Research Trends in Exercise Science Using LDA Algorithm: Focusing on the Period from 2015 to 2024." Exercise Science 33, no. 4 (2024): 399–408. https://doi.org/10.15857/ksep.2024.00584.

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PURPOSE: The purpose of this study was to analyze the research trends in exercise physiology over the past decade, ultimately providing new prospectives on the fields.METHODS: We targeted the titles of papers published on the official website of the Korean Society of Exercise Physiology between January 2015 and August 2024. In total, 367 articles were included. Among them, 98 articles had English titles and were analyzed after translation into Korean. The “Tokenization” process, which extracts noun words and “Stopwords” to eliminate unnecessary particles of articles, was executed. Subsequently

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Aftab, Muhammad, Joseph C. Cleveland, and T. Brett Reece. "Noteworthy Literature Published in 2016 for Cardiac Surgery." Seminars in Cardiothoracic and Vascular Anesthesia 21, no. 1 (2017): 30–35. http://dx.doi.org/10.1177/1089253216688694.

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Cardiac surgical care of patients continued to evolve rapidly in 2016. In this article, 3 topics of considerable change are discussed based on recent publications. The first topic reviews the potential risks and benefits of newly instituted low-risk percutaneous aortic valve replacement. The second topic reviews the increasing utilization of more extensive arch replacements in acute type A dissection. The final topic reviews current trends and justification for changes in patterns of use of cardioplegia options. The topics discussed are contemporary issues facing cardiac surgery, so they shoul

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Okamoto, Dina G., and Lynn Smith-Lovin. "Changing the Subject: Gender, Status, and the Dynamics of Topic Change." American Sociological Review 66, no. 6 (2001): 852–73. http://dx.doi.org/10.1177/000312240106600604.

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Social scientists have devoted a great deal of attention to how much people talk, but have paid little attention to what they talk about. Research in the tradition of conversation analysis suggests that transitions between topics of conversation are accomplished in a systematic, structured way, and that social status can affect whose topics are developed and whose are lost. The authors use insights from conversation analysis to develop a systematic coding system for identifying topic shifts in task-oriented discussions. Hypotheses from the literature on group processes predict who will suggest

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Anonymous. "First IGBP Topic: Past Global Change." Eos, Transactions American Geophysical Union 69, no. 51 (1988): 1652. http://dx.doi.org/10.1029/88eo01252.

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Ferrer, Jovelyn, Juliana Malagon, and Enrique ter Horst. "Does Climate Change News Matter?" Sustainability 15, no. 18 (2023): 13865. http://dx.doi.org/10.3390/su151813865.

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We explore the importance of climate change as a news topic and examine the relationship between climate change news and financial returns using a large news database that consists of more than 4 million news stories. We use multinomial inverse regression—a Bayesian approach capable of handling the multi-dimensionality of our data—to translate news into a quantifiable input. We also build a climate change dictionary from different sources to identify climate change related words. We find that climate change is a persistent topic in our news universe, which indicates that it is a relevant news

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Jeong, Seong Yun, and Nam Gon Kim. "Topic modeling and topic change trend analysis for advanced construction technologies." Korean Institute of Smart Media 10, no. 4 (2021): 102–10. http://dx.doi.org/10.30693/smj.2021.10.4.102.

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이승민. "Topic structure and topic change type of the Korean and Japanese." Journal of Japanese Language and Literature 67, no. 1 (2008): 293–310. http://dx.doi.org/10.17003/jllak.2008.67.1.293.

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Xi, Yaoyi, Bicheng Li, and Yongwang Tang. "Topic Model Based New Event Detection Within Topics." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 3 (2016): 467–76. http://dx.doi.org/10.20965/jaciii.2016.p0467.

