Topic Popularity Research Articles

Impact of emotional contagion on waste separation intention in social media settings—Evidence based on machine learning and text analysis

Emotional contagion refers to the emotional experience caused by, and matched with, others' emotions, and is a process of emotional transmission. The emergence of social media has reshaped emotional contagion and the ways in which information is disseminated. Clarifying the emotional contagion mechanism associated with waste separation discussions on social networks and its dynamic effects on residents' intentions to separate waste is important in guiding residents toward waste separation. This study used data mining technology to crawl through 906,680 texts from social media. Machine learning models were used to identify emotions, and topic variables were extracted from text data to explore the effects of emotional contagion on residents’ intentions to separate waste. The empirical analysis indicated that the information disseminators’ emotions positively affected the information receivers’ emotions, thus indicating that an emotional contagion phenomenon exists in the social network and positively promotes residents' intentions to support waste separation, but also has negative effects on residents' intentions to implement waste separation. These findings imply inconsistencies in residents' attitudes and behaviors toward waste separation. Topic popularity buffered the effect of emotional contagion: excessive publicity did not result in better publicity effects. In addition, the regional economic development level weakened the influence of emotions on residents' intentions to separate waste. This study explored the mechanisms of emotional contagion and intention transmission pertaining to environmental protection topics, and offers important insights into the government's use of social media platforms to promote waste separation behavior among the public.

Analysis of the Correlation of Topic Feature Changes Based on the LDA Model

Abstract. As is well known, with the continuous development of artificial intelligence technology and the increasing accessibility of data, various social platforms are committed to using intelligent recommendation algorithms to cater to user preferences. Some platforms even exaggerate facts and push sensational, valueless information to users, leading to the "Screaming Effect" and the "Echo Chamber Effect." The prolonged existence of these effects may result in "Information Cocoon," which is detrimental to the healthy development of individuals and society. To address this issue, different topics can have varying trajectories as online comments ferment, potentially reaching a neutral consensus or resulting in polarization. As a mainstream social platform in China, Weibo users serve as nodes for the dissemination of public opinion information, and the characteristics of information release, reception, forwarding, and commenting all influence the effectiveness of communication. First, we selected the topics "COVID-19" and "IG Electronic Sports Club" as our research subjects, identifying a range of topic popularity through Baidu Index, followed by data collection. Second, we used perplexity and coherence to determine the optimal number of topics for LDA, analyzing the changes in topic feature characteristics over different time periods. Through correlation analysis, we reached the following conclusions: Higher Weibo levels correlate with better information dissemination effectiveness; the quantity of information published on Weibo negatively impacts the forwarding and commenting behaviors; and as events progress, the enthusiasm for information dissemination on Weibo declines, with daily dissemination gradually decreasing.

Prevalence, Presentation, and Popularity of Political Topics in Social Media Influencers’ Content Across Two Countries

ABSTRACT Social media influencers (SMIs) are not only important players in marketing but have also repeatedly posted about political issues on their channels. Yet, we lack insights into the prevalence of their political communication, their portrayal of different political subjects, and factors driving content popularity among audiences. This comparative study tackles these gaps: Quota-based youth surveys in Germany and Belgium (N Total = 2,800) informed a YouTube content analysis in both countries (N Total = 5,740), which was complemented by video metadata (i.e. views and likes per views on videos). Our findings show that most youth encounter political content from SMIs, but on a more occasional basis. Correspondingly, we found that most of the SMIs in our sample addressed political topics rather sporadically. However, their political videos received more views and likes than their nonpolitical content, implying that their discussion of meaningful subjects garners audiences’ attention. Our five-year analysis further suggests that political topics have become more prevalent in their content over time, pointing to an upwards trend in their political communication in recent years. Moreover, findings indicate that lifestyle-based political topics (e.g., gender, health) are most frequently discussed by SMIs. Generally, political topics were most often presented in the form of commentaries or reaction videos, which has several theoretical implications. Last, our results demonstrate that commentary-style videos and those characterized by high infotainment are most liked by audiences, showing that this type of content resonates strongly with SMIs’ viewers.

