Hindu Research Articles

Translation and Adaptation of Cognistat in Hindi Language: For Computerized Evaluation of Cognitive Functioning.

Cognitive assessment is a crucial element of the mental health screening process. However, there is a lack of culturally appropriate cognitive screening tools for the Hindi-speaking aging population in India. We aimed to translate and culturally tailor the English version of the computerized Cognistat test for the Hindi-speaking aging population. The computer-based Cognistat Assessment System was culturally adapted for the North Indian Hindi-speaking population. Participants with mild cognitive impairment (MCI) (n =30), depression (n =30), and healthy control (n =30) groups between the age range of 50 and 83years were assessed using the translated version of the tool. The group differences were analyzed using analysis of variance, multivariate analysis of variance, Tukey's post hoc analysis for continuous variables, and Fisher's exact test for categorical variables. The correlation between the Cognistat domains was analyzed using Pearson's correlation, and test reliability was assessed using Cronbach's alpha. The MCI group had significantly lower scores as compared with the depression and control groups on orientation, language, repetition, and calculation domain tasks. For attention and construction tasks, the MCI group had lower scores than the control group. MCI group scores were significantly lower than the control group on naming domain. The Hindi version of the test was reliable for the Hindi-speaking aging population. Cognistat Hindi can be used by trained healthcare professionals with Hindi-speaking populations for culturally tailored primary evaluation of cognitive difficulties. Future research should focus on further validation and assessment of its properties.

Sistem Aguron-guron di Griya Agung Bangkasa Kecamatan Abiansemal Kabupaten Badung

The aguron-guron system is an educational system developed by the Hindu religion to teach knowledge and skills in the religious field. The system is still highly relevant for imparting spiritual knowledge in the process of producing a pandita/sulinggih (spiritual teacher). The pandita, as a spiritual leader, holds a significant position and authority in the religious life of the Hindu community. Research related to the aguron-guron system was conducted at Griya Agung Bangkasa because this griya (household) is one of the ancient griyas with a long lineage of sulinggih and is committed to developing the aguron-guron system. There are three issues addressed in this research, namely related to the form, function, and implications of the aguron-guron system in Griya Agung Bangkasa. This qualitative research with a theological approach uses structural functionalism and symbolic interactionism theories to analyze the issues so that data can be presented descriptively qualitatively. The form of the aguron-guron system in Griya Agung Bangkasa is an education system known as "Garis Kapurusan Parampara." This education system is implemented intensively and exclusively by teachers/nabe towards their students/sisya. The aguron-guron education is carried out with the aim of achieving parartha and paramartha. The components involved include nabe, nanak, curriculum, walaka griya, and overseeing foundations. The aguron-guron system in Griya Agung Bangkasa serves educational, religious, and social functions. Lastly, regarding the implications of the aguron-guron system in Griya Agung Bangkasa, it gives rise to educational, theological, and sociological implications both internally and externally. This exclusive aguron-guron system is unique due to the presence of pawintenan wiwa and the existence of nabe siksa in the process, both of which are efforts to improve the quality of the implemented aguron-guron education. The exclusive nature of the aguron-guron system is the best choice for providing spiritual education, enriching the educational system, and creating a holistic education.

Deep Learning-Based Aspect Term Extraction for Sentiment Analysis in Hindi

Objectives: Aspect terms play a vital role in finalizing the sentiment of a given review. This experimental study aims to improve the aspect term extraction mechanism for Hindi language reviews. Methods: We trained and evaluated a deep learning-based supervised model for aspect term extraction. All experiments are performed on a well-accepted Hindi dataset. A BiLSTM-based attention technique is employed to improve the extraction results. Findings: Our results show better F-score results than many existing supervised methods for aspect term extraction. Accuracy results are outstanding compared to other reported results. Results showed an outstanding 91.27% accuracy and an F–score of 43.16. Novelty: This proposed architecture and the achieved results are a foundational resource for future studies and endeavours in the field. Keywords: Sentiment analysis, Aspect based sentiment analysis, Aspect term extraction, Deep Learning, Bi LSTM, Indian language, Hindi

Semantic Model for Fragment of Hindi (Part 1)

This paper proposes a formal model for syntactic and semantic analysis for the Hindi language using context-free grammar. In this paper, we developed a syntactic parser that generates syntactic trees for Hindi sentences based on rules of propositional logic, and gender conventions. The context-free rules we have written follow a top-down approach with a sentence that goes on self-arrangement. A set of experiments were run based on the corpus we have created, and significant results are presented in this paper. In addition to the above, the model characterizes lexical items in terms of individuals and sets for the syntactic distribution for well-formed formulas.