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Traditional new event detection is first proposed by Topic Detection and Tracking and it is actually first event detection. However, one topic usually consists of many events. The automatic instant detection of each event in one topic, not only the first event but also the second, the third and so on, is very useful for users to correctly understand the main development trend of the topic. In this paper, we address the problem of new event detection in one single topic and propose a novel topic model to detect new events along with the topic evolution. Our topic model treats new event detectio

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Knights, Dan, Michael Mozer, and Nicolas Nicolov. "Detecting Topic Drift with Compound Topic Models." Proceedings of the International AAAI Conference on Web and Social Media 3, no. 1 (2009): 242–45. http://dx.doi.org/10.1609/icwsm.v3i1.13982.

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The Latent Dirichlet Allocation topic model of Blei, Ng, and Jordan (2003) is well-established as an effective approach to recovering meaningful topics of conversation from a set of documents. However, a useful analysis of user-generated content is concerned not only with the recovery of topics from a static data set, but with the evolution of topics over time. We employ a compound topic model (CTM) to track topics across two distinct data sets (i.e. past and present) and to visualize trends in topics over time; we evaluate several metrics for detecting a change in the distribution of topics w

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Quintiliani, Lisa M., Marci K. Campbell, J. Michael Bowling, Susan Steck, Pamela S. Haines, and Brenda M. DeVellis. "Results of a Randomized Trial Testing Messages Tailored to Participant-Selected Topics Among Female College Students: Physical Activity Outcomes." Journal of Physical Activity and Health 7, no. 4 (2010): 517–26. http://dx.doi.org/10.1123/jpah.7.4.517.

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Background:A better understanding of identifying tailoring variables would improve message design. Tailoring to a behavior that a participant selects as one they would like to work on may increase message relevance, and thus effectiveness. This trial compared 3 groups: message tailored to physical activity as a participant-selected topic (choice), message tailored to physical activity as an expert-determined topic (expert), or nontailored message (comparison).Methods:408 female college students received web-delivered computer-tailored messages on physical activity. Outcomes were immediate and

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Li, Jing, Haiyan Liu, and Lei Kang. "Visual analysis of ICC themes and topics from 2009 to 2019." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-213-2019.

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<p><strong>Abstract.</strong> The themes and topics of the conference reflect the hot issues of the conference. The change of conference theme reflects the development and change of the hot topics of discipline research from the side. This paper uses bibliometrics to quantitatively analyze the topics and topics of International Cartographic Conference（ICC）from 2009 to 2019, and presents them through visualization methods such as label clouds, charts and so on.</p><p>The research mainly includes three aspects: 1. Fixed topic analysis refers to the analysis of topic

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Wang, Kai, and Fuzhi Wang. "Topic-Feature Lattices Construction and Visualization for Dynamic Topic Number." Journal of Systems Science and Information 9, no. 5 (2021): 558–74. http://dx.doi.org/10.21078/jssi-2021-558-17.

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Abstract The topic recognition for dynamic topic number can realize the dynamic update of super parameters, and obtain the probability distribution of dynamic topics in time dimension, which helps to clear the understanding and tracking of convection text data. However, the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge. Therefore, it is impossible to deeply perceive the dynamic change of the topic in the time series. By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation mo

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Zhu, Tongyu, and Jianjun Yu. "A Prerecognition Model for Hot Topic Discovery Based on Microblogging Data." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/360934.

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The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the top

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Xu, Yang, Yueyi Zhang, Yefang Sun, and Hanting Zhou. "An adaptive method for determining the optimal number of topics in topic modeling." PeerJ Computer Science 11 (February 28, 2025): e2723. https://doi.org/10.7717/peerj-cs.2723.

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Topic models have been successfully applied to information classification and retrieval. The difficulty in successfully applying these technologies is to select the appropriate number of topics for a given corpus. Selecting too few topics can result in information loss and topic omission, known as underfitting. Conversely, an excess of topics can introduce noise and complexity, resulting in overfitting. Therefore, this article considers the inter-class distance and proposes a new method to determine the number of topics based on clustering results, named average inter-class distance change rat

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Jontes, Dejan, Maruša Pušnik, and Anamarija Šiša. "Advocates or observers? Slovenian newsworkers and climate change." Anthropological Notebooks 30, no. 1 (2024): 71–98. https://doi.org/10.5281/zenodo.11214246.

