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Right to Education Sans Development: An Analysis of the Educational Status of Children Living in Slums
India, as a developing country, has been facing many challenges. Of them, providing free and compulsory education to all its children is one such challenge. Despite many efforts by the law makers and executives, education to all the children remains a distant dream. Poverty and accessibility are cited as two important reasons for the short fall. Comparing to their counterparts, the situation of children living in slums is more vulnerable to exploitation. Taking into account this scenario, the present study attempts to understand the various problems faced by the children living in slums in pursuing their education. The researcher is hopeful of getting some valuable insights into the issue to support suitable remedial measures to improve the educational status of children living in slums. Bangalore alone holds around 570 slums and above 5 lakhs of people living in them. The constitution already gives the right for free education, up to 10th standard which can be utilized by them, which in turn can help in free and compulsory education for everyone. If the people are educated they can improve their standard of living and so be able to create an atmosphere altogether better than the slums. The study tries to look upon the role of social and economic situation of children in their education. It also seeks to understand the reasons for the attrition rate and will strive to find out if there is any discrimination the candidate faces while pursuing education. It also focusing the the relevance of the present Right to Education Act, (2010) on the light of data collected. It also tries to find out some solution to improve educational participation of children living in the slums of Bangalore. Education is the gateway to success in life. The importance of education is not realised by all. Education has been thought to bring about a qualitative difference in the life of individuals and groups. Significance is to bring about a social change through information about the provisions of education and the right of every individual to education, it is expected that the demand for education will grow. This consciousness can be brought about through the process of education itself. It is one of the most important responsibilities of the governments and people involved in human affairs to find means and ways to make it available to all on an equitable basis. With an analysis of various articles, books, journals and research findings, the paradigm of the study becomes clear. Review done in the initial stage of the study, equips the researcher in a better way to understand the various concepts, key variables, methods and the history of the topic being studied. Review of literature is a collective body of works done by scholars and published in the form of books or in the form of articles in journals or published as monograph etc. Every research starts with a Review of Literature. These materials are gathered by the researcher from many sources such as journals, books, documents etc. The Researcher feels that it is essential to understand the problems faced by slum dwellers in getting access to education in the selected slums of Bangalore. Researcher also felt it important to compare the slums as they are distinct in terms of their social and economic conditions. For the present study, the researcher has selected two slums in Bangalore urban purposefully which is Bommanahalli and Kannahalli. Each slum is distinct in terms of its character and population. From each slum, 50 households were identified randomly from households with children below the age of 15, either school going or dropouts. The researcher has used the descriptive design for the study. Descriptive research is used to obtain information concerning the current status of the phenomena to describe "what exists" with respect to variables or conditions relating to the educational status of children living in slums. The methods involved range from the survey which describes the status quo, the correlation study which investigates the relationship between variables, to developmental studies which seek to determine changes over time. Researcher has used both primary and secondary data. Primary data which is provided by the researcher is an original one. Researcher has collected these data from the slums selected. For the collection of primary data, the researcher has used Focus Group Discussions, Interview schedule and Interview Guide as tools. From the study researcher has understood that these people are socially and financially backward. Their income is not enough to satiate their daily needs, which makes it further difficult for supporting education. Their backwardness and illiteracy does not give them a proper job. This results in other members of the family including housewives also to work for supporting themselves. Most of the families in order to reduce their expenses have limited themselves to nuclear family structure and also the number of children is a maximum of two. In some families the parents are not taking any initiative in educating their girl child. Most of them consider it is a waste of money. They prefer only the career for their male child. The dropout rates are very high in these two slums. In each year, 20% dropouts are registered. Financial instability or the poverty is the main cause of dropout. Most of the children are going out for work so they are not getting proper time to study. Some of them are facing discrimination from