Tracing the technological trajectories of smart logistics domain based on citation analysis and topic modelling

ABSTRACT The emergence and development of intelligent technology are triggering major changes in the logistics industry, and relevant scientific and technological research on smart logistics (SL) is emerging endlessly. However, there is no research that systematically explores SL from the technological perspective. Therefore, this article selects 47,253 documents retrieved from the Derwent Innovation Index for systematic analysis and provides a comprehensive understanding of the SL domain. We combine main path analysis (MPA) and LDA topic modelling approaches to identify technological evolution trajectories. Through three main paths, the key technologies and technological evolution directions in the SL domain are revealed. Through topic identification and topic correlation calculation, global topic popularity trends and local topic evolution paths are identified. Finally, this study summarises our findings, contributions, and limitations. This is the first attempt to detect key technologies in the SL domain through MPA and topic analysis, thereby guiding relevant researchers and enterprises.

Topicality boosts popularity: a comparative analysis of NYT articles and Reddit memes

This study sheds light on interconnected topic dynamics across traditional news sources and social media platforms, emphasizing the influential role of topicality in shaping content popularity in social media. Using the Latent Dirichlet Allocation and BERTopic models, we define sets of 120 New York Times (NYT) topics to compare with 899,766 image-with-text memes from Reddit, showing that social media content aligns with many of the same topical patterns observed in news outlets. Topicality is formalized based on the temporal distributions of topics over the past 5 years. Using these topicality features, the investigation reveals significant correlations between the rising popularity of NYT topics and increased average upvotes on Reddit, particularly evident in “innovator” memes posted during the early stages of a topic’s prevalence in the NYT. Furthermore, topicality features show significant predictive power over other content-based control features in a CatBoost classifier prediction of viral Reddit memes.

IS MESH TERROR ENDEMICAL? A GEOGRAPHICAL ANALYSIS OF TRENDS

Abstract Introduction Mesh reinforcement for hernia repair has demonstrated to reduce recurrence rates for many scenarios of ventral and inguinal defects. In recent years, many hernia surgeons from specific geographies have encountered patients who feel strongly against the use of mesh, while physicians from other areas of the world have not reported this situation. This study aims to explore the regional trends associated with this phenomenon. Methods A global Google Trends search using the query “hernia”, “mesh complications” and “hernia mesh lawsuit” was used for data analysis. Search results are normalized to the time and location of a query by the following process: each data point is divided by the total searches of the geography, language, and time range it represents to compare relative popularity. The popularity index is represented as a percentile. Results An increase in popularity of hernia-related topics has been consistent for the past 15 years and this phenomenon has been consistent almost worldwide. The search term “mesh complications” also showed an increase in popularity mainly among English-speaking countries: the average popularity index since 2004 for this term has been 12% for the United States, 8% for the United Kingdom and <1% for Australia. “Hernia mesh lawsuit” has shown a significant increase in its popularity within the United States with an average popularity index score of 4% since 2004 and growing to 10% after 2016; while remaining relatively low (1–2%) for the rest of English-speaking countries. Even after adjusting for proportionality, non-English (Spanish, Mandarin, Portuguese and Hindi) mentions of “mesh complications” and “hernia mesh lawsuit” were significantly less frequent and were, in fact, very often advertising translations of legal firms within the United States. Conclusion Parallel to a global increase in the interest in hernia knowledge, there has been an escalation in the search for mesh complications information especially within the United States. This increase appears to be related to a surge in law firm advertising for hernia related issues. Further studies should focus on improving understanding of the general public perception and refining education mechanisms to assist patients and surgeons.

