Topic Search Research Articles

Bibliometric and visualized analysis of 2014-2024 publications on therapy for diabetic peripheral neuropathy.

This research aimed to examine the global developing patterns in the treatment of diabetic peripheral neuropathy (DPN) using a bibliometric analysis of published literature. We extracted publication data from papers published between 2014 and 2024 using a specific topic search in the "Web of Science Core Collection" (WoSCC) database. Various metrics, such as the number of papers, citations, authors, countries, institutions, and references, were collected for analysis. To further explore the data, CiteSpace was employed to examine co-citation patterns among authors, identify collaborative efforts between countries and institutions, and uncover emerging trends using burst keywords and reference analysis. The study encompassed 2,488 publications that exhibited an increasing trend in annual output. Notably, the journal PAIN, the United States, the Pfizer institution, and the author Feldman, EvaL emerged as the most prolific contributors to this research domain. The term "placebo-controlled trial" was the most prominent burst keyword from 2014 to 2017, whereas "spinal cord stimulation" held this distinction in the recent 5-year span. Furthermore, the publication titled "Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis-2015" demonstrated the highest burst in terms of references. This study is the first to objectively reveal the current hotspots and trends in DPN treatment. The results indicate that drug therapy remains the primary first-line treatment for DPN and that future research on DPN treatment will likely focus on "spinal cord stimulation" and "pain management." These findings provide valuable insights into DPN treatment.

Comparison Between SGLT2 Inhibitors and Lactation: Implications for Cardiometabolic Health in Parous Women.

Sodium-glucose cotransporter-2 (SGLT2) inhibition and lactation result in the excretion of large amounts of glucose in urine or milk and are associated with a lower risk of cardiovascular events. The respective mechanisms behind this association with cardiovascular protection are not clear. This review compares the contribution of noninsulin-mediated glucose transport during pharmacologic inhibition of SGLT2 with noninsulin-mediated glucose transport during lactation in terms of the implications for the cardiometabolic health of parous women. The search topics used to obtain information on SGLT2 inhibitors included mechanisms of action, atherosclerosis, and heart failure. The search topics used to obtain information on lactation included cardiovascular health and milk composition. Subsequent reference searches of retrieved articles were also used. Active treatment with SGLT2 inhibitors affects glucose and sodium transport in the kidneys and predominantly protects against hospitalization for heart failure soon after the onset of therapy. Active lactation stimulates glucose transport into the mammary gland and improves subclinical and clinical atherosclerotic vascular disease years after delivery. Both SGLT2 inhibitors and lactation have effects on a variety of glucose transporters. Several mechanisms have been proposed to explain the cardiometabolic benefits of SGLT2 inhibition and lactation. Learning from the similarities and differences between both processes will advance our understanding of cardiometabolic health for all people.

Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review

According to the European Data Strategy established in 2020, the European Open Science Cloud (EOSC) is described as “the basis for a science, research and innovation data space… and will be connected and articulated with the sectoral data spaces”, being one of the 14 European Common Data Spaces. While current cross-sectoral interactions with the EOSC are realised through the association’s Health Data Task Force, advancements in other EU priorities, such as the Green Deal and the Digital Strategy, should be accelerated in the green and digital transitions and integrated by reinforcing each other to be climate-neutral by 2050. With this motivation, this paper systematically reviews data spaces and digital twins (DTs) within the context of research and innovation. Specifically, focusing on the relevance of the EOSC to the Green Deal Data Space (GDDS) and DTs of the Earth, the relationship between them is explored using a topic search with various keyword combinations in the Web of Science and CORDIS databases. Based on the selected scientific articles and projects, collaboration opportunities are mapped to connect relevant stakeholders. Furthermore, existing and developing service components that could contribute to technical building blocks for the GDDS are identified. In summary, key findings are highlighted, addressing the current gaps and opportunities among the GDDS initiatives presented in this review.

