Research on the Model of Consumer Health Information Seeking Behavior via Social Media

Purpose: We aim to create a model of consumer health information seeking behavior via social media, then to have a better understand of it. After that further efforts should be made to provide targeted recommendations for media managers to promote health communication via social media. Methods: Our custom model was derived from literature review, empirical research was tested by the use of questionnaire investigation, and then the collected data were analyzed by structural equation model tool SmartPLS. Finally, the custom model was modified according to the experimental results of SmartPLS. Results: A total of 239 (66.39%) of the respondents were female and 121 (33.61%) were male. The maximum of two stages of age were 18 - 29 (70.56%), 30 - 39 (13.89%). Wechat (60.28%), QQ Zone (55.22%), Micro-blog (48.89%) were the most commonly used social media to obtain health information. About 44.72% of respondents used social media to obtain health information multiple times a day. The whole numerical values of AVE, cronbach’s alpha, CR and square roots of AVE were above the benchmarks of themselves and showed great reliability and validity. All the 11 hypotheses had obvious statistical significance, the P-value of eight path coefficients exhibited <0.001, one path coefficient exhibited <0.01 and two path coefficients exhibited <0.05. Conclusions: A suitable model of consumer health information seeking behavior via social media was created and some inner relationships were found. Namely, gratification of health information and its platform had a positive effect on attitudes toward health information seeking behavior. Health information literacy and health status were proved to have a significant influence on attitudes toward health information seeking behavior, subject norms and perceived behavioral control respectively. In addition, attitudes toward the health information seeking behavior, subject norms and perceived behavioral control were proved to positively associate with health information seeking behavior intention.

Consumer’s Purchase Intention towards Luxury Retailer’s Social Media Advertisements —A Case Study of a Shoe Retail—UAE-Dubai Mall

Digital marketing is considered the preferred method comparing to traditional marketing nowadays [1], but is it true for luxury and expensive products? Since the perception prevails that the concepts “luxury” and “digital” are quite incompatible [2], this paper aims to explore the effectiveness of digital marketing advertisements of luxury retailers, while also exploring consumer’s purchasing intent based on the viewing of such promotions. The overall goal is to provide a model of luxury purchase behaviour through harnessing social media. As a constructionist ontology-based researcher, I believe in multiple versions of reality which can evolve based on my target consumer experiences [3]. My epistemological stance is interpretivism with a subjective approach, inductively interacting with consumers to better understand what this “truth” means to them, incorporating textual material to support the analytical interpretations [4]. It is hoped this paper will inform fashion brands marketers about social media practice to achieve creation of purchase intention and ultimately achieve target sales. The paper is useful to both practitioners and academics in the fields of social media marketing and purchase intention. The research provides some initial insights into consumer perspectives of social media ads and online purchase behaviour.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Associations between Social Media Use and Sleep Quality in China:Exploring the Mediating Role of Social Media Addiction

Sleep quality is closely linked to people’s health,and during the COVID-19 pandemic,the sleep patterns of residents in China were notably poor.The lockdown in China led to an increase in social media use,prompting questions about its impact on sleep.Therefore,this study investigates the association between social media use and sleep quality among Chinese residents during the COVID-19 outbreak,highlighting the potential mediating role of social media addiction.Data were collected via questionnaires through a cross-sectional survey with 779 valid responses.Variance analysis was used to test for differences in social media use among different demographic variables.Bivariate correlation analysis was employed to explore the relationships between variables,while regression analysis investigated the correlations between various media factors and sleep quality.Additionally,Bootstrap sampling was utilized to analyze the potential mediating influence of social media addiction in the relationship between social media use and sleep.The study's findings reveal a significant correlation between social media use,particularly before bedtime,and sleep quality(p<0.01),with pre-sleep activity notably linked to poorer overall sleep scores(β=0.141,p=0.004).Although the daily use of social media did not directly impact most individuals’sleep quality,specific platforms like news apps,short video apps,dating apps,and content community platforms were associated with higher levels of social media addiction,subsequently negatively affecting sleep quality.Specifically,the use of news apps(B=0.068,95%CI[0.000,0.019]),short video apps(B=0.112,95%CI[0.001,0.031]),dating apps(B=0.147,95%CI[0.000,0.028]),and content community platforms(B=0.106,95%CI[0.001,0.028])was found to increase the risk of social media addiction,subsequently leading to adverse effects on sleep quality.The study underscores a notable link between social media use and sleep quality,suggesting that mindful social media habits,particularly before bedtime,and reducing addiction-associated apps could enhance sleep quality.

Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

A study on the temperature sensitivity of NMR porosity in porous media based on the intensity of magnetization Dedicated to the special issue “Magnetic Resonance in Porous Media”

The measurement of nuclear magnetic resonance(NMR)porosity is affected by temperature.Without considering the impact of NMR logging tools,this phenomenon is mainly caused by variations in magnetization intensity of the measured system due to temperature fluctuations and difference between the temperature of the porous medium and calibration sample.In this study,the effect of temperature was explained based on the thermodynamic theory,and the rules of NMR porosity responses to temperature changes were identified through core physics experiments.In addition,a method for correcting the influence of temperature on NMR porosity measurement was proposed,and the possible factors that may affect its application were also discussed.

Acute Otitis Media in Children Aged 0-5 Years, Epidemiological Aspects and Management in the Paediatrics Department of the Hospital National Ignace Deen (Conakry)

Introduction: Acute otitis media is an acute inflammation of the mucosa of the middle ear cavities. It is often secondary to nasopharyngitis, which favors the passage of infection through the Eustachian tube to the middle ear. The aim of our study was to improve the management of AOM in the Paediatric Department of the Hospital National Ignace Deen (Conakry). Patients and Methods: This was a prospective descriptive study lasting 6 months from 01 July to 31 December 2011;the study covered 525 cases out of a total of 6276 children, i.e. a frequency of 8.36%. Results: The most affected age group was 6 to 11 months. Males predominated (69.71%). 82.29% had a history of recurrent rhinopharyngitis. The most frequent reason for consultation was incessant crying (66.29%). Rhinopharyngitis and malaria were the most commonly associated pathologies (87.62% and 39.62% respectively). 72.19% of our patients were admitted with congestive AOM and received medical treatment. We recorded one case of otomastoiditis which was treated surgically. Conclusion: AOM is more common in children aged between 6 and 24 months. Good collaboration between paediatricians and ENT specialists is essential to reduce the morbidity of AOM.

Co-infection with Neisseria mucosa in a patient with tuberculous otitis media

Tuberculous otitis media(TOM) is a rare manifestation caused by Mycobacterium tuberculosis with low incidence rates among extrapulmonary tuberculosis cases. Diagnosis is often delayed because of the presence of several clinical manifestations and the high prevalence of secondary bacterial infections. Few reports have attributed secondary bacterial infections in patients with TOM to commensal Neisseria. Thus, understanding the pathogenic mechanisms and clinical features of commensal Neisseria is important, considering its recent presentation as an infection-causing pathogen. Neisseria mucosa is a commensal inhabitant in humans and is generally considered non-pathogenic but can cause infection in rare cases. Here, we report an atypical secondary infection caused by Neisseria mucosa in an 81-year-old woman with TOM being treated for pulmonary tuberculosis. Direct purulent otorrhea smear microscopy revealed no acid-fast bacilli using Ziehl-Neelsen staining, whereas the phagocytosis of gram-negative cocci by white blood cells was confirmed using Gram staining. Otorrhea culture revealed the growth of N. mucosa. Subsequently, M. tuberculosis infection in the otorrhea was identified using a culture-based method. Vigilance is critical for the early detection of TOM to prevent further complications. This report raises awareness regarding TOM and provides insight into the pathogenicity of N. mucosa in otitis media.