What is discussed about Flutter on Stack Overflow (SO) question-and-answer (Q&A) website: An empirical study

Context:Mobile applications are growing in prevalence. Cross-platform application is one of the main challenges within mobile application development. Aiming to facilitate the process of mobile application development, the software engineering community developed multiple solutions to support cross-platform application development. Flutter is a recent cross-platform software development kit (SDK) that has been rising in popularity. Objective:This study aims to gain a better understanding of Flutter stance on Stack Overflow (SO). Method:The study identified and analyzed 176,876 Flutter-related questions to understand the interest towards Flutter. The study utilized Latent Dirichlet Allocation (LDA) to identify Flutter-related topics discussed within the identified questions. Subsequently, a number of heuristics were utilized to gauge the popularity and difficulty of topics. Results:The study revealed that interest towards Flutter was steadily increasing on SO until it dropped in 2023 and SO users discuss 12 Flutter-related topics, with the topic of setup and build automation being the most popular and most difficult. Conclusion:This study highlights the interest towards Flutter on SO, identifies Flutter-related topics discussed on the website, and assess the topics popularity and difficulty. Software researchers, practitioners, educators, and Flutter contributors may utilize the results to steer their future Flutter-related efforts.

A Literature Review of Covid-19 Research: Taking Stock and Moving Forward

ABSTRACT After the outbreak of the pandemic, research on COVID-19 has increased substantially. This study provides a literature review of COVID-19 research in the field of public administration. Applying a Structural Topic Model (STM), this review analyzes 710 articles. The analysis identifies and maps the 27 most salient topics. We find that the popularity of most topics remains highly robust over time. We also find that the salience of the topics depends strongly on the journal and origin of the author and less on the internationality of the research team. Based on this comprehensive analysis, potential areas for research and theory development are explored.

Climate impacts to inland fishes: Shifting research topics over time

Climate change remains a primary threat to inland fishes and fisheries. Using topic modeling to examine trends and relationships across 36 years of scientific literature on documented and projected climate impacts to inland fish, we identify ten representative topics within this body of literature: assemblages, climate scenarios, distribution, climate drivers, population growth, invasive species, populations, phenology, physiology, and reproduction. These topics are largely similar to the output from artificial intelligence application (i.e., ChatGPT) search prompts, but with some key differences. The field of climate impacts on fish has seen dramatic growth since the mid-2000s with increasing popularity of topics related to drivers, assemblages, and phenology. The topics were generally well-dispersed with little overlap of common words, apart from phenology and reproduction which were closely clustered. Pairwise comparisons between topics revealed potential gaps in the literature including between reproduction and distribution and between physiology and phenology. A better understanding of these relationships can help capitalize on existing literature to inform conservation and sustainable management of inland fishes with a changing climate.

Mobile Prenatal Education and Its Impact on Reducing Adverse Pregnancy Outcomes: Retrospective Real-World Study.

Pregnancy is a pivotal phase in a woman's life, demanding special attention to ensure maternal and fetal health. Prenatal education plays a vital role in promoting healthy pregnancies and reducing adverse outcomes for pregnant women. Mobile prenatal education programs have gained traction due to their accessibility and timeliness, especially in light of finite health care resources and the constraints imposed by the COVID-19 pandemic. This study aims to develop and evaluate the effectiveness of a mobile-based prenatal education program in improving pregnancy outcomes. We developed a mobile-based prenatal education curriculum in collaboration with a multidisciplinary maternal care team from Peking Union Medical College Hospital (PUMCH) in Beijing, China. Data were retrospectively collected from 1941 pregnant women who had registered for the PUMCH mobile prenatal education program and subsequently delivered at PUMCH between May 2021 and August 2022. The study compared pregnancy outcomes between the completing group, which were pregnant women who had completed at least 1 course, and the noncompleting group. We also analyzed differences among course topics within the completing group and assessed course topic popularity among pregnant women. The PUMCH mobile prenatal education curriculum consists of 436 courses across 9 topics. Out of the participants, a total of 1521 did not complete any courses, while 420 completed at least 1 course. Compared with the noncompleting group, pregnant women who completed courses exhibited a significant reduction in the risk of gestational diabetes mellitus, induced abortion, postpartum infection, fetal intrauterine distress, and neonatal malformation. Among those in the completing group, a total of 86% (361/420) started course completion during the first and second trimesters. Furthermore, completing courses related to topics of pregnancy psychology and pregnancy nutrition was associated with reduced risks of premature rupture of membranes and small for gestational age infants, respectively. Pregnancy psychology and postpartum recovery were the preferred topics among pregnant women. The study demonstrates the potential of mobile-based prenatal education programs in improving pregnancy outcomes and supporting health care providers in delivering effective prenatal education. The rise of mobile prenatal education presents an opportunity to improve maternal and child health outcomes. Further research and broader implementation of such programs are warranted to continually improve maternal and child health.