their friends and teachers .High levels of discriminations reported in private schools. Some of them are lacking support from their parents. There is no good school in their locality and the distance of the school is also a main cause for high dropout rate. The parents cannot afford the travelling cost of their children. Less attention by the teachers towards the children is also a reason. People did not know about the RTE Act and its provisions or privileges. Most of them did not get admission on the basis of RTE. Some schools have not properly implemented the RTE Act. The researcher has brought out the following suggestions for the study or the problem. These suggestions are collected from the population selected for the study. The Government should be able to implement the Right to education act. It should be effective in each and every school, rather than being only in papers. Every effort to open more and more schools for the backward section in the society should be taken into prior consideration by the Government in the centre and also within the states. More concentration on educating the slum children should also be initiated and the Government should be able to open schools in the surrounding areas of slum. Right to education act, should not only be an act in papers and something which is kept within protected walls. All efforts for publicity of the Act should be taken in by the government. It should be publicized in such a manner that all the doubts concerning the act be cleared. More and more advertisement or campaign regarding the right to education act and its facilities should be initiated. The privileges of the backward sections be made cleared to them, so that these sections of society are aware of their privileges and are able to use it. All effort should be taken by the Government to provide some more privileges to the backward sections and they should implement that in a proper way. -
Molecular detection of Kudoa septempunctata (Myxozoa: Multivalvulida) in sea water and marine invertebrates
The exportation of cultured olive flounder (Paralichthys olivaceus) in Korea has been recently decreasing due to the infections with a myxozoan parasite Kudoa septempunctata, and there is a strong demand for strict food safety management because the food poisoning associated with consumption of raw olive flounder harbouring K. septempunctata has been frequently reported in Japan. The life cycle and infection dynamics of K. septempunctata in aquatic environment are currently unknown, which hamper establishment of effective control methods. We investigated sea water and marine invertebrates collected from olive flounder farms for detecting K. septempunctata by DNA-based analysis, to elucidate infection dynamics of K. septempunctata in aquaculture farms. In addition, live marine polychaetes were collected and maintained in well plates to find any possible actinosporean state of K. septempunctata. The level of K. septempunctata DNA in rearing water fluctuated during the sampling period but the DNA was not detected in summer (June-July in farm A and August in farm B). K. septempunctata DNA was also detected in the polychaetes Naineris laevigata intestinal samples, showing decreased pattern of 40 to 0%. No actinosporean stage of K. septempunctata was observed in the polychaetes by microscopy. The absence of K. septempunctata DNA in rearing water of fish farm and the polychaetes N. laevigata intestinal samples during late spring and early summer indicate that the infection may not occur during this period. N. laevigata was suspected as the possible alternate invertebrate host of K. septempunctata, but the actinosporean stage was not found by well plate method and further studies will be necessary. This research provides important baseline information for understanding the infection dynamics of K. septempunctata in olive flounder farms and further establishment of control strategies. 2017 The Author(s). -
MXene Composite-Based Nanogenerators and Applications
Energy harvesting modules are becoming increasingly vital for developing autonomous, self-powered microelectronic devices. MXenes, a class of two-dimensional (2D) transition metal carbides/nitrides, have recently gained attention as promising candidates for energy applications due to their excellent electrical conductivity, large specific surface area, and tunable properties. MXene-based nanogenerators (NGs) represent a cutting-edge advancement in energy harvesting technology, harnessing the unique properties of MXenes to enhance performance. Incorporating MXenes into composite materials facilitates efficient ion/electron transport and increases the surface charge density, leading to higher output performance. Additionally, MXenes abundant functional groups and tunable surface properties enable strong interactions with polymer matrices, resulting in composites with superior mechanical strength and flexibility. This book chapter delves into the various properties of MXenes, highlighting their importance in energy harvesting technology and their inherent piezoelectric properties. It also covers using MXene-based composite materials in NG technology, focusing on MXenepolymer, MXenemetalorganic framework (MOF), and MXenecarbon composites. Additionally, the chapter discusses the applications of these composite-based NGs in various fields, including wearable technology and biomedical devices. Finally, the chapter summarizes the recent advancements in this field and future aspects in enhancing the use of MXene in energy harvesting technology. 2026 Taylor & Francis Group, LLC. -
