Media Networks Research Articles

An Exploration of Online Abbreviations in Network Media Platforms

With the rapid development of network information technology and the increasing frequency of online communication, abbreviations in network media platforms have emerged as a significant linguistic phenomenon. Network abbreviations serve not only as convenient tools in online communication but also as a microcosm of network culture and language development. This paper aims to explore the origins, types, characteristics, and impacts of abbreviations in network media platforms. Through in-depth research on network abbreviations, this paper reveals the unique roles of network language in terms of communication efficiency and cultural expression, and puts forward reasonable suggestions for standardizing the use of abbreviations on network platforms, providing a new perspective for understanding network language phenomena.

Analyzing the Impact of Social Media on Sports Marketing

The study's findings demonstrate the substantial social media's effects on sports marketing strategies. First of all, by enabling direct and instantaneous communication between sports teams and their fan base, social media networks have entirely transformed fan involvement. Sports marketers may use tools like live streaming, fan forums, and social media campaigns to foster a sense of community, encourage fan participation, and create unique experiences that boost fan loyalty are now powerful instruments for brand-building in sports marketing. Sports companies may showcase their principles, improve their brand messaging, and create interesting material that appeals to their target audience by utilising Facebook, Twitter, Instagram, and YouTube.

Mobile Applications and Artificial Intelligence for Nutrition Education: A Narrative Review

Mobile applications, websites and social media networks are now widely used communication tools. With the emergence of communication-related technologies in our lives and, consequently, the rise of social media networks and mobile applications, nutrition-related applications have become popular. Smartphones and other artificial intelligence technologies have become very useful tools for delivering nutrition-related interventions because they are very accessible and cost-effective. Digital interventions are also able to serve a larger number of communities than traditional interventions. Nutrition is not a field that has remained on the sidelines of these technological advances, and numerous mobile applications and technological tools have emerged that are intended to provide dietary advice or guidelines on the process of recovering from a disease. However, many of these applications have limitations and barriers that are important to consider. The aim of this review was to analyze the most current and widely used mobile applications related to nutrition, as well as their complementary tools (activity bracelets and smart scales, among others), highlighting their importance in improving lifestyle habits. In addition, their advantages and disadvantages are discussed and future directions are proposed.

An Optimized Public Opinion Communication System in Social Media Networks Based on K-means Cluster analysis

This study proposes a public opinion monitoring model that combines the K-means clustering algorithm with Particle Swarm Optimization (PSO) to enhance the accuracy and effectiveness of public opinion monitoring on social media. The model’s performance across various dissemination indicators is studied in detail. Through experiments conducted on social media datasets, the study comprehensively evaluates the model from four dimensions: dissemination speed, scope, depth, and sentiment dissemination effectiveness. The experimental results indicate that the proposed optimization model excels in multiple areas, particularly in dissemination depth and sentiment dissemination effectiveness. Specifically, in the three dimensions of dissemination speed, the proposed model achieves scores of 4.3, 4.2, and 4.4 in initial dissemination speed, decay speed, and peak dissemination speed, respectively. In the dimensions of user coverage, geographic coverage, and platform coverage under dissemination scope, the model scores 4.4, 4.5, and 4.3, demonstrating a broad dissemination capability. Additionally, in the dimensions of hierarchical dissemination depth and key node influence within dissemination depth, the model scores 4.3 and 4.5, indicating excellent performance in multi-level dissemination and key node activation. In sentiment dissemination effectiveness, the model receives scores of 4.4, 4.5, and 4.4 in emotional tendency change, polarity distribution, and diffusion intensity, showcasing its advantages in sentiment classification and dissemination. Sensitivity analysis further validates the model’s sensitivity to parameter settings, with experiments showing that reasonable adjustments to parameters such as the K value, PSO inertia weight, and learning factors can reduce the Sum of Squared Errors to 3209.72. Meanwhile, it can improve clustering purity to 0.822 and raise the Rand index to 0.623. Therefore, this study offers an efficient and reliable solution for public opinion monitoring on social media, providing valuable reference significance.