Effects of confining pressure and pore pressure on multipole borehole acoustic field in fluid-saturated porous media

In-situ stress is a common stress in the exploration and development of oil reservoirs. Therefore, it is of great significance to study the propagation characteristics of borehole acoustic waves in fluid-saturated porous media under stress.Based on the acoustoelastic theory of fluid-saturated porous media, the field equation of fluid-saturated porous media under the conditions of confining pressure and pore pressure and the acoustic field formula of multipole source excitation in open hole are given. The influences of pore pressure and confining pressure on guided waves of multipole borehole acoustic field in fluid-saturated porous media are investigated. The numerical results show that the phase velocity and excitation intensity of guided wave increase significantly under the confining pressure. For a given confining pressure, the phase velocity of the guided wave decreases with pore pressure increasing. The excitation intensity of guided wave increases at low frequency and then decreases at high frequency with pore pressure increasing, except for that of Stoneley wave which decreases in the whole frequency range. These results will help us get an insight into the influences of confining pressure and pore pressure on the acoustic field of multipole source in borehole around fluid-saturated porous media.

An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.

Explosion of research on psychopathology and social media use after COVID-19:A scientometric study

BACKGROUND Despite advances in research on psychopathology and social media use,no comprehensive review has examined published papers on this type of research and considered how it was affected by the coronavirus disease 2019(COVID-19)outbreak.AIM To explore the status of research on psychopathology and social media use before and after the COVID-19 outbreak.METHODS We used Bibliometrix(an R software package)to conduct a scientometric analysis of 4588 relevant studies drawn from the Web of Science Core Collection,PubMed,and Scopus databases.RESULTS Such research output was scarce before COVID-19,but exploded after the pandemic with the publication of a number of high-impact articles.Key authors and institutions,located primarily in developed countries,maintained their core positions,largely uninfluenced by COVID-19;however,research production and collaboration in developing countries increased significantly after COVID-19.Through the analysis of keywords,we identified commonly used methods in this field,together with specific populations,psychopathological conditions,and clinical treatments.Researchers have devoted increasing attention to gender differences in psychopathological states and linked COVID-19 strongly to depression,with depression detection becoming a new trend.Developments in research on psychopathology and social media use are unbalanced and uncoordinated across countries/regions,and more indepth clinical studies should be conducted in the future.CONCLUSION After COVID-19,there was an increased level of concern about mental health issues and a changing emphasis on social media use and the impact of public health emergencies.

Predicting Users’ Latent Suicidal Risk in Social Media: An Ensemble Model Based on Social Network Relationships

Suicide has become a critical concern,necessitating the development of effective preventative strategies.Social media platforms offer a valuable resource for identifying signs of suicidal ideation.Despite progress in detecting suicidal ideation on social media,accurately identifying individuals who express suicidal thoughts less openly or infrequently poses a significant challenge.To tackle this,we have developed a dataset focused on Chinese suicide narratives from Weibo’s Tree Hole feature and introduced an ensemble model named Text Convolutional Neural Network based on Social Network relationships(TCNN-SN).This model enhances predictive performance by leveraging social network relationship features and applying correction factors within a weighted linear fusion framework.It is specifically designed to identify key individuals who can help uncover hidden suicidal users and clusters.Our model,assessed using the bespoke dataset and benchmarked against alternative classification approaches,demonstrates superior accuracy,F1-score and AUC metrics,achieving 88.57%,88.75%and 94.25%,respectively,outperforming traditional TextCNN models by 12.18%,10.84%and 10.85%.We assert that our methodology offers a significant advancement in the predictive identification of individuals at risk,thereby contributing to the prevention and reduction of suicide incidences.

Consumer Culture in The Great Gatsby

F.Scott Fitzgerald’s The Great Gatsby successfully portrays the“Jazz Age”.In the early 20th century,the United States transitioned from a production-based society to a consumer-based society,leading to an era of unparalleled prosperity.However,in the context of consumer culture,individuals often transition from being masters of their possessions to becoming enslaved by them.As a result,their behaviours and values become increasingly associated with extravagance and consumption.This paper uses Baudrillard’s theory of consumer society and textual analysis to explore the impact of consumer culture on human beings through the symbolization of men and objectification of women in The Great Gatsby.The meanings embedded in the novel are revealed from a different perspective.