Rain of Life, Rain of Music: Music as Life Power in Indian Thought and Contemporary Musical Traditions
Conceived as a life force, rain has a significant place in Indian thought. Sanskrit and vernacular literary and religious texts, as well as visual arts, emphasise its auspiciousness and importance in human life. Additionally, through the use of poetical images and metaphors, these texts and images associate rain with music and identify thunder with drums. Through the analysis of compositions from the repertoire of different drums such as the dhrupad pakh?vaj, the mi??vu of K?tiy???a? Sanskrit theatre, and the ritual music of Brahmanical temples of Kerala, this article studies the association of drumming with rain as a symbol of life force, consciousness and enlightenment. 2022 South Asian Studies Association of Australia. -
Human Consumption of Digital Synthetic Outputs: Cross Checking Real or Fake Information
AI-Generated content, deepfakes and synthetic media, people are increasingly wondering how they can discern the difference between genuine and fake. People may become confused, change their minds, and make unwise decisions that put their safety at danger when they see false information and manipulated pictures and videos, such AI-generated deepfakes. AI detection techniques, and teaching people how to read and write have all helped with these difficulties. Blockchain technology analyzes the digital history of anything to make sure it is authentic. Two significant steps toward making things more open are regulatory frameworks and ethical AI practices. Users should be vigilant and examine a lot of trustworthy sources, including reverse image search or deepfake detectors. The influence of incorrect information will be lessened if individuals are more informed and encouraged to utilize internet resources properly. To use another metaphor, let's make sure that people know what they're talking about when we speak about synthetic things. 2026, IGI Global Scientific Publishing. All rights reserved. -
A Hybrid Deep-ensemble Decision-Support Framework for Reliable Early Breast Cancer Detection: A Cross-validated Outcome Analysis
OBJECTIVE The necessity to diagnose breast cancer early and correctly is the need to minimize the diagnostic uncertainty and unwarranted clinical procedures. This paper assesses the reliability of a hybrid deep-ensemble decision-support model in terms of diagnostic reliability, stability of outcome, and translational feasibility of the model via structured clinical data to detect early breast cancer. METHODS The Wisconsin Diagnostic Breast Cancer dataset which consisted of 569 cases of benign and malignant tumors was analyzed retrospectively. The framework proposed combines the deep learning of latent representations with stacked classification, ensemble-based feature selection, and stacked classification. Performance evaluation was performed based on sensitivity, specificity, accuracy, F1-score, and area under the curve (AUC) performed using stratified 10-fold cross-validation. The statistical stability across folds and the comparison with baseline models were determined with the help of non-parametric tests (p<0.05). RESULTS The model had good diagnostic performance with an accuracy of between 91.2-100 (Mean 96), Sensitivity of 76.2-100, good specificity value, and AUC 0.973-1.000. Variability in performance between folds was low, and statistically significant enhancement as compared to baseline classifiers were present. CONCLUSION The hybrid deep-ensemble model is highly diagnostic, has robust discriminative ability, and ultimately remains stable, which demonstrates the methodological robustness and diagnostic reliability of the proposed framework as a proof-of-concept decision-support model for early breast cancer detection, with potential translational relevance subject to further external clinical validation. 2026, Turkish Society for Radiation Oncology. -
A Novel Machine Learning-Based Prediction Method for Early Detection and Diagnosis of Congenital Heart Disease Using ECG Signal Processing
Congenital heart disease (CHD) represents a multifaceted medical condition that requires early detection and diagnosis for effective management, given its diverse presentations and subtle symptoms that manifest from birth. This research article introduces a groundbreaking healthcare application, the Machine Learning-based Congenital Heart Disease Prediction Method (ML-CHDPM), tailored to address these challenges and expedite the timely identification and classification of CHD in pregnant women. The ML-CHDPM model leverages state-of-the-art machine learning techniques to categorize CHD cases, taking into account pertinent clinical and demographic factors. Trained on a comprehensive dataset, the model captures intricate patterns and relationships, resulting in precise predictions and classifications. The evaluation of the models performance encompasses sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. Remarkably, the findings underscore the ML-CHDPMs superiority across six pivotal metrics: accuracy, precision, recall, specificity, false positive rate (FPR), and false negative rate (FNR). The method achieves an average accuracy rate of 94.28%, precision of 87.54%, recall rate of 96.25%, specificity rate of 91.74%, FPR of 8.26%, and FNR of 3.75%. These outcomes distinctly demonstrate the ML-CHDPMs effectiveness in reliably predicting and classifying CHD cases. This research marks a significant stride toward early detection and diagnosis, harnessing advanced machine learning techniques within the realm of ECG signal processing, specifically tailored to pregnant women. 2024 by the authors. -