Applications of Google Trends as a Data Source for Statistical Models

As technology advances, there is a growing number of potential data sources that can provide an alternative to traditional surveys. An example of this is the real time search popularity data made available through Google Trends. This type of data makes it possible to study public opinion, behaviour and attitudes in society or forecast economic phenomena. A definite advantage of using search popularity data is the immediate availability and low cost of obtaining such data. Also of significance is the fact that the Google Trends tool allows for direct research into the behaviour of Internet users, and not just their declarations as in the case of a survey. This can make a difference if respondents consider one of the answers to be more morally correct. Nevertheless, the use of Google Trends requires selecting correct search topics and terms to be included in the study and an awareness of the fact that the research sample is limited to Google search engine users. The paper will present the advantages and disadvantages of Google Trends and review its usefulness as a data source especially in times of higher market volatility.

Informal participation in digital planning: How can third parties use social media to shift power relations in planning?

In recent years, social media has become an influential tool for engaging various participants and facilitating inclusivity in digital planning. While many studies highlight local governments' use of social media for formal participation, limited research assesses its impact on power dynamics in informal participation. This study aims to fill the gap by identifying key features of social media that facilitate informal participation and applying Castells' four forms of network power to understand power dynamics among civil society, journalism, citizens, and governments in planning processes. It also develops a novel mixed-methods approach that combines social media scraping, social network analysis (SNA), semi-structured interviews, and field observation. This approach is applied to investigate the Enning Road regeneration project in Guangzhou as a case study. Analyzing data from China's Weibo, the study reveals network disputes across three dimensions: graph, community, and network statistics. Hyperlink-Induced Topic Search (HITS) and community detection results suggest that civil society and journalism have substantial networked power as they strategically utilize social media to promote collaboration, mobilize citizens, and foster communities. They also excise network-making power by switching online and offline networks, thereby transmitting online debate to a wide range of audiences and compelling local governments to shift planning priorities from demolitions to preservation.

Following Trending Topics: The Influence Mechanism of Chinese Hot Search Topics on Urban Dissemination in the Era of Short Video

The research on the influence mechanism of hot search topics on urban communication helps understand the media power and discourse practice of urban image construction in the era of short video. Therefore, this paper takes 17 cases of Chinese hot search urban topics from 2020 to 2024 as the research object and extracts one outcome variable and seven explanatory variables on urban hot search topics based on existing literature. Through the qualitative comparison of clear sets (QCA) analysis, it is found following trending topics has become a major way and pattern of urban public opinion discourse generation on short video platforms. On the one hand, the discourse is connected by the extension of urban hot search topics, and the spontaneous expression of netizens’ demands has exceeded the topic itself and has become the public’s concern. On the other hand, institutional media and mainstream media form event characterization through macro interpretation of hot topics, which often relate to urban governance and government administration, and further affect urban communication.

Spatiotemporal patterns of public attention to invasive species across an invasion front: a case study of lionfish (Pterois miles) from the Mediterranean Sea

Understanding societal interest in invasive species is crucial as greater public attention can support the success of conservation efforts. One of the main challenges in monitoring societal interest to support conservation is the absence of near-real-time indicators to track large-scale spatiotemporal dynamics of public attention. However, the digital revolution has opened up new opportunities to develop such indicators in support of invasive species research and management. Here, we aim to evaluate public awareness and interest in the invasive lionfish (Pterois miles) in the Mediterranean Sea and investigate spatiotemporal patterns of public interest in the species along its invasion front by using Google search volumes as a proxy for public attention. We implemented topic searches for the lionfish to download Google search volumes from 2013 to 2022 and used these data to test two hypotheses: (1) countries experiencing lionfish invasion exhibit higher public attention than those without lionfish, and (2) in invaded countries, public attention peaks around the arrival year, followed by a decline to baseline levels. Our study confirmed the first hypothesis, showing higher public attention in invaded countries. However, temporal patterns of attention did not fully align with the year of lionfish arrival, suggesting that the socio-political complexity of the region (e.g., cultural trends or internet accessibility), may be a key aspect to consider in future studies. Overall our study shows that digital data sources provide a unique opportunity to monitor social aspects of biological invasions with low associated costs and quick access to a great amount of data generated by internet users.

Preprint pointers from a long COVID scoping review: considerations for source selection and searching.