What's next? Forecasting scientific research trends

Scientific research trends and interests evolve over time. The ability to identify and forecast these trends is vital for educational institutions, practitioners, investors, and funding organizations. In this study, we predict future trends in scientific publications using heterogeneous sources, including historical publication time series from PubMed, research and review articles, pre-trained language models, and patents. We demonstrate that scientific topic popularity levels and changes (trends) can be predicted five years in advance across 40 years and 125 diverse topics, including life-science concepts, biomedical, anatomy, and other science, technology, and engineering topics. Preceding publications and future patents are leading indicators for emerging scientific topics. We find the ratio of reviews to original research articles informative for identifying increasing or declining topics, with declining topics having an excess of reviews. We find that language models provide improved insights and predictions into temporal dynamics. In temporal validation, our models substantially outperform the historical baseline. Our findings suggest that similar dynamics apply across other scientific and engineering research topics. We present SciTrends, a user-friendly webtool for predicting future publication trends for any topic covered in PubMed.

Popular contraception videos on TikTok: An assessment of content topics

ObjectivesThis study aimed to explore the contraception content topics on the highly popular social media platform TikTok to understand this influential information source patients may bring into birth control counseling visits. Study designUtilizing a snapshot method, we collected the 100 most popular TikTok English-language videos for each of the eight contraception-specific search terms. We abstracted video content topics addressed and creator attributes. Two independent abstractors coded each video with high agreement, with a third coder adjudicating discrepancies. ResultsThe final data set included 700 unique videos, with a total of 1.18 billion views, 131 million likes, 1.5 million comments, and 4.1 million shares. In these videos, the most common topics addressed were patient experience (n = 365, 52.1%) and logistics of use (n = 351, 50.1%). Health care professionals created only 19.3% of videos (n = 135), but these videos accounted for a larger portion of the total video views (41.3%). Health care professionals largely made educational videos (92.6%) compared to 22.5% of videos coded as educational videos when made by perceived non–health care professionals. A small number of prolific video creators developed the majority of videos made by health care professionals, with 91 (67.4%) made by six TikTok creators. ConclusionsTikTok contains highly accessible contraception content, which garners high viewership, especially when created by health care providers. Clinicians should be aware of TikTok’s potential to influence patients prior to contraceptive counseling visits and recognize this platform as a public health instrument to disseminate contraceptive information to a key demographic. ImplicationsFew previous studies have examined the presence and popularity of contraception content topics on TikTok; little is known about the health content on this highly popular platform. Providers should be aware of the contraceptive topics on TikTok for understanding both patient perceptions and the potential for health education through this media.

