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Unravelling Post-harvest Ripening Metabolomics of a New White Variety Guava Fruit (Cv Arka Mridula) with Special Emphasis on Phenolics and Corresponding Antioxidants
The phenolic, antioxidant and metabolic profiling of a new white variety guava fruit Arka Mridula (AM) was performed during its storage at theroom temperature (28 2 C). The comparative profiles were generated at three ripening stages (pre-ripe, ripe and over-ripe) of the fruit. Generally, a steady decrease of the phenolic and antioxidant content from the pre-ripe to the ripe stage and a subsequent increase from the ripe to over-ripe stage was observed. Further, a powerful correlation between the phenolic content and antioxidant principles was noted through the principal component analysis. We could identify 53 compounds for the hydro-methanolic fruit extract through LC and GC-MS aided metabolic analysis, and the identified compounds were dominated by phenolics (~ 44%). The statistical analysis revealed that phytochemicals catechin, myricitrin, myricetin, kaempferol glycosides and n-hexadecanoic acid contributed significantly towards the ripening process of AM, during the storage. The present study is expected to provide important insight into the ripening biochemistry of AM. Subsequently, it may help in the future development of metabolically stable guava cultivars with extended post-harvest shelf life. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Unravelling the potential plant growth activity of halotolerant Bacillus licheniformis NJ04 isolated from soil and its possible use as a green bioinoculant on Solanum lycopersicum L.
Immensely expanding world population and narrowing arable land for agriculture is a mighty concern faced by the planet at present. One of the major reasons for decline in arable lands is the increased soil salinity, making it unfavourable for crop cultivation. Utilisation of these saline land for agriculture is possible with suitable invention for improving the soil quality. Biofertizers manufactured out of Plant Growth Promoting Rhizobacteria is one such innovation. In the present study, Bacillus licheniformis NJ04 strain was isolated and studied for its halotolerance and other effective plant growth promoting traits. The NJ04 strain was able to tolerate salt up to 10% and highlighted remarkable antifungal activity against common fungal phytopathogens. The preliminary seed germination test in Solanum lycopersicum seeds revealed a significant increase in root length (16.29 0.91 cm) and shoot length (9.66 0.11 cm) of treated plants as compared with the control plants and thereby shows its possible use as a green bioinoculant in agriculture and an ideal candidate to compete with salt stress. 2022 Elsevier Inc. -
Unseen motivators: A study exploring the effect of subliminally priming known human faces vs unknown human faces on consumers product selection decisions
The human mind is constantly being influenced by a vast number of external stimuli that are perceived consciously as well as unconsciously. The chapter attempts to explore how unconscious (subliminal) priming of known and unknown human faces could impact product selection and decision-making time of consumers. 2 (Known face X Unknown face) X 2 (Product selection X Decision-making time) within-subject design was used for the study. A pilot study was conducted to estimate the subliminal time threshold of the population. It was found to be 17ms. A stimulus-priming experiment designed in Opensesame software was used to subliminally expose the participants to both known and unknown human faces. They were then asked to select a product that they were willing to buy from an option of four products, of which one of the products was primed along with human face (known vs. unknown). The product selection rates as well as the time taken to select the product were recorded. A total of 100 participants falling in the age category of young adults (18-39) took part in the study. 2024, IGI Global. All rights reserved. -
Unsteady natural convection in a liquid-saturated porous enclosure with local thermal non-equilibrium effect
Stability analysis of free convection in a liquid-saturated sparsely-packed porous medium with local-thermal-non-equilibrium (LTNE) effect is presented. For the vertical boundaries freefree, adiabatic and rigidrigid, adiabatic are considered while for horizontal boundaries it is the stress-free, isothermal and rigidrigid, isothermal boundary combinations we consider. From the linear theory, it is apparent that there is advanced onset of convection in a shallow enclosure followed by that in square and tall enclosures. Asymptotic analysis of the thermal Rayleigh number for small and large values of the inter-phase heat transfer coefficient is reported. Results of DarcyBard convection (DBC) and RayleighBard convection can be obtained as limiting cases of the study. LTNE effect is prominent in the case of BrinkmanBard convection compared to that in DBC. Using a multi-scale method and by performing a non-linear stability analysis the GinzburgLandau equation is derived from the five-mode Lorenz modal. Heat transport is estimated at the lower plate of the channel. The effect of the Brinkman number, the porous parameter and the inter-phase heat transfer coefficient is to favour delayed onset of convection and thereby enhanced heat transport while the porosity-modified ratio of thermal conductivities shows the opposite effect. 2020, Springer Nature B.V. -
Unsteady squeezing flow of a magnetized nano-lubricant between parallel disks with Robin boundary conditions