This paper describes the search approach for preprints for a post COVID-19 condition (i.e., long COVID) scoping review, including source selection, search strategy development, challenges, and insights throughout a project life cycle. With the growth of medical preprints since the COVID-19 pandemic, information professionals and researchers should be aware that preprints are possible sources of evidence and be prepared to manage them in evidence reviews for COVID-19 topics and beyond. Preprints are not peer-reviewed but can include important evidence about emerging topics. Because of the importance of preprints to the scoping review, a preprint search of Europe PubMed Central (PMC) was added. Europe PMC and similar aggregators combine multiple preprint servers and often have Boolean search, but sometimes limited search functionalities or few export options. Strategy translation encountered challenges such as varying and inconsistent terminology for post-COVID-19 condition, a complex search, and negotiating large numbers of preprints with resource constraints. Europe PMC identified additional preprints for inclusion due to additional preprint server coverage. It was helpful to limit the preprint search to the title and abstract fields, and to run an extra Internet search for publication of included study preprints. Challenges and potential solutions are summarized to support those conducting preprint searches for COVID-19 and other topics.

P-346 A systematic review of the gonadotoxicity of osteoscarcoma and Ewinǵs sarcoma chemotherapies in postpubertal females and males

Abstract Study question What is the postpubertal gonadotoxicity of osteosarcoma (OS) and Ewing’s sarcoma (ES) chemotherapies to better counsel females and males about the risk of infertility? Summary answer Limited data indicate a risk of infertility in OS in 5.1% of females and 52.2% of males and in ES in 13.0% and 89.5% respectively. What is known already Data on the gonadotoxicity of different chemotherapies are essential to better advise young women and men about the risk of treatment-related infertility and to better assess the need for fertility preservation measures prior to cancer treatment. Such data specific to bone-cancer have not yet been systematically reviewed. This review is part of the FertiTOX project (www.fertitox.com) which aims to close the gap of data regarding gonadotoxicity of cancer therapies to enable more accurate counselling regarding fertility preservation. Study design, size, duration A systematic review was conducted to address the issue of gonadotoxicity of bone-cancer specific chemotherapies. Combined search topics included 1) bone-cancer, 2) cancer therapies and 3) fertility parameters after cancer therapy. All relevant documents published between 09/2000 and 08/2022 from the information sources MEDLINE, Embase, and Cochrane Library were included. Participants/materials, setting, methods Only post-pubertal women and men aged < 40 years without recurrent or metastatic disease were included. Due to the inconsistent description of post-treatment fertility parameters, the parameter “suspected infertility” was introduced to summarise and interpret the results. “Suspected infertility” was defined as follows: in women, any menstrual cycle disorder, gonadotropin or anti-mullerian hormone outside the reference range and a diagnosis of premature ovarian failure; in men, the presence of azoospermia or oligozoospermia. Main results and the role of chance A total of 11 out of 831 trials were included in the review. All studies were registry or observational studies. The rate of suspected infertility varied considerably in both OS and ES. Suspected infertility was found in 10/190 (5.1%, range 0-66%) female patients with OS (6 studies), 24/46 (52.2%, range 46-100%) male patients with OS (3 studies), 18/138 (13.0%, range 3-18%) female patients with ES (3 studies) and 34/38 (89.5%) male patients with ES (1 study). It was not possible to calculate the risk associated with specific chemotherapies. The risk of suspected infertility tended to be higher in ES, where all (100%) patients received alkylating chemotherapy, compared with 40% of women and 90% of men in OS. In both OS and ES, the overall rate of suspected infertility appeared to be higher in men than in women. Limitations, reasons for caution The limited data and heterogeneity of fertility-related outcomes in most trials made it necessary to define the rather vague outcome “suspected infertility”. Wider implications of the findings Our data suggest a moderate to high risk of infertility due to chemotherapies in bone cancer. This appears to be more pronounced in males than in females, although precise information cannot be given due to limited data. However, even though the study emphasizes the importance to consider fertility preservation measures. Trial registration number not applicable