A Practical Guide to Selecting Foot and Ankle Journals for Publication

Category: Other Introduction/Purpose: It is often difficult for early career investigators to identify the ideal journal readership for foot and ankle research without knowledge of each journal’s culture and article preferences. Bibliometric analyses have shown the popularity of certain topics can vary widely between similar journals. However, in the foot and ankle literature, there is very little information available regarding the publication preferences of common journals. The goal of this project was to provide a practical table with publishing trends to help investigators identify one or more journals most suitable for a given manuscript. Methods: We examined 43 journals, including both general orthopedic journals and foot and ankle-specific publications. We utilized the National Library of Medicine’s MEDLINE database for general article information, and Web of Science’s (WOS) Journal Citation Report for citation counts. Journals were only included for analysis if they published a minimum of 50 foot and ankle (FA) articles in the past five years, and were indexed in both MEDLINE and WOS. Variables such as publishing nationality, number of authors, and article type were collected using MEDLINE article metadata. Keyword lists were generated by our author team for each topic, and keywords were then searched to calculate the percentage of articles categorized under that topic. To measure the impact factor of a journal, we calculated a 5-year “impact factor” following modified WOS guidelines (total citations in 2020 for articles published 2015-2019 / total publications from 2015-2019). Results: 29 journals met our inclusion criteria for analysis (67%), of which 6 specialized in foot and ankle (Table 1). The popularity of certain article topics varies widely between journals. For example, while the Journal of Foot and Ankle Research publishes more than twice as many sports articles than any other FA publication (25%), it publishes five times less arthroscopy publications (2%). Similarly, we also find notable differences in the type of article published by journals – while only 1% of the total articles published by FAI are case reports, the Journal of Foot and Ankle Surgery published 30% case reports the past five years. We also found the distribution of American first authors can vary widely – ranging from 95% to 0% in different journals. Conclusion: This data set is aimed to provide a practical tool for early investigators to select ideal journals that would be appropriate for their work. Metrics like nationality may help authors intentionally reach out to a more diverse international audience, or an American readership, when appropriate. Likewise, targeting manuscripts that are a topic of interest to journals can save time in the publication process that is spent in initial review. While this data set relies exclusively on publicly available metadata from MEDLINE and WOS, we believe it offers an encouraging start to better understand the foot and ankle publishing landscape.

Myths of past biases and progress in biology.

Two ideas are popular among biologists. The first idea is concerned with the biased nature of biology, especially the idea that biologists have overemphasized the importance of competition in the past. The second idea is concerned with progress in correcting for biases, namely, that the biased nature of biology decreases with time. To test these ideas, data on the popularity of interaction topics, such as competition, predation, and mutualism, was collected from articles published in biology journals. Research biases should be visible in publication data as systematic over- and underemphases regarding the popularity of alternative, viable research topics. Were the two ideas correct, data should show that the popularity of a historically dominant topic(s) diminishes with time, whereas the popularity of historically marginal, alternative topics increases with time. The data show that the two ideas are false. According to publication data, the biased nature of biology increases with time, which is a sign of regress rather than progress in biology.

Characterizing engagement dynamics across topics on Facebook.

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic.

Discovering knowledge map and evolutionary path of HRM and ER: using the STM combined with Word2vec

PurposeThe purpose of this study is to comprehensively review the human resource management (HRM) and employment relations (ERs) field and explore the knowledge map, knowledge evolution trends and paths and paradigm shifts within this field.Design/methodology/approachThe Structural Topic Model in combination with Word2vec is proposed and applied in this work. First, this paper detects and interprets the research topics by reviewing 23,786 papers from 29 important journals in this field from 1990 to 2021. Then, this research explores popularity trends by aggregating topic proportions from a temporal perspective. Finally, this work explores the research topic evolution from the semantic perspective.FindingsThis paper obtains the following findings: (1) Sixteen research topics are identified, which provide the basic research overview of the whole field. (2) The changes in topic popularity over time map the tendency for employee benefits to be valued. (3) The evolutionary trajectories of temporal local topics are provided, which reflect the mechanisms of the paradigm and ideological migration and fusion.Originality/valueThis work adopts state-of-the-art textual as well as semantic mining techniques to establish a comprehensive knowledge map for HRM and ER research. Furthermore, these results uniquely demonstrate the pluralistic ideological orientation at the social level is gradually integrated into more micro levels, such as enterprises and individuals. These are the contents that were mentioned from previous studies by scholars, but not meticulously verified and interpreted.

How online review environment affects review generation behavior: A competing for attention perspective

From the perspective of competing for attention, this study attempts to examine how a potential reviewer’s review content in terms of topic diversity and topic popularity is affected by the review environment, which is characterized by review volume, review variance, and time distance. The empirical analysis is based on 70,383 restaurant reviews collected from Yelp. The Latent Dirichlet Allocation (LDA) model is adopted to conduct review text mining. Our empirical findings indicate that reviewers are more likely to evaluate the product on a wider range of topics when exposed to a larger volume or lower variance of existing reviews. Our findings also show that reviewers prefer to talk about popular topics as the volume of prior reviews increases or when prior reviews exhibit higher variance, but they tend to discuss unpopular topics when time distance from the first review increases.