The aim of the present work is to examine the impact of magnetized nanoparticles (NPs) in enhancement of heat transport in a tribological system subjected to convective type heating (Robin) boundary conditions. The regime examined comprises the squeezing transition of a magnetic (smart) Newtonian nano-lubricant between two analogous disks under an axial magnetism. The lower disk is permeable whereas the upper disk is solid. The mechanisms of haphazard motion of NPs and thermophoresis are simulated. The non-dimensional problem is solved numerically using a finite difference method in the MATLAB bvp4c solver based on Lobotto quadrature, to scrutinize the significance of thermophoresis parameter, squeezing number, Hartmann number, Prandtl number, and Brownian motion parameter on velocity, temperature, nanoparticle concentration, Nusselt number, factor of friction, and Sherwood number distributions. The obtained results for the friction factor are validated against previously published results. It is found that friction factor at the disk increases with intensity in applied magnetic field. The haphazard (Brownian) motion of nanoparticles causes an enhancement in thermal field. Suction and injection are found to induce different effects on transport characteristics depending on the specification of equal or unequal Biot numbers at the disks. The main quantitative outcome is that, unequal Biot numbers produce significant cooling of the regime for both cases of disk suction or injection, indicating that Robin boundary conditions yield substantial deviation from conventional thermal boundary conditions. Higher thermophoretic parameter also elevates temperatures in the regime. The nanoparticles concentration at the disk is boosted with higher values of Brownian motion parameter. The response of temperature is similar in both suction and injection cases; however, this tendency is quite opposite for nanoparticle concentrations. In the core zone, the resistive magnetic body force dominates and this manifests in a significant reduction in velocity, that is damping. The heat build-up in squeeze films (which can lead to corrosion and degradation of surfaces) can be successfully removed with magnetic nanoparticles leading to prolonged serviceability of lubrication systems and the need for less maintenance. IMechE 2021. -
Unsteady thin film flow with ohmic heating and chemical reactions
In this study, we have analyzed magnetohydrodynamic (MHD) consequences on the heat and mass transmission within unsteady dissipated liquid film flow. Flow is generated due to stretchable surface accompanied with effects of ohmic heating, chemical reaction and heat absorption. Moreover, the flow governing partial differential equations (PDEs) are further modified into equivalent ordinary differential equations (ODEs) by applying regular perturbation method to get its analytical solution after that we have applied sixth-order RungeKutta technique to get its numerical solution. These two solutions are validating each other in the simulations. Figures are plotted to study the changes in physical quantities like skin friction coefficient, concentration, velocity, temperature, Sherwood and Nusselt number with the variations of Prandtl numbers Pr, parameters of chemical reaction ?, Eckert numbers Ec, magnetic parameter Ha (also known as Hartman number) Schmidt number and coefficient of heat absorption ?. World Scientific Publishing Company. -
Unsteady three-dimensional MHD flow of a nano Eyring-Powell fluid past a convectively heated stretching sheet in the presence of thermal radiation, viscous dissipation and Joule heating
The purpose of this study is to investigate the unsteady magnetohydrodynamic three-dimensional flow induced by a stretching surface. An incompressible electrically conducting Eyring-Powell fluid fills the convectively heated stretching surface in the presence of nanoparticles. The effects of thermal radiation, viscous dissipation and Joule heating are accounted in heat transfer equation. The model used for the nanofluid includes the effects of Brownian motion and thermophoresis. The highly nonlinear partial differential equations are reduced to ordinary differential equations with the help of similarity method. The reduced complicated two-point boundary value problem is treated numerically using RungeKuttaFehlberg 45 method with shooting technique. A comparison of the obtained numerical results with existing results in a limiting sense is also presented. At the end, the effects of influential parameters on velocity, temperature and nanoparticles concentration fields are also discussed comprehensively. Further, the physical quantities of engineering interest such as the Nusselt number and Sherwood number are also calculated. 2016 University of Bahrain -
Unsupervised Feature Selection Approach for Smartwatches
Traditional feature selection methods can be time-consuming and labor-intensive, especially with large datasets. This studys unsupervised feature selection approach can automate the process and help identify important features preferred by a particular segment of users. The unsupervised feature selection method is applied for smartwatches. Smartwatches continue to gain popularity. It is important to understand which features are most important to users to design and develop smartwatches that are more engaging, user-friendly, and meet the needs and preferences of their target audience. The rapid pace of technological innovation in the smartwatch industry means that new features and functionalities are constantly being developed. Multi-cluster feature selection, Laplacian score, and unsupervised spectral feature are used. Conjoint analysis is done on the most common features in all three selection methods. The unsupervised feature selection technique is used for identifying the relevant and important features of new smartwatch users.The practical implication of the research is in the application of the technique in the new product design of smartwatches. The result of the study also informs smartwatch manufacturers and developers on the features they need to prioritize and invest in. This can ultimately result in better and more user-friendly smartwatches and a good overall experience for the user. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Unsupervised Learning for Understanding Diversity: Applying Feature Engineering and Cluster Analysis to Deaf and Hard of Hearing Data