Analysis of A Systematic Literature Review on Dyslexia in Children

This research aims to find the main themes and research categories on reading difficulties (Diselectia). For the data taken to fulfill the purpose of this study, the authors searched several relevant sources from Google Scholar and Scopus (SAGE et al. & Francis). Articles were determined using four combinations of keywords; reports were included in the data set, and the researcher applied a systematic literature review method. Pieces that will become research sources are limited to the last six years. The total number of articles reviewed was 921 from different sources, namely Springer, Elsevier, SAGE, Eric, and Taylor & Francis. Articles were re-selected according to indicators, and then 194 articles were obtained. The dominant research methodology of the articles reviewed is qualitative. The four main themes revealed from the qualitative content analysis are dyslexia, causes of dyslexia, cases of dyslexia, and solutions to overcome dyslexia. Articles are filtered from topic descriptions, eligibility criteria, and search strategies. The cause of dyslexia can be due to developmental errors during pregnancy or other factors such as physical defects or habits that the child has. The solution offered by the teacher is to use several methods and learning media that are appropriate to the child's condition.

Temporary lentic water bodies of Latin America and Caribbean: a scientometric study

ABSTRACT Temporary lentic waters, those which alternate wet and dry periods, are globally distributed and highly prevalent on Earth and can be classified according to their hydroperiod. We used a scientometric perspective, to summarize the knowledge about temporary lentic ecosystems in 19 Latin American and Caribbean countries. We conducted a topic search in Web of Science (WoS) using various keyword combinations of hydroperiod type (temporary, ephemeral, intermittent, episodic and seasonal), type of aquatic lentic ecosystem (wetland, pond, pool, lake and lagoon) and the name of the country. Final searches and screenings provided 608 publications. To analyze the data, we used two qualitative approaches. We generated word clouds to ascertain the primary research topics concerning temporary lentic waters in Latin America. In addition, we constructed a bipartite network to visualize the geographical distribution of publications by topics. Knowledge gaps observed were geographical, encompassing disparities between and within countries, and thematic, as certain topics have received limited attention. Moreover, we detected a terminology gap: a lack of consensus about the terms used that are associated with temporary waters and a collaborative gap: the study of temporary waters has historically been fragmented in Latin America. Finally, we attempted to unravel the potential factors contributing to these knowledge gaps. By revealing major gaps in understanding the structure and functioning of temporary water bodies in the region, our study provides a valuable tool for identifying pertinent research areas to be explored in the future.

Anaphylaxis: What Parents Need to Know

Patient Education| 2021 Anaphylaxis Connected Content Translation: Anafilaxis Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Anaphylaxis . Pediatric Patient Education 2021; 10.1542/peo_document203 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Topics: anaphylaxis, hypersensitivity Anaphylaxis includes a wide range of symptoms that often happen quickly. The most severe symptoms restrict breathing and blood circulation. Combinations of symptoms may occur. The most common symptoms may affect the following: SKIN: itching, hives, redness, swellingNOSE: sneezing, stuffy nose, runny noseMOUTH: itching, swelling of lips or tongueTHROAT: itching, tightness, difficulty swallowing, hoarsenessCHEST: shortness of breath, cough, wheeze, chest pain, tightnessHEART: weak pulse, passing out, shockGUT: vomiting, diarrhea, crampsNEUROLOGIC: dizziness, fainting, feeling that you are about to die Anaphylaxis occurs when the immune system overreacts to normally harmless substances called allergens. The following are the most common allergens that can trigger anaphylaxis: Food such asPeanutsNuts from trees (such as walnuts, pistachios, pecans, cashews)Shellfish (such as shrimp, lobster)Fish (such as tuna, salmon, cod)MilkEggsIn rare... Copyright © 2007 American Academy of Pediatrics2007American Academy of Pediatrics You do not currently have access to this content.

Public and Research Interest in Telemedicine From 2017 to 2022: Infodemiology Study of Google Trends Data and Bibliometric Analysis of Scientific Literature.