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This paper analyses perceptions of the climate crisis by newsworkers of Slovenian (online) media and their news coverage of this topic. Through qualitative analysis of the in-depth interviews, the paper offers insights into the attitudes, perceptions, and motivations of selected Slovenian journalists and editors about climate change reporting and new insights into journalism practice and environmental journalism in Slovenia in terms of the peculiarities and contextual factors that can influence coverage of extreme weather events and climate change. The results show that the environmental and c

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Galdeman, Alessia, and Luca Maria Aiello. "Mapping the Climate Change Landscape on TikTok." Proceedings of the International AAAI Conference on Web and Social Media 19 (June 7, 2025): 2614–21. https://doi.org/10.1609/icwsm.v19i1.35962.

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Social media platforms shape climate action discourse. Mapping these online conversations is essential for effective communication strategies. TikTok’s climate discussions are particularly relevant given its young, climate-concerned audience. In this work, we collect the first TikTok dataset on climate topics. We collected 590K videos from 14K creators along with their follower networks. By applying topic modeling to the video descriptions, we map the topics discussed on the platform on a climate taxonomy that we construct by consolidating existing categorizations. Results show TikTok creators

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Putra, Arya Adi Pratama, M. Khusnu Milad, Yusuf Amrozi, Ahmad Kemal al-Izzi, and Moch Ramzy Rifaldi. "Analisis Trend Terhadap Isu Gerakan Mahasiswa di Surabaya Menggunakan Metode Topic Modelling dengan Latent Dirichlet Allocation." Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) 7, no. 6 (2024): 1699–706. https://doi.org/10.32672/jnkti.v7i6.8262.

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Abstrak - Mahasiswa memegang peranan penting dalam membangun dan membentuk masa depan bangsa. Mahasiswa kerap terlibat dalam berbagai gerakan untuk menyuarakan aspirasi dan membawa perubahan dalam masyarakat. Gerakan-gerakan tersebut merupakan ekspresi kepedulian mahasiswa terhadap berbagai isu penting dalam masyarakat dan menjadi sarana untuk memengaruhi perubahan positif dalam skala yang lebih besar. Oleh karena itu, penting untuk melakukan analisis mendalam terhadap gerakan mahasiswa yang sedang berlangsung maupun yang telah berlalu. Penelitian ini berfokus pada analisis gerakan mahasiswa d

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Han, Xuehua, and Juanle Wang. "Modelling and Analyzing the Semantic Evolution of Social Media User Behaviors during Disaster Events: A Case Study of COVID-19." ISPRS International Journal of Geo-Information 11, no. 7 (2022): 373. http://dx.doi.org/10.3390/ijgi11070373.

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Public behavior in cyberspace is extremely sensitive to emergency disaster events. Using appropriate methodologies to capture the semantic evolution of social media users’ behaviors and discover how it varies across geographic space and time still presents a significant challenge. This study proposes a novel framework based on complex network, topic model, and GIS to describe the topic change of social media users’ behaviors during disaster events. The framework employs topic modeling to extract topics from social media texts, builds a user semantic evolution model based on a complex network t

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Morandini, L., A. R. Mohammad, and R. O. Sinnott. "MAPPING THE CHATTER: SPATIAL METAPHORS FOR DYNAMIC TOPIC MODELLING OF SOCIAL MEDIA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 6, 2022): 315–20. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-315-2022.

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Abstract. Topic modelling is a branch of Natural Language Processing (NLP) that deals with the discovery of conversation topics in a given document corpus. In social media, this translates into aggregating social media posts, e.g. tweets, into topics of conversation and observing how these topics evolve over time (hence the “dynamic” adjective). Conveying the results of topic modelling can be challenging since the topics often do not lend themselves naturally to meaningful labelling. The volume of real world (global) social media also means that millions of topics can be ongoing at any given t

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Tucker, G. Richard. "LANGUAGE CONTACT AND CHANGE: SUMMARY OBSERVATIONS." Annual Review of Applied Linguistics 23 (March 2003): 243–49. http://dx.doi.org/10.1017/s0267190503000308.