As e-Learning emerges as a promising tool for instruction delivery, personalizing the e-Learning platform for DHH learners will benefit them to improve their learning engagement and educational attainment. This study aims to collect and analyze the different features unique to DHH learners and analyze the significant features among them. This study highlights the importance of addressing the diversity among DHH learners, while creating a personalized learning environment for them. With this focus, we employ the K-Means clustering algorithm to group the learners based on similar needs and preferences and identified that distinguishing clusters can be formed within the DHH group. We also tried to understand the significant features contributing to forming well separated groups. These results provide valuable insights into the diverse preferences and requirements when they interact with the learning materials. These findings emphasize the significance of personalized approach for DHH learners in educational settings and serve as the stepping stone to develop a personalized learning environment for them. 2024 IEEE. -
Untold and Painful Stories of Survival: The Life of Adolescent Girls of the Paniya Tribes of Kerala, India
Tribal adolescent girls are vulnerable to neglect, abuse and exploitation across the world. Literature on the status of adolescents belonging to the Paniya tribe is scanty. However, limited information about the Paniya tribe of Kerala indicates that they are neglected and deprived from basic facilities. According to the Census Report of India (2011), 49.5% of the Paniya tribe members are literate. The lives of adolescents in the Paniya community are distinct from those of other sections of society, and they are yet to be addressed by the government or the media. The objective of this chapter is to discuss the issues and concerns of Paniya adolescent girls of Kerala. A Paniya girl from Vattachira (Calicut) treks around 2 km during her menstruation to fetch fresh and clean water. They use pieces of clothes to manage menstruation since they do not have access to pads or tampons. Drying their garments during the rainy season is difficult, which leaves them susceptible to rashes and infections. They are provided with residential educational facilities by the government, but they are unable to adjust to the lifestyles of other members of the society and are frequently bullied and discriminated, leading to school dropouts. Sexual exploitation by strangers and community members is widespread among Paniya girls, and unmarried mothers under the age of 18 are also prevalent among this community. The chapter highlights upon some of the challenges of the Paniya Tribal adolescent girls of Kerala and offers some suggestions for improving the quality of life of this marginalized group, which will assist the policymakers and government for taking need-based measures. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Untold Stories from the Slums: A Qualitative Exploration of the Lives of Female Informal Waste Workers
The present study investigates the nuanced experiences of urban informal waste workers, shedding light on the intricate realities shaping their daily lives. Employing purposive sampling, in-depth interviews were conducted, specifically targeting female participants aged eighteen and above, engaged in informal waste work for a minimum duration of one year. A total of ten in-depth interviews were meticulously executed, with recordings subsequently translated and transcribed for thorough analysis. Utilizing Braun and Clarks thematic analysis method, a comprehensive examination of the data yielded a hierarchical structure comprising codes, sub-themes, and overarching themes. The central themes identified encapsulate the multifaceted challenges encountered by urban informal waste workers, including Occupational Hardships and Vulnerability, Economic Struggles and Diminished Quality of Life, Commitment to Family, Emotional and Psychosocial Challenges, Appreciation and Acknowledgment of Support Received, Decreased Willingness to seek help, and Aspirations and Hopes for the future. By amplifying the voices of these marginalized workers, this study advocates for the implementation of inclusive policies and interventions tailored to address their diverse needs within the urban milieu. Through its findings, the study aims to cultivate a more compassionate and supportive environment that not only recognizes the invaluable contributions of urban informal waste workers but also strives to enhance their overall well-being and socio-economic standing. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Unusual Generation of Filament-Like Crystal on Vapor-Deposited Sb2Se3 Whiskers Under Ambient Atmosphere