Benang yang Hilang: Mengurai Alienasi Kultural Hindu dan Aniaya Budaya di Tengah Urbanisasi Generasi Z

Cultural alienation has resulted in changes in the religious culture and feelings of generation Z with several cultural cases causing a sharp decline in cultural values, customs and religious practices. This is especially sad in the context of Hinduism, where traditional traditions are at risk of extinction, as a result of cultural persecution and cultural alienation. The aim of this research is to reveal the extent of the cultural transformation experienced by Generation Z during the urbanization process, as well as identify specific factors that contribute to cultural alienation and persecution within the Hindu community by proposing effective solutions and interventions to mitigate the decline in cultural values, customs, and Hindu religion. Researchers use qualitative research with the research approach that will be used is ethnography. Data collection techniques using in-depth interviews, surveys and participant observation. In a novel way, this research introduces a new perspective by focusing on the intersection between urbanization, Generation Z, and Hindu culture, revealing the intricacies of cultural alienation and cultural persecution. The results of this research show that traditional customs are giving way to a more contemporary lifestyle, which shows that there is a complex negotiation between cultural heritage and modernity, so that factors emerge that contribute to cultural alienation, including (1). Peer influence, (2). The impact of media hegemony (flexing content) and the rapid pace of urban life emerge as the main factors contributing to cultural alienation among Generation Z. Several solutions to increase the fighting power of Generation Z return to the axis of Hindu culture and religion, without abandoning the positive innovations of the impact of urbanization, including: (1) Strengthening Cultural Education, (2) Community Engagement Initiatives, (3) Adapting Traditions in a Modern Context, (4) Digital Platforms for Cultural Awareness, (5) Intergenerational Cross Experience. It is concluded that the cultural structure of Generation Z in a dynamic urbanization landscape requires special handling and that preserving values and traditions is a shared responsibility for all aspects of social life.

Psychometric Properties of the Oral Health Values Scale and Cultural Adaptation in the Indian Population.

The Oral Health Values Scale is a multidimensional instrument that identifies and measures a person's values related to oral health. This scale has been validated in American respondents. This study aims to evaluate the adaptability and validity of the Oral Health Values Scale in the Hindi language (H-OHVS). A total of 240 adults participated in the study that was carried out from July to November 2022. An offline one-to-one survey was carried out to collect data by an investigator blinded to the study protocol. The translation and testing of the OHVS were carried out based on the cross-cultural adaptation guidelines of the American Academy of Orthopedic Surgeons (AAOS) Evidence-Based Medicine Committee. The content validity was assessed by an expert panel. Construct validity was analyzed through Exploratory Factor Analysis (EFA), utilizing principal component analysis with varimax rotation. The internal consistency of the Hindi version of OHVS was evaluated using Cronbach's alpha. The results showed that H-OHVS had an Item-level Construct Validity Index (I-CVI) ranging from 0.82 to 1.00. Two components, compliance and hesitance, were formed on H-OHVS accounting for 63.91% of the cumulative variance. The resulting model fit indices on confirmatory factor analysis presented an adequate fit to the data.The overall Cronbach's alpha coefficient for H-OHVS (α = 0.868) presents excellent internal consistency. The study findings provide a certain degree of evidence in favor of this scale and establish the Oral Health Values Scale (OHVS) as a psychometrically sound measure.