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Various facets of the general topic of multilingualism, including language contact, have been dealt with in previous ARAL volumes (e.g., under separate entries in volumes 1, 2, 4, 5, 10, 12, 13, and 15) and as a major substantive focus in volumes 6, 14 and 17. Nonetheless, it does not seem at all surprising that we return to the specific topic of language contact and change in volume 23 given the worldwide incidence of the phenomenon and the attention, and often controversy, which various aspects of language contact, language change or language loss arouses. Thus, I find it interesting that, w

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Hamid, Ihsanullah, Hikmatullah Himat, Uzair Hidari, Abdul Waheed Waheed, and Mohammad Azim Azimee. "Climate Change Education in Afghanistan High School Curriculum: Depictions of the Causes, Impacts and Solutions." Nangarhar University International Journal of Biosciences 03, ICCC(special) (2024): 586–90. http://dx.doi.org/10.70436/nuijb.v3i02.305.

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Climate change education is crucial for equipping students with the knowledge to address environmental challenges. This study analyzes climate change education in Afghanistan's high school curriculum. Using content analysis, the research identifies climate change topics in geography, biology, and chemistry syllabi for grades 10 to 12. The study focuses on causes, impacts, and solutions to climate change and examines topic distribution across grades. The findings reveal that climate change-related topics are included in the geography, biology, and chemistry curriculums. In the geography curricu

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Yang, Hyunyoung, Jeongyeon Chae, A.-Ram Yang, Rujito Agus Suwignyo, and Eunho Choi. "Trends of Peatland Research Based on Topic Modeling: Toward Sustainable Management under Climate Change." Forests 14, no. 9 (2023): 1818. http://dx.doi.org/10.3390/f14091818.

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Peatlands are wetlands with an accumulation of peats, partially decomposed organisms, under waterlogged and anoxic conditions. Despite peatlands being extensively studied due to their wide distribution and various functions, the trends in peatland research have hardly been analyzed. We performed dynamic topic modeling (DTM) and network analysis to investigate the changes in the global trends in peatland research. Among the searched studies using the keyword ‘peatland’ from ScienceDirect, titles and abstracts from 9541 studies (1995–2022) were used for the analysis. They were classified into 16

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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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Lou, Shaoke, Tianxiao Li, Xiangmeng Kong, et al. "TopicNet: a framework for measuring transcriptional regulatory network change." Bioinformatics 36, Supplement_1 (2020): i474—i481. http://dx.doi.org/10.1093/bioinformatics/btaa403.

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Abstract Motivation Recently, many chromatin immunoprecipitation sequencing experiments have been carried out for a diverse group of transcription factors (TFs) in many different types of human cells. These experiments manifest large-scale and dynamic changes in regulatory network connectivity (i.e. network ‘rewiring’), highlighting the different regulatory programs operating in disparate cellular states. However, due to the dense and noisy nature of current regulatory networks, directly comparing the gains and losses of targets of key TFs across cell states is often not informative. Thus, her

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Shedler, Jonathan. "Changing the topic does not change the facts." Lancet Psychiatry 5, no. 7 (2018): 539. http://dx.doi.org/10.1016/s2215-0366(18)30093-2.

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McCarl, Bruce A., and Thomas W. Hertel. "Climate Change as an Agricultural Economics Research Topic." Applied Economic Perspectives and Policy 40, no. 1 (2018): 60–78. http://dx.doi.org/10.1093/aepp/ppx052.

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Lim, Yon-Soo. "Topic Modeling of YouTube Contents on Climate Change." Korean Journal of Security Convergence Management 12, no. 2 (2023): 139–50. http://dx.doi.org/10.24826/kscs.12.2.9.