Telemedicine offers a multitude of potential advantages, such as enhanced health care accessibility, cost reduction, and improved patient outcomes. The significance of telemedicine has been underscored by the COVID-19 pandemic, as it plays a crucial role in maintaining uninterrupted care while minimizing the risk of viral exposure. However, the adoption and implementation of telemedicine have been relatively sluggish in certain areas. Assessing the level of interest in telemedicine can provide valuable insights into areas that require enhancement. The aim of this study is to provide a comprehensive analysis of the level of public and research interest in telemedicine from 2017 to 2022 and also consider any potential impact of the COVID-19 pandemic. Google Trends data were retrieved using the search topics "telemedicine" or "e-health" to assess public interest, geographic distribution, and trends through a joinpoint regression analysis. Bibliographic data from Scopus were used to chart publications referencing the terms "telemedicine" or "eHealth" (in the title, abstract, and keywords) in terms of scientific production, key countries, and prominent keywords, as well as collaboration and co-occurrence networks. Worldwide, telemedicine generated higher mean public interest (relative search volume=26.3%) compared to eHealth (relative search volume=17.6%). Interest in telemedicine remained stable until January 2020, experienced a sudden surge (monthly percent change=95.7%) peaking in April 2020, followed by a decline (monthly percent change=-22.7%) until August 2020, and then returned to stability. A similar trend was noted in the public interest regarding eHealth. Chile, Australia, Canada, and the United States had the greatest public interest in telemedicine. In these countries, moderate to strong correlations were evident between Google Trends and COVID-19 data (ie, new cases, new deaths, and hospitalized patients). Examining 19,539 original medical articles in the Scopus database unveiled a substantial rise in telemedicine-related publications, showing a total increase of 201.5% from 2017 to 2022 and an average annual growth rate of 24.7%. The most significant surge occurred between 2019 and 2020. Notably, the majority of the publications originated from a single country, with 20.8% involving international coauthorships. As the most productive country, the United States led a cluster that included Canada and Australia as well. European, Asian, and Latin American countries made up the remaining 3 clusters. The co-occurrence network categorized prevalent keywords into 2 clusters, the first cluster primarily focused on applying eHealth, mobile health (mHealth), or digital health to noncommunicable or chronic diseases; the second cluster was centered around the application of telemedicine and telehealth within the context of the COVID-19 pandemic. Our analysis of search and bibliographic data over time and across regions allows us to gauge the interest in this topic, offer evidence regarding potential applications, and pinpoint areas for additional research and awareness-raising initiatives.

Missing in action: A bibliometric analysis of military research in the medical literature since 1950.

Top-tier general and specialty scientific journals serve as a bellwether for national research priorities. We hypothesize that military-relevant publications are underrepresented in the scientific literature and that such publications decrease significantly during peacetime. We identified high impact journals in the fields of Medicine, Surgery and Critical Care and developed Boolean searches for military-focused topics using National Library of Medicine Subject Headings terms. A PubMed search from 1950 to 2020 returned the number of research publications in relevant journals and the rate of military-focused publications by year. Rates of military publications were compared between peacetime and wartime. Publication rate trends were modeled with a quadratic function controlling for the start of active conflict and total casualty numbers. Baseline proportions of military physicians relative to the civilian sector served to estimate expected publication rates. Comparisons were performed using Pearson's χ 2 and Mann-Whitney U test, with p < 0.05 considered a significant difference. From 1950 to 2020, a total of 716,340 manuscripts were published in the journals queried. Of these, military-relevant manuscripts totaled 4,052 (0.57%). We found a significant difference in the rate of publication during times of peace and times of war (0.40% vs. 0.69%, p < 0.001). Subgroup analysis found significantly reduced rates of publication in medical and critical care journals during peacetime. For each conflict, the percentage of military-focused publications peaked during periods of war but then receded below baseline levels within a median of 2.5 years (interquartile range, 1.5-3.8 years) during peacetime. The proportion of military-focused publications never reached the current proportion of military physicians in the workforce. There is marked reduction in rates of publication for military-focused articles in high impact journals during peacetime. Military-focused articles are underrepresented in high-impact journals. Investigators of military-relevant topics and editors of high-impact journals should seek to close this gap.