Analysis of feature extraction techniques for sentiment analysis of tweets

Over the past few years, sentiment analysis has moved from social networking services like LinkedIn, Facebook, YouTube, Twitter, and online product-based reviews to determine public opinion or emotion using social media textual contents. The methodology includes data selection, text pre-processing, feature extraction, classification model, and result analysis. Text pre-processing is an important stage in structuring data for improved performance of our methodology. The feature extraction technique (FET) is a crucial step in sentiment analysis as it is difficult to obtain effective and useful information from highly unstructured social media data. A number of feature extraction techniques are available to extract useful features. In this work, popular feature extraction techniques including bag of words (BOW), term frequency and inverse document frequency (TF-IDF), and Word2vec are compared and analyzed for the sentiment analysis of social media contents. A method is proposed for processing text data from social media networks for sentiment analysis that uses support vector machine as a classifier. The experiments are carried on three datasets of different context namely US Airline, Movie Review, and News from Twitter. The results show that TF-IDF consistently outperformed other techniques with best accuracy of 82.33%, 92.31%, and 99.10% for Airline, Movie Review, and News datasets respectively. It is also found that the proposed method performed better than some existing methods.

Lexicon-Based Approach in Sentiment Analysis of Yemeni Dialect for Social Media Network

Recently, the number of Yemeni users has been expanding quickly on social media platforms. Most research in Arabic sentiment analysis has gained on Modern Standard Arabic (MSA) and some specific dialects, such as Egyptian, Levantine, and Gulf. However, there is a noticeable gap in Yemeni dialect sentiment analysis research. The reason for that is the lack of reliable Yemeni lexical and corpus and a real dataset for social media sentiment analysis. This research addresses this lack by presenting the Yemeni Dialect sentiment lexicon and corpus. This lexicon and corpus provide valuable resources for researchers and practitioners seeking to analyze sentiment in Yemeni dialect social media content, contributing to a better understanding of Yemeni public opinion, social media monitoring, marketing, cultural understanding, and assisting in efforts to respond to crises in Yemen. The Yemeni Dialect sentiment lexicon is enriched with a reasonable number of words and phrases categorized according to their positive and negative sentiment tendencies. Moreover, we constructed a corpus dataset of more than 54,000 comments built from the Facebook platform. A large dataset of unlabeled comments from the main Yemeni telecommunications companies in Yemen (Yemen Telecom, Yemen Mobile, YOU, and Sabafon), are people commenting on a public issue related to the services provided by those companies. The lexicon-based approach is used to extract the sentiment’s polarity and label each of the provided comments to formulate a corpus dataset as being either positive, negative, or neutral. The evaluation metrics of experiments are accuracy, recall, precision, f-measure, and the confusion matrix. The accuracy result of the lexicon-based labeling approach was calculated through a comparison between the achieved results and the ones achieved through manually labeled comments by three Yemeni experts. Evaluation results using a lexicon-based approach achieved an accuracy of 90.05%.

Social Media Networks and Stock Price Synchronicity: Evidence from a Chinese Stock Forum

The widespread communication and interaction between small investors on social media in the capital market has resulted in the formation of a social media network specific to listed companies. Using a unique dataset from an active online stock forum in China, we construct a social media network of listed companies by assigning listed companies as nodes and common commenters who post in each of the subforums for two listed companies in a year as edges. Then, we investigate the relationship between the network centrality of the listed companies and stock price synchronicity. The results show that there is a significantly negative relationship between the social network centrality of listed companies and stock price synchronicity, indicating that social media networks can improve the price efficiency of capital markets. The mechanism analysis shows that social media networks can produce more corporate‐specific information and improve the efficiency of information dissemination, thus reducing stock price synchronicity.

“Symptoms” of Chinese Women’s Appearance Anxiety

The pervasive issue of “appearance anxiety” among young females has emerged as a significant psychosocial concern in contemporary society. This study employs qualitative research methods to investigate the social mechanisms underlying the development of “appearance anxiety” among young women, adopting a sociological standpoint on body-related matters. The findings of this study reveal that social factors contribute to the development of “appearance anxiety” in young women, as they strive to establish intimate relationships and attain societal validation. Consequently, young women are compelled to conform to societal gender norms, subjecting themselves to the scrutiny of aesthetic standards, while simultaneously resisting the detrimental effects of “appearance anxiety” through various forms of body consumption practices. Although the proliferation of information network media has provided women with expanded platforms for self-presentation, it has concurrently reinforced both societal aesthetic ideals and consumerist culture. Moreover, the media’s perpetuation of rigid body image standards, coupled with the propagation of misconceptions about body consumption, further entangles young women in a cyclic social framework characterized by “societal aesthetics - appearance anxiety - body consumption.”