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Wang, Liu, Xin Li, Le-Jian Liao, and Li Liu. "A Momentum Theory for Hot Topic Life-cycle: A Case Study of Hot Hashtag Emerging in Twitter." International Journal of Computers Communications & Control 11, no. 5 (2016): 734. http://dx.doi.org/10.15837/ijccc.2016.5.2540.

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The existing work on mining of hot topics is mainly based on topic multiplicity andattention from users in unit time. With the advent of social networking, the weight has been put on the hot topics which can effectively describe the importance and hotness of a topic. However, the researches on the influence exerted by the accumulation of attention towards hot topics and the alternation between hot topics and outdated ones are still relatively weak. In this paper, a novel algorithm for calculating the hotness of topics is proposed based on momentum. The number of the participants, but also the

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Fu, Luoyi, Dongrui Lu, Qi Li, Xinbing Wang, and Chenghu Zhou. "Can we ‘feel’ the temperature of knowledge? Modelling scientific popularity dynamics via thermodynamics." PLOS ONE 16, no. 2 (2021): e0244618. http://dx.doi.org/10.1371/journal.pone.0244618.

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Just like everything in nature, scientific topics flourish and perish. While existing literature well captures article’s life-cycle via citation patterns, little is known about how scientific popularity and impact evolves for a specific topic. It would be most intuitive if we could ‘feel’ topic’s activity just as we perceive the weather by temperature. Here, we conceive knowledge temperature to quantify topic overall popularity and impact through citation network dynamics. Knowledge temperature includes 2 parts. One part depicts lasting impact by assessing knowledge accumulation with an analog

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Ružić, Nataša, Maruša Pušnik, Jovana Kečina, and Babić Aleksandra Kovačević. "Media coverage of climate change and newsroom politics: The case of Montenegro." Anthropological Notebooks 29, no. 1 (2023): 44–73. https://doi.org/10.5281/zenodo.8346670.

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Climate change is one of the most important global topics of public interest. Consequently, the role of the media is crucial to inform citizens about it and to raise public awareness. This paper is devoted to an analysis of the reporting methods of the most visited Montenegrin web portals regarding the topic. We al-so aim to determine how media workers and political agents cover this topic. Since 2007, Montenegro has been constitutionally represented as an ecological state, which has an excellent legislative framework but also numerous environ-mental problems. Bearing these facts in mind, we i

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Коcharyan, Garnik S. "Conversion Therapy. Reflections on the Topic." 18, no. 18 (December 30, 2022): 34–39. http://dx.doi.org/10.26565/2410-1249-2022-18-05.

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Currently, there are two approaches to the therapy of ego-dystonic homosexuals. According to the first approach (gay affirmative therapy), they need to be adapted to their sexual desire. According to the second approach (conversion / reparative therapy), it is necessary to help patients change their sexual orientation in accordance with their desire and rejection of homosexuality and a homosexual lifestyle for themselves. Each approach has its supporters. Ego-dystonic homosexuality, which was included in the list of mental disorders in ICD-10, was not included in this list in ICD-11. In some c

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S. Kocharyan, Garnik. "Conversion Therapy Reflections on the Topic." Psychology and Mental Health Care 7, no. 3 (2023): 01–06. https://doi.org/10.31579/2637-8892/202.

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Currently, there are two approaches to the therapy of ego-dystonic homosexuals. According to the first approach (gay affirmative therapy), they need to be adapted to their sexual desire. According to the second approach (conversion / reparative therapy), it is necessary to help patients change their sexual orientation in accordance with their desire and rejection of homosexuality and a homosexual lifestyle for themselves. Each approach has its supporters. Ego-dystonic homosexuality, which was included in the list of mental disorders in ICD-10, was not included in this list in ICD-11. In some p

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Choi, Seongmi, Mihui Kim, and Won Jin Seo. "Research Trends on Living Donors for Liver Transplantation: A Text Network Analysis and Topic Modeling." Journal of Korean Academy of Fundamentals of Nursing 31, no. 2 (2024): 157–67. http://dx.doi.org/10.7739/jkafn.2024.31.2.157.