The Use of Generative AI for Scientific Literature Searches for Systematic Reviews: ChatGPT and Microsoft Bing AI Performance Evaluation.

A large language model is a type of artificial intelligence (AI) model that opens up great possibilities for health care practice, research, and education, although scholars have emphasized the need to proactively address the issue of unvalidated and inaccurate information regarding its use. One of the best-known large language models is ChatGPT (OpenAI). It is believed to be of great help to medical research, as it facilitates more efficient data set analysis, code generation, and literature review, allowing researchers to focus on experimental design as well as drug discovery and development. This study aims to explore the potential of ChatGPT as a real-time literature search tool for systematic reviews and clinical decision support systems, to enhance their efficiency and accuracy in health care settings. The search results of a published systematic review by human experts on the treatment of Peyronie disease were selected as a benchmark, and the literature search formula of the study was applied to ChatGPT and Microsoft Bing AI as a comparison to human researchers. Peyronie disease typically presents with discomfort, curvature, or deformity of the penis in association with palpable plaques and erectile dysfunction. To evaluate the quality of individual studies derived from AI answers, we created a structured rating system based on bibliographic information related to the publications. We classified its answers into 4 grades if the title existed: A, B, C, and F. No grade was given for a fake title or no answer. From ChatGPT, 7 (0.5%) out of 1287 identified studies were directly relevant, whereas Bing AI resulted in 19 (40%) relevant studies out of 48, compared to the human benchmark of 24 studies. In the qualitative evaluation, ChatGPT had 7 grade A, 18 grade B, 167 grade C, and 211 grade F studies, and Bing AI had 19 grade A and 28 grade C studies. This is the first study to compare AI and conventional human systematic review methods as a real-time literature collection tool for evidence-based medicine. The results suggest that the use of ChatGPT as a tool for real-time evidence generation is not yet accurate and feasible. Therefore, researchers should be cautious about using such AI. The limitations of this study using the generative pre-trained transformer model are that the search for research topics was not diverse and that it did not prevent the hallucination of generative AI. However, this study will serve as a standard for future studies by providing an index to verify the reliability and consistency of generative AI from a user's point of view. If the reliability and consistency of AI literature search services are verified, then the use of these technologies will help medical research greatly.

What Canadians search about asthma: A 10-year Google Trends study on asthma and related topics

BackgroundGoogle Trends (GTr) is now becoming an important tool in epidemiological studies to assess the trend of online searches by people of any geographical location. While previous studies assessed trends in searches for some allergic conditions, very few studies reported search patterns for asthma and asthma-related topics. MethodsWe took monthly Canadian GTr data for asthma-related keywords such as ‘asthma’, ‘shortness of breath’, ‘wheeze’, ‘asthma emergency’, ‘asthma hospital’, and ‘asthma medication’ between January 1, 2014, and December 31, 2023. We assessed the trend of yearly relative search volume (RSV) for the past 10 years. We also assessed the trend by influenza and wildfire seasons. ResultsWe observed a marginal increase in searches for some asthma-related topics such as ‘asthma’ ‘shortness of breath’, and ‘wheeze’ in Canada between 2014 and 2023 but not other topics such as ‘asthma emergency’, ‘asthma hospital’, and ‘asthma medication’. The pattern of searches for ‘asthma’, ‘shortness of breath’, and ‘wheeze’ did not change by influenza of wildfire seasons across the years. ConclusionOur study is the first to demonstrate searches for asthma and related topics by Canadians in the past 10 years and indicates GTr as an emerging tool in epidemiology that can be used in planning the implementation of public health policies.