Tobacco smoking during COVID-19 pandemic among social media users in Russia

Abstract Background The COVID-19 pandemic has forced countries to take various restrictive measures, including “lockdowns”, which may have affected tobacco smoking. The study explored associations between an increase in smoking, sociodemographic, and related to pandemic factors during pandemic among social media users in Russia. Methods Between June-September 2020, 1518 users of the most popular in Russia social media networks participated in online survey investigating changes in alcohol, tobacco, and substance use during pandemic. Binary logistic regression was used to identify factors associated with an increase in tobacco smoking. The analysis was adjusted for sex, level of education, perception of the severity of public life restrictions, negative work/financial consequences of the pandemic, stress, changes in the frequency of drinking, heavy episodic drinking (6 or more standard drinks at a time), and the volume of alcohol consumed on a typical occasion. Results 46.8% of the surveyed population were current smokers. 17.0% of them reduced, 37.9% increased, and 45.1% didn’t change their smoking during the pandemic. Relative to those whose smoking reduced or didn’t change, those who increased their smoking were more likely to be: 18-29 years old (OR = 1.906; 95% CI = 1.109-3.277), residents of medium to big cities (up to 1 mln inhabitants) (1.519; 1.017-2.270), had their income reduced (1.508; 1.024-2.222), faced severe restrictions in everyday life as a result of measures taken to contain SARS-CoV-2 (2.398; 1.440-3.758). After introducing alcohol consumption variables to the model, only two factors were associated with an increase in smoking: severe restrictions in everyday life (2.147; 1.227-3.993) and increased frequency of heavy episodic drinking during pandemic (2.338; 1.167-4.685). Conclusions Increase in tobacco smoking during pandemic was associated with severe restrictions in everyday life and increased frequency of heavy episodic drinking among social media users in Russia. Key messages • More than a third of social media users increased tobacco smoking during pandemic, which was associated with severe restrictions in everyday life and increased frequency of heavy episodic drinking. • During pandemics and similar public health crises, it is advisable to expand remote counseling services for alcohol and tobacco cessation, which can be delivered through social media.

Word Formation Processes in the Context of Social Media Discourse: A Case of Chuka University Students

The social media discourse is a hybrid of both written text and spoken discourse and therefore exhibits unique linguistic features that researchers can explore. This paper reveals the new dynamics of word formation processes in the social media discourse context, which is apparently a new genre. Morphological processes have in the past been analyzed in the context of spoken and written discourse. However, due to the evolution of the social media discourses that emanate from the communications that is mediated by divergent media platforms such as Facebook, WhatsApp, Instagrams and twitter, there is a need to shed light on how language is used in social media. This paper focuses on one aspect of such usage; how words are formed in the social media milieu. This paper therefore analyses the morphological processes drawing from Chuka University students’ social media discourse on WhatsApp platform. Students exhibits similar language usage due to the fact that they share a lot in common as a speech community. The paper therefore utilizes the social network theory to show how the interactants exploits the linguistic artifacts available at their social media network to interact meaningfully. Particularly, the focus is on the morphological processes that are evident in their interactions. The research design used is descriptive and the approach to data analysis is qualitative. The data used to inform this paper is drawn from the researcher’s thesis (2019). The findings revealed that students’ social media discourse results in the formation of new lexical items, use of symbols, Arabic numerals and letters to represent morphemes or words that are used in their day-to-day interactions. Similarly, morphological processes such as compounding, blending, clipping, borrowing, abbreviations and acronyms are common in the students’ social media discourse.

PUBLIC PARTICIPATION MECHANISM IN LOW-CARBON TRANSPORTATION FROM THE PERSPECTIVE OF CARBON NEUTRALITY

Under the goal of carbon neutrality, public participation in green travel is the fundamental premise of low-carbon transportation development. Based on the multiple mediation effect model, this paper explores the mechanism of social interaction on public participation in low-carbon transportation, and the hierarchical regression method is used to test the moderating effect of social network intensity and information network intensity. The results show that: (1) Both network media and social relations have a prominent positive effect on public participation, but the effect of network media is better than that of social relations. (2) Network media and social relations affect residents’ low-carbon travel behavior through three mediating variables, namely, traffic information, environmental protection knowledge and social norms. (3) The moderating effect of social network intensity on the relationship between network media and low-carbon travel behavior is prominently negative, while the moderating effect of information network intensity is significantly positive. Therefore, it is necessary to stimulate more public participation in low-carbon transport through real-time pushing of traffic information and strengthening the closeness of social relations.

Tendencies and characteristics of public fitness behavior in the digital era: an Internet ethnography study based on the K Community in China.