Using e-petition data to quantify public concerns during the COVID-19 pandemic: a case study of England

ABSTRACT The COVID-19 pandemic has had a profound impact on society and many governments and politicians were required to make quick decisions to protect public health. In reaching these decisions they needed to weigh advice from experts in many fields and then “sell” these decisions. However little was known at the time about the desires and aspirations of their electorates. Here we identify one such source of public opinion, signatures to various COVID-19 related Parliamentary e-petitions Whilst there were over 1,500 such e-petitions, we identify 27 common and meaningful topics and show how the strength of these topics varies between individual parliamentary constituencies. Using a measure of support for each topic in the constituencies we identify five constituency groupings. There are two Conservative voting groups, “Middle England” and “Equity of Support”, the former are located largely in southern England whilst the latter are in the midlands and northern England. The groups that show strong support in Labour voting constituencies are ones around education and funding issues. This article shows how a targeted range of e-petitions can be grouped into topics and the popularity of topics established, and thereby function as a useful way of augmenting democracy and democratic institutions.

Coevolution modeling of group behavior and opinion based on public opinion perception

It is important to study the evolution mechanism of group behavior for the prevention and control of harmful group behavior on social networks. Most researchers focus on the study of group behavior evolution in a deterministic environment, ignoring the influence of the uncertain environment formed by the randomness of behavioral decision-making, the incompleteness of public opinion information, and the instability of behavioral states. Therefore, this paper starts with the behavior decision-making process of individuals in an uncertain environment, defines the perception of public opinion, and builds a coevolution model of group behavior and opinion. First, considering the impact of public opinion information on group behavior evolution, this paper defines emotional resonance and topic popularity to quantify public opinion perception and designs an uncertain behavior decision-making model based on public opinion perception. Then, for the influence of the instability of the behavioral state on the opinion evolution process, this paper designs an opinion evolution model for perception based on the unstable behavioral state. Finally, we design the behavior state evolution mechanism based on the instability of the behavior state and fuse it with the behavior decision-making model and opinion evolution model to construct a coevolution model of group behavior and opinion. Compared with the experimental results of other models and real group behavior evolution, our model is effective.

Google Trends as a digital marketing tool: methodical aspects

The aim of the article is to identify and analyze the menus and options of Google Trends for the digital marketers. Analyses results. The article is devoted to the problem of expanding the information base of marketers through the use of Google Trends, which allows to analyze the search queries of users of the Google search system and create appropriate graphic visualizations of the popularity of various search terms and topics. It was established that the researched tool expands the information base for the work of digital marketers, in particular through the use of such sections of the service as «Explore», «Compare», «Trending Searchers. Daily search trends», «Trending Searchers. Realtime Search Trends», «Year in Search», «Subscriptions». For example, data from the «Year in search» category, in particular the «purchase of the year» category, shows the most relevant user needs that were relevant in a certain year. The general and additional capabilities of Google Trends for digital marketers have been highlighted. The general capabilities of this service include: determining trends by specific search terms or topics, determining the specifics of the dynamics of the popularity of specific search terms or topics, searching and analyzing competitors, researching various digital search platforms, and operational monitoring general current trends in the country. The general capabilities will be useful for all digital marketers, regardless of the specifics of their activity. Additional features of Google Trends include: creation of relevant content, refinement of the semantic core of the site, optimization of the content plan, clustering of topics and the search for reasons for website traffic fluctuations. Additional opportunities will be useful for more highly specialized product promotion specialists (content marketers, brand marketers, SEO specialists, SMM marketers, story makers, etc.). The authors summarized that the research of the dynamics of interest of network users through Google Trends helps to plan marketing initiatives for the future, align the content of sites with current trends, and analyze the activities of competitors. Conclusions and directions for further research. The analysis of the features of the use of other digital marketing tools and the comparison between them in terms of the effectiveness of their use for the performance of specific tasks set before digital marketers are identified as promising for further research.