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Purpose: This study aimed to identify research topics and trends on living liver donors over time through text network analysis and topic modeling.Methods: Five electronic databases (PubMed, CINAHL, Embase, Web of Science, and PsycINFO) were reviewed for studies published through September 2023, and 392 studies were included. Text network analysis was used to identify the basic characteristics and centrality of the network. The topics were named after extracting meaningful topics through topic modeling using latent Dirichlet allocation.Results: A total of 1,111 keywords were extracted from the

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Schubatzky, Thomas, and Claudia Haagen-Schützenhöfer. "Debunking Climate Myths Is Easy—Is It Really? An Explorative Case Study with Pre-Service Physics Teachers." Education Sciences 12, no. 8 (2022): 566. http://dx.doi.org/10.3390/educsci12080566.

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Climate change is a complex topic and hence makes teaching climate change a demanding task. This is especially because climate change still represents a (socially) controversial topic and students may be confronted with misrepresentations and misinformation about climate change in their daily lives. Therefore, it is important that science teachers are equipped with skills to properly respond to or “debunk” climate change misinformation, and to train their students on how to identify and respond to misinformation. To address this, we developed an intervention based on inoculation theory and kno

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Murakami, Akira, Paul Thompson, Susan Hunston, and Dominik Vajn. "‘What is this corpus about?’: using topic modelling to explore a specialised corpus." Corpora 12, no. 2 (2017): 243–77. http://dx.doi.org/10.3366/cor.2017.0118.

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This paper introduces topic modelling, a machine learning technique that automatically identifies ‘topics’ in a given corpus. The paper illustrates its use in the exploration of a corpus of academic English. It first offers the intuitive explanation of the underlying mechanism of topic modelling and describes the procedure for building a model, including the decisions involved in the model-building process. The paper then explores the model. A topic in topic models is characterised by a set of co-occurring words, and we will demonstrate that such topics bring us rich insights into the nature o

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Cho, Eun-Byul. "Research Trends on Non Face-to-face Counseling Using Text Mining." Korean Youth Counseling Association 5, no. 4 (2024): 117–39. https://doi.org/10.51613/jkyca.2024.5.4.117.

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This study conducted text mining on domestic journal articles focused on non face-to-face counseling to analyze research trends. Articles from domestic journals have been identified since 2002, and a total of 369 papers were used for analysis. First, in the results of TF and TF-IDF, keywords such as 'video counseling,' 'counselor,' and 'experience' were identified as key terms that represent the characteristics of non face-to-face counseling research. Second, topic modeling was conducted on the collected documents, resulting in the extraction of seven topics. These topics were named: 'Understa

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Silvi, Nurus silvia. "Conversation CONVERSATION STYLE: ANALYZING TALK AMONG ‘’KICK ANDY'S TALK SHOW WITH THE FIVE TOWER STATE NOVEL'S AUTHOR’’ Abstrack The conversation analysis contained in the Talk Show Kick Andy video contains four topics, including the topic of conversation, the str." JournEEL (Journal of English Education and Literature) 4, no. 2 (2022): 10–22. http://dx.doi.org/10.51836/journeel.v4i2.357.

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Abstrack The conversation analysis contained in the Talk Show Kick Andy video contains four topics, including the topic of conversation, the structure of the conversation, the transfer of conversation, and the coherence of conversational discourse. On the topic of conversation, three topics were found, namely general topics, ongoing topics and real topics. Furthermore, in the conversation structure, the topic of conversation is found at the beginning of the conversation, the core of the conversation, and the end of the conversation. The conversational speech transfer contains two types o

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Tol, Anthony. "Time and Change in Vollenhoven." Philosophia Reformata 60, no. 2 (1995): 99–120. http://dx.doi.org/10.1163/22116117-90000094.