Sodium AlginateEngineered CaF? NPs: Surface Passivation, and Tunable Biofunctional Performance
The optimization of surface chemistry in nanomaterials is vital for enhancing their applicability in advanced healthcare sectors. This study focuses on synthesizing polymer-functionalized NPs (NPs) to improve structural stability and biological efficacy against a broad spectrum of pathogens. Herein, calcium fluoride (CaF?) and sodium alginate-functionalized CaF? (CaF?SA) NPs were synthesized to determine the impact of SA on physicochemical and optical properties. The synthesized NPs were extensively characterized using XRD, UV-Vis, DLS, FTIR, PL, electron microscopy (SEM/TEM), and XPS. Their enhanced performance is attributed to defect passivation, reduced crystallite size, and the formation of a homogeneous organic-inorganic interface through strong chemical interactions between Ca? sites and alginate functional groups. The CaF?SA NPs exhibited superior broad-spectrum antimicrobial activity compared to bare CaF? against S. aureus, S. pneumoniae (Gram-positive), K. pneumoniae, E. coli (Gram-negative) and C. albicans (fungal strains). The quantitative assessments via MIC, MBC, and CFU assays confirmed effective inhibition of CaF2-SA. These findings highlight defect modulation and polymer passivation as powerful strategies, suggesting CaF?SA NPs as promising candidates for advanced bio-interactive and healthcare applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. -
Assessing the role of trade openness, FDI, and political stability on sustainable development: Evidence from developed and developing economies
The study tries to investigate the long run and short run relationship between trade openness (TO), political stability (PO), and FDI on sustainable development of select developed and developing nations. Time series data from 1995 to 2021 of about 25 economies-10 developed economies and 15 developing economies-was collected and analyzed using Phillips Perron Fisher panel unit root test, panel auto regressive distributed lag (PARDL) model, and panel fully modified least squares/fully modified OLS. From the result, it found that FDI and TO are positively contributing to sustainability development index (SDI) in developing countries rather than the developed countries in the long run. In addition to this, changes in the SDI score is significantly influenced by the present and past import and export activities in developed as well as developing economies in the short run. 2023, IGI Global. All rights reserved. -
Exploring the Influence Dynamism of Economic Factors on Fluctuation of Exchange Rate-An Empirical Investigation for India Using ARDL Model
The Indian Foreign Exchange Market has experienced significant changes over the past decade, due to high degree of instability of the Indian Rupee leading to its devaluation against major global currencies. Exchange rate is considered as one of crucial indicators to determine the economic growth. Volatility of exchange rate of each day is influenced by various factors such as demand and supply, Gross Domestic Product, Interest rate, employment rate, public debt, balance of payments, inflation etc. Though there are multiple causes to determine the movement of exchange rate, but still the accurate level of causation is unpredictable. Keeping this in mind, this paper tries to attempt the relationship that exists between the exchange rate and select macroeconomic factors. To analyse the extent of influence of the selected variables on the exchange rate, the research paper uses 10 years of data spanning from Jan 2013 to Nov 2022. Further, the study uses monthly data of above-mentioned variables to bring out the analysis to meet the objectives. Descriptive statistics is used to find the characteristics of the data, correlation analysis and Ordinary Least Square method is used to find the relationship and impact level select macroeconomic factors on exchange rate. Autoregressive Distributed Lag (ARDL) model is used to find if any short run and long run association exists between the variables and the exchange rate. 2023, ASERS Publishing House. All rights reserved. -
Measurement Model of CO-PO Attainment in Higher Education: A Simplified Approach
The educational system in most countries are moving toward Outcome-Based Education (OBE) which is a student-centric teaching and learning methodology. The basic idea behind the adoption of OBE model is that the graduates should possess a sound knowledge in their respective disciplines and also have global mobility and acceptance. The Outcome-Based Education (OBE) should be based on the vision and mission of the institution. The institutions should clearly spell out the learning objectives of the program and course. The Course Outcome (CO), Program Outcome (PO), Program Specific Outcome (PSO) and Program Educational Objectives (PEO) determine clearly what the students are expected to accomplish, post their course or program respectively. This study aims to provide the simplified approach on assessment, evaluation and calculating the attainment levels of students through COs and POs in a management program. To assess the CO attainment for management courses, the authors have identified the subject Entrepreneurship Development offered in the first semester from the 2018-2020 batch of 60 students from the MBA program of an autonomous institute. The Course Outcome (CO) and Program Outcome (PO) are mapped with the Continuous Internal Assessments (CIA) and Semester Exam End (SEE) and thus the attainment levels of each CO are measured. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Attention to Economic Factors and Its Response to Foreign Portfolio Investment: An Evidence from Indian Capital Market