The deep integration of media technologies into fitness activities in the era of digital intelligence has created a new and evolving landscape for public fitness. This transformation significantly impacts the practices and experiences of fitness. This study employs Internet ethnography as a qualitative research methodology, focusing on the daily activities of participants in a digital fitness community known as the K-community. Through immersive observation and analysis, the research seeks to uncover the evolving patterns and characteristics of fitness practices in China during the digital era. As media technology and network culture advance, participants in digital fitness increasingly display fragmented, digitized, entertaining, ritualized, and highly socialized behaviors. These traits reflect the community's desire for varied and complex exercise experiences within the context of modern technology. The evolution of fitness behavior not only reflects the operational principles of contemporary media technologies but also encapsulates the essence of popular culture in the digital age. This study enhances our comprehension of fitness practices in digital environments and their wider cultural ramifications.

Инженерный расчет гибких оболочек лесосплавных опор

Currently, the issue of delivering wood raw materials from remote forest areas, where the largest volumes are located, is relevant. Often, this delivery is economically justified only when using a network of medium and small rivers with the use of environmentally friendly technologies. On such rivers, it is preferable to use mobile anchors, in particular shore fillable ones, for fixing timber-rafting objects. A description has been given of a new modification of such an anchor, which differs from the prototype by a container having a flexible shell. This allows to significantly reduce the material consumption for manufacturing the container, the dimensions of the anchor in the transport position, and to produce anchors of any realistic size. The choice of the most rational option for such a container implies the scientific justification of its parameters. The aim of the study is to develop a scientific basis for this justification. Analytical formulas have been theoretically obtained for determining the basic geometric characteristics of the cross-section of the container under consideration. These formulas are useful in scientific research, but their application is very problematic in practical engineering calculations. This is due to the dependence of the specified characteristics on elliptic integrals and parameters, which are very difficult to measure in engineering practice. Having performed calculations using these formulas for a single cross-sectional area, we have obtained its specific geometric characteristics for various shapes, i.e. for various width-to-height ratios of a container to be filled. The results of the calculations have been approximating dependencies linking the named characteristics with the specified ratio, which is called the shape factor. Multiplying the specific characteristics by the square root of the cross-sectional area gives the absolute values of the corresponding characteristics. As a result, we have obtained formulas convenient for practical use, allowing to determine the width and height of the container to be filled, the width of its base, the perimeter of the cross-section, the heights of the zero pressure line and the extreme lateral point of the cross-section above the base of the container. The accuracy of calculations based on these and analytical formulas is almost the same. A formula for determining the specific tension of a flexible container shell has been obtained. The nature and degree of influence of the shape factor and length of the container on its other geometric characteristics have been established. An algorithm for substantiating the key parameters of a container to be filled with a flexible shell has been developed using the described results.

RHEOLOGICAL BEHAVIOR OF ALUMINUM SOAP: A NEW PROSPECT FOR TREAD RUBBER APPLICATION

ABSTRACT Aluminum soaps are notable for their enormous power of thickening many organic hydrocarbon solvents. We investigated the rheological behavior of aluminum dioleate, an aluminum soap, in squalane. Intriguingly, its linear rheological properties resembled those of entangled polymer melts, whereas its nonlinear behavior exhibited similarities to the Payne effect observed in particle-suspended systems. Using high-resolution microscopy, we discovered that its thickening power arises from the formation of spherical nanoparticles from the aluminum soap molecules that then aggregate into highly fractal networks in the dispersion medium. Remarkably, this nanoparticle formation occurs not only in small-molecule organic media but also in long-chain macromolecular rubber matrices, such as SBR. This discovery suggests that the aluminum soap may reinforce the polymer matrices and offer some rheological benefits in resulting rubber compounds. We then incorporated 10 phr of the aluminum soap into a silica-filled tread rubber formulation. The results revealed significant enhancements in tensile strength, accompanied by reduced rolling resistance. These promising outcomes highlight the practical application potential of aluminum soaps in tread formulations.

Analyzing the Role of Media, ICTS, and Communication Networks in Promoting Development Goals, Social Change, and Political Participation in Nigeria

Analyzing the Role of Media, ICTS, and Communication Networks in Promoting Development Goals, Social Change, and Political Participation in Nigeria

Evaluation of the Iraqi Media Network's Proposed Strategy for the Period (2024-2028)