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Within the movement of reformational philosophy much attention has been given to the topic of time. Dooyeweerd initiated the discussion in the mid-30’s with his first publications on this topic. What turned out to be most challenging was not so much his treatment of time as such—e.g. his distinction between “cosmic time” and “modal time”—but the anthropological implication of the supra-temporality of the heart that transcends the temporal human functions of body and mind. Vollenhoven long remained in the background of this debate, at least in its printed form, though it is common knowledge t

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Dilaver, Irem, Serdar Karakullukcu, Fatih Gurcan, Murat Topbas, Omer Faruk Ursavas, and Nazim Ercument Beyhun. "Climate Change and Non-Communicable Diseases: A Bibliometric, Content, and Topic Modeling Analysis." Sustainability 17, no. 6 (2025): 2394. https://doi.org/10.3390/su17062394.

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This study examines research on the impact of climate change (CC) on non-communicable diseases (NCDs) using bibliometric analysis, topic modeling, and content analysis. Articles published in the Web of Science database between 2000 and 2024 were analyzed. VOSviewer and Biblioshiny were used for bibliometric analysis and Python for topic modeling. In addition, the 50 most cited articles were content analyzed. The results show that there has been an increasing number of publications over time and that the research originates predominantly from high/very high Human Development Index (HDI) countri

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Mylläri, Sanna, Suoma Eeva Saarni, Ville Ritola, et al. "Text Topics and Treatment Response in Internet-Delivered Cognitive Behavioral Therapy for Generalized Anxiety Disorder: Text Mining Study." Journal of Medical Internet Research 24, no. 11 (2022): e38911. http://dx.doi.org/10.2196/38911.

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Background Text mining methods such as topic modeling can offer valuable information on how and to whom internet-delivered cognitive behavioral therapies (iCBT) work. Although iCBT treatments provide convenient data for topic modeling, it has rarely been used in this context. Objective Our aims were to apply topic modeling to written assignment texts from iCBT for generalized anxiety disorder and explore the resulting topics’ associations with treatment response. As predetermining the number of topics presents a considerable challenge in topic modeling, we also aimed to explore a novel method

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Bai, Shizhen, Xinrui Bi, Chunjia Han, Mu Yang, and Hao He. "Exploring the Over-Time Variation in Customer Concerns on Sharing Economy Services." Journal of Global Information Management 31, no. 1 (2023): 1–21. http://dx.doi.org/10.4018/jgim.321435.

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The sharing economy represented by Airbnb has evolved rapidly. It is particularly important to identify and understand how consumer concerns change over time. As a result, this study employs structural topic modelling using room type and time as covariates to extract topics from 896,658 Airbnb reviews in London and to observe the variation in the prevalence of topics over time. The findings show that the topic proportion changed relatively sharply in the early years of Airbnb (2010-2013) and during the COVID-19 pandemic (2020-2022), but relatively smoothly in the middle period (2014-2019). Thi

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Yan, Zhihua, and Xijin Tang. "Exploring Evolution of Public Opinions on Tianya Club Using Dynamic Topic Models." Journal of Systems Science and Information 8, no. 4 (2020): 309–24. http://dx.doi.org/10.21078/jssi-2020-309-16.

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AbstractOnline media have brought tremendous changes to civic life, public opinions, and government administration. Compared with traditional media, online media not only allow individuals to browse news and express their views more freely, but also accelerate the transmission of opinions and expand influence. As public opinions may arouse societal unrest, it is worth detecting the primary topics and uncovering the evolution trends of public opinions for societal administration. Various algorithms are developed to deal with the huge volume of unstructured online media data. In this study, dyna

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Bogdanowicz, Alexander, and ChengHe Guan. "Dynamic topic modeling of twitter data during the COVID-19 pandemic." PLOS ONE 17, no. 5 (2022): e0268669. http://dx.doi.org/10.1371/journal.pone.0268669.