Stock market consists of a variety of investors. Among these, Foreign Portfolio Investors (FPIs) is a key investment influx. These investments can change or fluctuate due to several macroeconomic factors which can cause a shift in the dynamics of the markets in India. This paper examines the factors influencing for foreign portfolio investment in long run as well as short run. The sample comprises of 120 monthly observations on Foreign Portfolio Investment (FPIs) and Macro economic variables such as Oil prices (OP), Gross Domestic Product (GDP), Interest Rate (IR), Exchange rate of Indian Rupee with USD (ER), Inflation (CPI), Nifty Index (NSEI), 10year Bond Prices (BP) and Index of Industrial production (IIP) over a period of 10years, spanning from January 2013 to November 2022. The study employed Autoregressive Distributed Lag model (ARDL) to establish the long run association with error correction models. The result indicates that there is long run association between the Foreign Portfolio Investment and macro-economic variables. Among this, NSEI, IIP and ER played a significant role to determine FPI investments in the long run, whereas in the short run, FPI was impacted by ER and NSEI significantly. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Autoregressive Distributed Lag Approach for Estimating the Nexus between Net Asset Value of Mutual Fund and Economic Determinants in India
India has seen a phenomenal growth in cumulative mutual fund investment from Rs 7.93 trillion in 2012 to Rs 40.38 trillion in 2022, which is more than a five-fold increase since last 10 years. Retail investors are now realizing the power of savings and Systematic Investment Plans (SIP) to build long term wealth. A financial literacy wave which is sweeping across India has projected mutual funds as a significant contributor and beneficiary of this phenomenon. The evolving economic landscape of India provides investors with excellent opportunities to capitalize on these fluctuations through systematic investment in safe investment vehicles like mutual funds. The market associated with mutual funds is always subjected to economic risks. The erratic fluctuations in macroeconomic variables can largely explain the Volatility in Net Asset Value (NAV) of equity oriented mutual fund schemes. With this background, this paper examines the impact of select macroeconomic variables on mutual funds performance in India. To analyse this, monthly observations of select macroeconomic variables, average NAV of large cap, mid cap, and small cap funds collected for a period of 10 years starting from January 2013 to November 2022. Descriptive statistics is used to probe the characteristics of the variable. In addition, correlation and ordinary least square method is applied to check the existing relationship and impact level of macroeconomic factors on NAV of select schemes. Lastly, short and long run relationship is analysed using Autoregressive Distributed Lag Model (ARDL). 2023, ASERS Publishing House. All rights reserved. -
Does Green Financing affect the Sustainable Economic Growth of Emerging Economies? Evidence from Panel ARDL Model
This study examines the nexus between green finance determinants and sustainable economic growth in Brazil, India, China, and South Africa using a panel Autoregressive Distributed Lag (ARDL) approach. These rapidly developing countries face the dual challenge of maintaining economic growth while addressing environmental sustainability. The analysis focuses on five key independent variables: Comparative Advantage in Low Carbon Technology Products, Total Trade in Low Carbon Technology Products, Trade Balance in Low Carbon Technology Products, Annual CO2 Emissions, and Lack of Coping Capacity. Short-run results indicate that Total Trade in Low Carbon Technology Products negatively affects GDP, suggesting that while green trade is expanding, it currently lacks stable, revenue-generating mechanisms. Annual CO2 Emissions and Lack of Coping Capacity positively influence GDP in the short term, reflecting continued dependence on emission-intensive industries and limited infrastructure for resilience. Comparative Advantage and Trade Balance in Low Carbon Technology Products are statistically insignificant in the short run, implying delayed economic benefits. In the long run, none of the green finance indicators show a significant relationship with GDP, possibly due to the substantial upfront investments required for green projects, which delay economic returns. The study underscores the need for strategic investments in technology, infrastructure, and governance to align economic growth with long-term sustainability goals. 2025 Sathish Pachiyappan et al., published by Oikos Institut d.o.o. -
Golden Insights: Analyzing the Influence of Economic Indicators on Sovereign Gold Bond Performance in India