ВІД АНАЛІЗУ ТЕКСТУ ДО МОДЕЛЮВАННЯ ПРИРОДНОЇ МОВИ: КОМПЛЕКСНЕ ДОСЛІДЖЕННЯ

The article presents a comprehensive analysis of modern techniques and technologies used to analyze the tonality of textual data. Through a series of experiments, basic machine and deep learning algorithms such as sentiment analysis were developed to automatically detect and classify emotional tones in texts. Practical applications of these methods are also explored, ranging from social network monitoring to expert analysis and analysis of user reviews. Next, the article delves into the classification of textual data using modern machine and deep learning methods. This section of the paper reviews several classification models, including the Bayesian most-narrow classifier, support vector methods, and neural networks, highlighting their advantages and limitations. In addition, it emphasizes the importance of implementing text classification in various fields, including social network analysis, news article categorization, and automated document processing. In addition, clustering of similar textual data is considered for further analysis. Various clustering algorithms, such as k-means, hierarchical clustering, and spectral clustering, are compared, with special emphasis on their application to large text corpora. A demonstration of the practical application of text clustering, including data organization, topic search, and style identification in paper works, was also demonstrated. Moving on, the article considers the processing of individual thematic structures in textual data and its further analysis. An in-depth analysis of topic modeling techniques, such as the realized Dirichlet distribution (LDA) model, as well as its capabilities and limitations, is explored. Practical applications of topic modeling are demonstrated in various ways, including text collection analysis, news trend detection, and automatic document categorization. Finally, the article discusses some challenges and future prospects for the development of thematic modeling.

Cultural affinity and international trade in motion pictures: Empirical evidence using categorised internet search activity

It is well established that cultural affinity between countries affects international trade patterns. To date, most research on this topic has only considered cultural affinity between a pair of countries as a single measure that is static over time. In this paper, we introduce a novel bi-directional and time-varying measure of cultural affinity and examine its relevance to sectoral trade with an application to the motion picture industry. Using Google Trends search topics related to countries, and specific to the ‘Arts and Entertainment’ category, we construct a measure of ‘relative search interest’ (RSI) as a proxy for cultural affinity. We incorporate this proxy into a structural gravity model of motion picture trade and find that a one percent increase in RSI is associated with a 0.2–0.4 percent increase in box office revenue flow. Our analysis suggests that RSI in other categories can provide useful insights in other industries.

A semi-supervised approach of short text topic modeling using embedded fuzzy clustering for Twitter hashtag recommendation

Social media stands as a crucial information source across various real-world challenges. Platforms like Twitter, extensively used by news outlets for real-time updates, categorize news via hashtags. These hashtags act as pivotal meta-information for linking tweets to underlying themes, yet many tweets lack them, posing challenges in topic searches. Our contribution addresses this by introducing a novel heuristic for hashtag recommendation. Extracting 20 thousand tweets, 5000 each from distinct categories health, sports, politics, and technology we applied fundamental data cleaning and tokenization techniques. Leveraging Word2Vec, we vectorized tokens, capturing nuanced semantic meanings and mitigating data sparsity issues. The proposed heuristic creates clusters of different topic by combining these embedded features and idea of fuzzy C-Means technique. Develop a rule-based approach that combines both supervised and unsupervised methods to label clusters, indicating their respective topic. The experimental outcomes shows that our proposed techniques achieve better performance metrics in precision, recall, and F1-score compared to specific baseline models.

Sleep Apnea and Your Child

Patient Education| 2021 Sleep Apnea and Your Child Connected Content Translation: La apnea del sueño y su hijo: (Sleep Apnea and Your Child) Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Sleep Apnea and Your Child. Pediatric Patient Education 2021; 10.1542/peo_document090 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Topics: obstructive sleep apnea, sleep apnea syndromes If your child has these symptoms, he may have a condition known as sleep apnea. Sleep apnea is a common problem that affects an estimated 2% of all children, including many who are undiagnosed. If not treated, sleep apnea can lead to a variety of problems. These include heart, behavior, learning, and growth problems. Symptoms of sleep apnea include Frequent snoringProblems breathing during the nightSleepiness during the dayDifficulty paying attentionBehavior problems If you notice any of these symptoms, let your pediatrician know as soon as possible. Your pediatrician may recommend an overnight sleep study called a polysomnogram. Overnight polysomnograms are conducted at hospitals and major medical centers. During the study, medical staff will watch your child sleep. Several sensors will be attached to your child to monitor breathing, oxygenation, and brain waves. An electroencephalogram (EEG)... © 2003 American Academy of Pediatrics, Updated 10/2012. All rights reserved. You do not currently have access to this content.