The strategy of the Iraqi media network has faced a significant challenge during the recent decades due to instability resulting from the political and security conditions experienced by Iraq. This deeply impacts various aspects of life, especially the media industry. In light of these circumstances, the idea of evaluating the proposed strategy for the Iraqi media network has emerged. The current research aims to study a crucial phase of strategic management, strategic evaluation, to assess the proposed strategy through data analysis, ensuring its implementation with minimal deviation from the planned course. The study focuses on studying and evaluating the proposed strategy for the Iraqi media network for the years 2024-2028, examining its effectiveness and alignment with the state's directions. That involves understanding the realism of strategic visions, plans, and programs and building a suitable conceptualization. This research focuses on environmental conditions and relies on scientific foundations and steps to formulate and evaluate the strategy. We created a study of senior figures, including general managers and experts in the Iraqi Media Network, 15 of whom purposefully selected the experts most relevant to the strategy and those responsible for evaluating it. The research hypothesis suggests a consensus among the network's managers and experts on the proposed strategy for the next five years in all its dimensions. The research results indicate that the reality of plans, programs, and visions is very good, developed by experienced leaders capable of evaluating the proposed strategy. The findings also demonstrate obvious acceptance of the strategy by the research sample and alignment with the proposed strategic alternative. Research Type: Research Paper

The Impact of Blind Box Economy on Consumer Behavior in Social Media Networks

Blind box is a kind of non-transparent box, consumers can not know in advance of the specific product style of the goods, and this random form of consumption is being sought after by a large number of young people. With the continuous enrichment of blind box products, in the era of social media, the blind box economy is growing stronger. Blind box economy, as a special consumption model, has risen rapidly in social media networks in recent years. This paper aims to explore the definition, characteristics, and effects of blind box economy on consumer behavior. Firstly, the definition and characteristics of blind box economy are introduced, including aesthetic experience, emotional value, social value, and second-hand value. Secondly, the influence path of blind box economy on consumer behavior is analyzed, and the interest groups, purchasing process, consumption behavior and symbol consumption are discussed. Finally, the positive and negative effects of blind box economy on consumer behavior are summarized, and relevant suggestions are put forward to promote the healthy development of blind box economy and the reasonable choice of consumers.

The Influence Of Social Presence, Physical Presence, And Trust On Impulsive Buying Behavior In Tiktok Live Users In Java Island

This research is a quantitative research that intends to determine the positive influence of social presence, physical presence, and trust separately on impulsive buying in TikTok Live users. Non-probability sampling technique with purposive sampling approach was used on 189 respondents with certain criteria, namely domiciled in Java, age range 18-34 years, and have shopped online through TikTok Live. Data collection techniques through Google Form questionnaires use Likert scale and processed using SPSS 27.The results showed that (1) Social presence (Sig = 0,001) had a significantly positive influence on the impulsive buying of TikTok Live users, (2) Physical presence (Sig = 0,025) had a significantly positive influence on the impulsive buying of TikTok Live users, and (3) Trust (Sig = 0.028) has a significantly positive influence on the impulsive buying of TikTok Live users. Technology in today's era has developed rapidly, making life more practical, because everything can be done through social media. With the application of technology, digital marketing has taken a leading role in all areas of marketing, creating an attractive landscape and atmosphere for customers, particularly in the field of social media networks, particularly TikTok Live.

Boring stories: What connects 18th-century shipping to today’s global media network?

Boring stories: What connects 18th-century shipping to today’s global media network?

The association of social networks with the job performance of primary health care professionals: the mediating effect of knowledge sharing.

Social networks formed through social media platforms have facilitated knowledge sharing among primary health care professionals (PHCPs). However, the impact of these networks on PHCPs' job performance and the mediating role of knowledge sharing remain underexplored. This study aimed to investigate the association between social networks formed via social media and the job performance of PHCPs, and to explore the mediating role of knowledge sharing in this association. A cross-sectional survey was carried out among PHCPs in Henan Province, China, involving 655 valid responses. Validated scales measured the key variables, and structural equation modeling (SEM) tested the proposed hypotheses, including the mediating effect of knowledge sharing through bootstrap method. Statistical analysis was performed using SPSS 24.0 and AMOS 24.0. The degree centrality (β = 0.225; p = 0.001) and network heterogeneity (β = 0.093; p = 0.043) of the social network had a significant direct association with job performance, whereas the direct associations of betweenness centrality and network tie strength with job performance were not significant. Knowledge sharing mediated the relationship between degree centrality (β = 0.147; p = 0.001), network heterogeneity (β = 0.251; p = 0.043), and job performance. The study revealed the internal mechanisms by which social network characteristics influence PHCPs' job performance, highlighting the mediating role of knowledge sharing. Social networks formed within social media contexts have multifaceted effects on job performance, with knowledge sharing as a critical mediating variable. These findings underscore the importance of leveraging social media for professional networking and knowledge exchange to enhance PHCPs' job performance.