The Media Logic and Cultural Impact of WeChat

Through its media logic, which is defined by programmability, pervasiveness, connectivity, and datafication, WeChat establishes a non-linear, interactive, and user-dominated media environment. This media logic enhances the influence of each user within WeChat’s narrative landscape and revolutionises traditional media narration methods by enabling them to generate and distribute content. In such an environment, users are able to edit, receive, and send information without constraints of time or distance, which enables delayed interactions that broaden the potential for human communication and dissemination. Additionally, WeChat partially replaces social behaviours and institutions, thereby modifying their original structures and characteristics. As individuals become more accustomed to this media environment, they progressively adjust to the forms that are appropriate for media representation on WeChat, thereby completing the mediatization of culture and society. In this process, individuals are becoming more dependent on media and media logic, with WeChat’s influence permeating social and cultural activities through its media logic. This interaction has a substantial impact on society and culture, thereby aiding in their reconstruction.

Consumers’ Perception and Knowledge of Food Additives in Senegal: A Pilot Study

Food safety has become a major concern for consumers, as well as a priority for regulatory authorities. Faced with the growing industrial and domestic use of food additives, many questions are being asked and concerns are being felt by consumers around the world. Consumer perception defines the acceptability or rejection of food products, and has an impact on consumption patterns and behavior. To assess the level of knowledge and perception of food additives, a pilot study was carried out on a sample of 200 people in Dakar and Saint-Louis. A questionnaire was used to assess the acceptance or rejection, use and impact of food additives by consumers in Senegal. The results revealed several aspects. On the whole, the people surveyed expressed great mistrust and even rejection of these substances added to food products. This consumer perception is shared throughout the world, as indicated in numerous surveys. It also emerges from this study that, although most consumers are aware of the existence of these additives and their uses in the home, they feel that the use of these substances in industrial production is too excessive. What’s more, consumers associate food additives with numerous pathologies such as cancer, diabetes, hypertension, stroke and even sexual impotence. For some of these indexed pathologies, scientific studies have reached the same conclusions, although controversy still persists. On the other hand, for some of the other adverse effects mentioned, no cause-and-effect relationship has been scientifically demonstrated. In these latter cases, it seems that negative communication, misinformation and misconceptions have a major influence on consumer perception of food additives.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Study on the Influence of Food Packaging on the Psychology of Different Groups of Consumers

With the vigorous development of consumer culture in today’s society,various types of food packaging also appear in front of consumers in different forms.There are very big differences in food packaging in terms of shape,color,style and other aspects of information transmission,which have the most direct impact on the audience’s food consumption needs.Driven by the consumption-oriented society,food packaging has shown very obvious comprehensive characteristics,is significantly interdisciplinary,and has close connections with other disciplines.This article will analyze and sort out the impact of food packaging on consumer psychology from different perspectives.

Anisotropic dynamic permeability model for porous media

Based on the tortuous capillary network model,the relationship between anisotropic permeability and rock normal strain,namely the anisotropic dynamic permeability model(ADPM),was derived and established.The model was verified using pore-scale flow simulation.The uniaxial strain process was calculated and the main factors affecting permeability changes in different directions in the deformation process were analyzed.In the process of uniaxial strain during the exploitation of layered oil and gas reservoirs,the effect of effective surface porosity on the permeability in all directions is consistent.With the decrease of effective surface porosity,the sensitivity of permeability to strain increases.The sensitivity of the permeability perpendicular to the direction of compression to the strain decreases with the increase of the tortuosity,while the sensitivity of the permeability in the direction of compression to the strain increases with the increase of the tortuosity.For layered reservoirs with the same initial tortuosity in all directions,the tortuosity plays a decisive role in the relative relationship between the variations of permeability in all directions during pressure drop.When the tortuosity is less than 1.6,the decrease rate of horizontal permeability is higher than that of vertical permeability,while the opposite is true when the tortuosity is greater than 1.6.This phenomenon cannot be represented by traditional dynamic permeability model.After the verification by experimental data of pore-scale simulation,the new model has high fitting accuracy and can effectively characterize the effects of deformation in different directions on the permeability in all directions.