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In an effort to gauge the global pandemic’s impact on social thoughts and behavior, it is important to answer the following questions: (1) What kinds of topics are individuals and groups vocalizing in relation to the pandemic? (2) Are there any noticeable topic trends and if so how do these topics change over time and in response to major events? In this paper, through the advanced Sequential Latent Dirichlet Allocation model, we identified twelve of the most popular topics present in a Twitter dataset collected over the period spanning April 3rd to April 13th, 2020 in the United States and di

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Majerský, Matej, and Viera Kačinová. "How Does the Media Communicate Information about Climate Change? Analysis of Slovak Mainstream Media in 2019-2024." Media Literacy and Academic Research 7, no. 2 (2024): 38–52. https://doi.org/10.34135/10.34135/mlar-24-02-03.

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Climate change is one of the biggest global issues and challenges facing society today. The media reflect this topic in their content, but it often fades into the background in terms of the importance of other events. However, the diversity of this topic does not stop at the issue of waste management or waste reduction. Climate change and related topics can be found in content that focuses on politics, economics, energy or culture. Certain social events can add important journalistic value to the topic in order to attract both journalists and audiences and thus make it into mainstream content.

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Majerský, Matej, and Viera Kačinová. "How Does the Media Communicate Information about Climate Change? Analysis of Slovak Mainstream Media in 2019-2024." Media Literacy and Academic Research 7, no. 2 (2024): 38–52. https://doi.org/10.34135/mlar-24-02-03.

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Climate change is one of the biggest global issues and challenges facing society today. The media reflect this topic in their content, but it often fades into the background in terms of the importance of other events. However, the diversity of this topic does not stop at the issue of waste management or waste reduction. Climate change and related topics can be found in content that focuses on politics, economics, energy or culture. Certain social events can add important journalistic value to the topic in order to attract both journalists and audiences and thus make it into mainstream content.

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Kim, Cheonsoo. "A Topic Modeling for Climate Change Reportsin Local Newspapers in South Korea." Journal of Public Policy Studies 39, no. 3 (2022): 83–107. http://dx.doi.org/10.33471/ila.39.3.4.

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Shi, Lei, Junping Du, and Feifei Kou. "A Sparse Topic Model for Bursty Topic Discovery in Social Networks." International Arab Journal of Information Technology 17, no. 5 (2020): 816–24. http://dx.doi.org/10.34028/iajit/17/5/15.

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Bursty topic discovery aims to automatically identify bursty events and continuously keep track of known events. The existing methods focus on the topic model. However, the sparsity of short text brings the challenge to the traditional topic models because the words are too few to learn from the original corpus. To tackle this problem, we propose a Sparse Topic Model (STM) for bursty topic discovery. First, we distinguish the modeling between the bursty topic and the common topic to detect the change of the words in time and discover the bursty words. Second, we introduce “Spike and Slab” prio

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Zou, Xiaolei, Ming Cai, Guoxiong Wu, and Zhemin Tan. "Editorial for the Topic “A Themed Issue in Memory of Academician Duzheng Ye (1916–2013)”." Remote Sensing 15, no. 18 (2023): 4586. http://dx.doi.org/10.3390/rs15184586.

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This Topic covers a wide range of topics, including atmospheric dynamics and physics, synoptic weather, climate variability, climate change, and remote sensing observations for weather and climate studies [...]

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Lee, Yeon Kyeong, and Sung kyoo Hong. "A Study on Issue Change through Trot Audition Program: Focusing on News Big Data." Korean Society of Culture and Convergence 45, no. 7 (2023): 97–116. http://dx.doi.org/10.33645/cnc.2023.07.45.07.97.

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This study derived trot-related keywords, topics, and topic changes by using topic modeling to understand the media's interest in the trot audition program. This study was conducted as of April 24, 2023, and investigated various trot audition programs aired from December 06, 2018, when the article on the trot audition program <Tomorrow is Miss. Trot> was first reported, to April 24, 2023. As a result, it was confirmed that the popularity and scope of some trot-related content decreased, and direct communication between singers and fans decreased. On the other hand, it can be seen that to

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