This research article proposes a novel strategy to explore the nucleation and growth mechanism of a filamentary spike-like feature (secondary growth) on vapor-deposited antimony selenide (Sb2S3) whiskers (primary crystallization) due to the influence of electric fields, defects, and ambient atmosphere. Small, ultra-long, branched whiskers were produced by the physical vapor deposition (PVD) method utilizing a homemade tubular furnace. In order to grow these crystal features, a temperature difference (?T) of 180C was maintained by adjusting the temperature in the hot (710C) and cold zones (530C), followed by a fast cooling rate of 12C/min. Optical and scanning electron microscopy, three-dimensional (3D) profilometry, and Raman imaging analysis were utilized to investigate the surface features of the as-grown and electrically activated whiskers under ambient atmosphere. A possible crystallization (secondary growth) mechanism of the filamentary crystals in the defective region under the influence of an electric field was proposed. We noted that the effect of extrinsic impurities like oxygen coupled with an electric field promoted the growth of filamentary crystals on the whiskers, which were probed utilizing x-ray diffraction (XRD), energy-dispersive x-ray analysis (EDAX), x-ray photoelectron spectroscopy (XPS), Raman analysis, thermogravimetric analysis (TGA), and differential thermal analysis (DTA). An orthorhombic crystal structure with unit dimensions of a = 11.632 b = 11.798 and c = 3.987was calculated from the XRD results. This research provides a new growth mechanism and a comprehensive picture of nucleation followed by branching of filamentary crystals on the primary crystallized Sb2Se3 whisker surface. The research output with regard to layered chalcogenide materials (LCMs) will undoubtedly help researchers focus on removing secondary/whisker growth from LCM-based optoelectronic devices. The Minerals, Metals & Materials Society 2025. -
Unveiling Cutting Edge Innovations in the Catalytic Valorization of Biodiesel Byproduct Glycerol into Value Added Products
The increasing production of biodiesel has led to a glut in the production of glycerol, which is a byproduct. This has resulted in the quest for alternative applications using glycerol as a cheap and readily available starting material. One promising approach is the catalytic valorization of glycerol, which converts glycerol into valuable chemicals such as 1,2-propanediol, lactic acid, and acrolein. The glycerol formed affects the efficiency of the biodiesel, and hence it must be removed. Different processes can convert glycerol to various useful products like glycerol carbonate, glycidol, solketal, lactic acid, and glyceric acid. These different products, the processes used for synthesis, and the various catalysts used have been discussed. The most effective methods for the syntheses, the numerous catalyst systems, mechanisms of the reactions, and applications of these products in different fields are discussed in this review. The paper also discusses the challenges and opportunities of glycerol valorization, including the need for improved catalyst selectivity and activity and the potential for integrating glycerol valorization with other biorefinery processes. Overall, the catalytic valorization of glycerol offers a promising pathway for utilizing this abundantly available resource, and this review provides valuable insights for researchers and practitioners working in this area. 2023 Wiley-VCH GmbH. -
Unveiling Dynamics of Structural Breaks in Global Stock Markets and Implications for Forecasting Accuracy
This research investigates structural breaks in global stock markets, employing the Chow test on major indices from January 2013 to November 2023. Results reveal significant breaks in NYSE (November 2020) linked to the US election and positive vaccine trials, Nasdaq (May 2020) amidst global concerns over COVID-19, and Euronext 100 (February 2021), suggesting market shifts. Notably, Shanghai Stock Exchange experienced a robust break in December 2014, contrasting with SZSE's non-significant break. HKEX experiences a significant shift in June 2020, possibly influenced by US regulatory policies and COVID-19. The Nifty index shows a profound break in December 2020, correlated with pandemic severity. LSE Group evidences a break in July 2019, while the Saudi Exchange shows non-significant evidence in March 2021. The study underscores the importance of considering structural breaks for accurate market forecasting and decision-making. Descriptive statistics provide insights into market characteristics. The methodology integrates the Chow test and CUSUM squares for break detection. Findings contribute to understanding global market dynamics and emphasize the impact of external events on structural stability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Unveiling Future Trends in Employer Branding: Systematic Review and Bibliometric Analysis
Employer branding, an emerging area in Human Resource Management (HRM), has gained significant importance. Despite its importance, the literature on employer branding remains fragmented due to the absence of a comprehensive review that consolidates the intellectual structure of the field. This study addresses the existing knowledge gap by conducting a systematic literature review accompanied by bibliometric analysis utilizing performance analysis and science mapping through the Tableau software package. Through a comprehensive review of 27 articles, this study reveals the key branding elements, top journals, contributing countries, industries, citation trends, sample statistics, theoretical contribution, and six key themes (i.e., Employer branding attributes, sustainable employer branding, employee-centric employer branding, social media employer branding, recruitment strategies, HRM practices of employer branding) that characterize the body of the employer branding. Finally, the study has identified an integrative framework and set the direction for future research. It offers actionable recommendations for HR practitioners, emphasizing technology integration in employer branding initiatives and incorporating sustainable practices to enhance organizational attractiveness. This research contributes to a deeper understanding of the concept of employer branding. It provides valuable guidance for organizations seeking to navigate and optimize their employer branding strategies for the future. (2025), (Regional Inform. Center for Sci. and Technol.). All rights reserved. -
Unveiling Green Supply Chain Practices: A Bibliometric Analysis and Unfolding Emerging Trends