India has been the leading consumers of gold with the consumption of around 774 metric tons in 2022. The demand for gold in India is majorly associated with its culture, tradition, attractiveness, and the source for financial security (GJC,n.d.)The gold market in India plays a vital role in the economy as a stable asset and hedge against inflation due to its ability to hold value over time. In order to limit the import of gold and reduce the countrys current deficit, the Indian Government introduced Sovereign Gold Bonds in 2015 as a substitute to physical gold. As SGBs export-import values are backed by Reserve Bank of India (RBI) they are considered as an inflation hedging tool. The study aims to examine the effectiveness of SGBs, in the changing economy by understanding the impact of key economic indicators Inflation Rate, Exchange Rate, Per Capita Income, Gold Prices, and GDP Growth Rateon the performance of Sovereign Gold Bonds (SGBs) in India. 36 months observations of the selected macroeconomic variables and series wise released prices are collected for a period starting from September 2021 till August 2024 for the analysis. Descriptive statistics is applied to understand the characteristics of the variables. Further, correlation and ordinary least square method is used to check the existing relationship and impact level of macroeconomic variables on SGBs. Lastly, both long run and short run relationships of these variables are analyzed using the Autoregressive Distributed Lag Model (ARDL). 2025, Iquz Galaxy Publisher. All rights reserved. -
The Macro Lens: Exploring the Impact of Macroeconomic Variables on Indias Small Cap, Mid Cap, and Large Cap Indices
Subject and Purpose of Work: This study explores the intricate relationship between key macroeconomic variables and Indias equity market segments, specifically the NIFTY Small-cap, Mid-cap, and Large-cap indices. The primary objective is to evaluate how selected macroeconomic factors influence market dynamics and investor sentiment in the Indian context. Materials and Methods: The research analyses monthly data spanning five years, from January 2019 to January 2024. The macroeconomic indicators considered include Foreign Institutional Investment (FII), Domestic Institutional Investment (DII), Consumer Price Index (CPI), Purchasing Managers Index (PMI), Treasury Bill Rate, Gold Price, and Reverse Repo Rate. Statistical techniques such as the Unit Root Test, Ordinary Least Squares (OLS), and Granger Causality Test are employed to assess the short-term and long-term impacts of these variables on market indices. Results: The findings reveal that GDP, CPI, PMI, and Gold Price exhibit no statistically significant influence on the NIFTY Small-cap, Mid-cap, or Large-cap indices, aligning with certain earlier studies. However, variables like FII, DII, Treasury Bill Rate, and Reverse Repo Rate show varying degrees of influence across the indices, highlighting the complex and segmented nature of the Indian equity market. Conclusion: These insights are valuable for investors, policymakers, and financial analysts in refining investment strategies, informing policy frameworks, and enhancing market forecasting models. The study underscores the need for continuous evaluation of macroeconomic influences to better navigate market volatility and investor behaviour. 2025 Sathish Pachiyappan et al., published by John Paul II University of Applied Sciences. -
Driving profitable business growth through economical optimization, energy management, and industrial 5.0 innovations
The chapter emphasizes the significance of economic optimization, energy efficiency, and Industrial 5.0 innovations in driving sustainable growth and profitability in today's business landscape. It highlights the strategic allocation of resources to maximize efficiency and minimize costs, using lean management principles, automation, and data analytics. Energy management is crucial for reducing operational costs and mitigating environmental impact, using renewable energy sources and smart technologies. Industrial 5.0, a new era of industrial transformation, combines automation, connectivity, and data exchange, with technologies like artificial intelligence, IoT, and blockchain. 2024, IGI Global. -
Scripts influence on reading processes and cognition: a preamble
[No abstract available] -
Editorial: Methods and applications in cognitive science
[No abstract available] -
A Multifaceted Approach at Discerning Redditors Feelings Towards ChatGPT
Generative AI platforms like ChatGPT have leapfrogged in terms of technological advancements. Traditional methods of scrutiny are not enough for assessing their technological efficacy. Understanding public sentiment and feelings towards ChatGPT is crucial for pre-empting the technologys longevity and impact while also providing a silhouette of human psychology. Social media platforms have seen tremendous growth in recent years, resulting in a surge of user-generated content. Among these platforms, Reddit stands out as a forum for users to engage in discussions on various topics, including Generative Artificial Intelligence (GAI) and chatbots. Traditional pedagogy for social media sentiment analysis and opinion mining are time consuming and resource heavy, while lacking representation. This paper provides a novice multifrontal approach that utilises and integrates various techniques for better results. The data collection and preparation are done through the Reddit API in tandem with multi-stage weighted and stratified sampling. NLP (Natural Language processing) techniques encompassing LDA (Latent Dirichlet Allocation), Topic modelling, STM (Structured Topic Modelling), sentiment analysis and emotional analysis using RoBERTa are deployed for opinion mining. To verify, substantiate and scrutinise all variables in the dataset, multiple hypothesises are tested using ANOVA, T-tests, KruskalWallis test, Chi-Square Test and MannWhitney U test. The study provides a novel contribution to the growing literature on social media sentiment analysis and has significant new implications for discerning user experience and engagement with AI chatbots like ChatGPT. 2024 Padarha et al., licensed to EAI.