Supply chain management is a multi-dimensional approach. Growing eco-consciousness has forced businesses to optimize operations and incorporate green practices across all the stages of supply chain in manufacturing and service sectors. Reviewing the past research literature propels us to understand its current and future prospects. Employing a systematic analysis, this research explores the intellectual structure of green supply chain practices and their connection to performance outcomes in various industries. This study covers a systematic literature review, content analysis, and bibliometric analysis on green supply chain management using VosViewer. It utilizes a PRISMA-guided screening method for identification, screening, eligibility and inclusion of literature from the literature available since 1999. The bibliometric analysis reveals key contributors, thematic clusters, prevailing theoretical frameworks, and emerging research trends in the domain of green supply chain management. China, followed by the United States and the United Kingdom, emerged as leading contributors to research in this area, driven by rapid economic growth, heightened environmental concerns, and well-established academic and industrial infrastructures. The study identifies eight thematic clusters within green supply chain management, including the triple bottom line, circular economy, and carbon emissions. The most highly cited papers within these clusters were examined for their methodologies, tools, and key findings, highlighting the prominent theories utilized in this field. Moreover, the research discusses how advanced technologies such as AI, blockchain, and big data analytics are poised to transform supply chains by enhancing decision-making and mitigating risks, thus playing a pivotal role in the future of green supply chain management. Copyright 2024 CA Rajkiran, Shaeril Michel Almeida. -
Unveiling mental health nuances of male Indian classical dancers.
This study explores the lives of male Indian classical dancers, highlighting the duality of dance as a sanctuary and a stressor. As male Indian classical dancers negotiate and redefine norms of masculinity, the study calls for recognition of diverse masculine identities within traditionally feminized spaces. (PsycInfo Database Record (c) 2026 APA, all rights reserved) 2025 American Psychological Association All rights, including for text and data mining, AI training, and similar technologies, are reserved.; This research explores the mental health nuances of male Indian classical dancers (MICDs), through a lens of redefining masculinity, focusing on their perceived quality of life, psychosocial challenges, and coping strategies. This study follows an interpretive phenomenological approach to follow the lived experiences of MICDs. The participants are male, fluent in English, and pursuing Indian classical dance styles professionally, like Kathak, Bharatanatyam, Chhau, etc. Six participants were recruited for personal, semistructured, in-depth interviews, whereas, a focus group discussion with four participants was conducted to explore the stigma. The data were analyzed using interpretive phenomenological analysis, revealing themes of (a) identity fragmentation and negotiation in gendered social contexts, (b) gendered experiences, (c) emotional distress and psychological challenges, (d) coping mechanisms and resilience, and (e) stigmatization and social integration dynamics. MICDs grapple with identity formation, navigating a paradox of self-perception, artistic identity, and societal expectation. They reported experiencing emasculation, compromising artistic expression, and struggling with gender norms and gendered training constraints. They have faced name-calling, bullying, taunting, slandering, and discrimination leading to psychological challenges and distress. However, the paradox continues as male dancers use adaptive coping strategies despite the adversities that intertwine self-perception, societal pressures, and their passion for dance. These findings provide a strong foundation for making changes in the dance community for acceptance of male dancers, policy making for better job opportunities for male dancers, and mental health services to be provided to help them deal with distress. (PsycInfo Database Record (c) 2026 APA, all rights reserved) 2025 American Psychological Association All rights, including for text and data mining, AI training, and similar technologies, are reserved. -
Unveiling metaverse sentiments using machine learning approaches
Purpose: The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers ones intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience. Design/methodology/approach: The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently. Findings: The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models. Research limitations/implications: Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverses experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverses economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust. Social implications: In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators. Originality/value: The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models. 2024, Emerald Publishing Limited. -
Unveiling metaverse sentiments using machine learning approaches
Purpose: The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers ones intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience. Design/methodology/approach: The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently. Findings: The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models. Research limitations/implications: Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverses experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverses economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust. Social implications: In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators. Originality/value: The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models. 2024, Emerald Publishing Limited.