Religious Leaders' Perspectives Towards LGBTIQ in Nepal

Lesbian, Gay, Bisexual, Trans gender, Intersex, Queer plus is an emerging social issue in Nepal. Still Nepalese society has hardly accepted the issue yet. There might be various reasons; this concept has not earned priority in current social structure. Social structures are guided by the religious belief and practice. Religious leaders’ hold the governing positions to construct the perception of society. For the reason, it aims to explore the perception of religious leaders towards LGBTIQ. The religious leaders from Hindus (Sanatana Dharma), Buddhist, Islam and Christian around Kathmandu valley were selected as the respondents of the research. Qualitative data were collected through in-depth interview. In their own worshipping places through field visit. Respondents felt uneasy on the topic though they preferred to explain the good features of the religion rather than the issue. Hindus claimed that they respect third gender as the grace of the god, though they believe that it is against the rule and nature constructed by the god. Similarly, the devotees of Buddhism take oath to follow the ‘Eight-Fold-Path’ as their guideline which consist the five precepts. The Christians consider sexuality to be a divine gift, though it ignores the sexual orientation of LGBTIQ and there are significant disagreements among the Christian community in Nepal. Islamic faith is controlled by holy Quran, which does not give permission for unnatural sex. Though, in the holy text, the story of Luth is mentioned to aware the devotees from the sinful act performed by LGBTIQ. Though, the religious leader accepted the biological features of the LGBTIQ but they denied the sexual activities they perform or express. They perceive it as a sinful act of previous life. Moreover, they believe that the lesbian, gay issues were mostly influenced by western culture and the advancement of the modern technologies. Thus, the religion guided structure of Nepal left behind to address the LGBTIQ to struggle for decades to achieve the rights in the country.

Prevalence and predictors of insomnia and its treatment-seeking among older adults in India

BackgroundInsomnia is a serious health problem among older adults and, if untreated, is linked to a high morbidity rate and decreased quality of life. There is limited empirical evidence on Insomnia and its treatment-seeking exclusively among older adults (60 plus years) using representative data in India. This study assesses the prevalence and predictors of Insomnia and its treatment-seeking among older adults.MethodsData gathered through the nationally-representative Longitudinal Ageing Study in India (LASI); Wave 1 (2017-18) was used for the analysis. Specifically, information from older adults aged 60 and above for whom complete information on insomnia was available (n- 31,464) was considered for the analysis. Binary logistic regression was used to check the adjusted effects of insomnia’s socio-demographic and economic predictors and its treatment-seeking status. Stata was used for the data analysis with a 5% significance level.Results37% of older adults had insomnia. Increasing age, female gender, living without a spouse, illiteracy, chronic health conditions, nutritionally underweight, physically inactive status, lack of exposure to mass media, Hindu religion, non-tribal status, and rural residence were significantly associated with insomnia. 3% of older adults sought treatment for insomnia. Not seeking treatment for insomnia was associated with male gender, exposure to mass media, physical activity, lack of chronic health issues, tribal status, living in a rural area, and being economically disadvantaged.ConclusionsA sizable number of older adults have insomnia, and the prevalence varies by their socioeconomic, demographic, and health status. Many modifiable risk factors like low education, chronic health conditions, smoking, being underweight, physical inactivity, and lack of exposure to mass media are identified. Treatment-seeking for Insomnia is further inadequate, enhancing the older adult’s vulnerability to various morbidities. Policy and program intervention to raise awareness about insomnia, including early identification and pharmacological and non-pharmacological treatment, will ensure better health and welfare of older adults. Estimations are based on self-report questionnaires; therefore, the possibility of recall bias and under-reporting cannot be ignored. Moreover, the estimation of insomnia may vary depending on various clinical definitions. However, a large sample size from a recent nationally representative survey with a robust sampling design is the strength of this study.

Deep Neural Networks for Location Reference Identification From Bilingual Disaster-Related Tweets

Twitter is increasingly being used during disasters to communicate with authorities, ascertain the ground reality, and coordinate real-time rescue and recovery activities. Geographical location information about users and events is critical in these scenarios. Geotagged tweets are extremely infrequent, and other location fields, such as user location and place name, are unreliable. The extraction of geographical information from tweet text is limited by the fact that individuals frequently publish multilingual tweets that contain numerous grammatical and spelling errors, as well as nonstandard acronyms. As a result, determining the geographical location of the tweet is a challenging problem. This article presents a technique based on deep neural networks for extracting geographical references mentioned in bilingual tweets. Several deep learning-based models, including convolutional neural networks (CNNs), long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and attention-based Bi-LSTM, are implemented on real-world English and Hindi language tweets to determine their suitability for extracting location references. The proposed CNN, along with a conditional random field at the last layer, is found to perform better than other models, with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_1$</tex-math> </inline-formula> -score of 0.858. The findings of this study can aid in early event detection, pinpointing the area of devastation and victims, real-time traffic management, and a number of other location-based applications. The suggested system’s code and trained model may be obtained at https://github.com/Abhinavkmr/Bi-lingual-location-reference-identification.git.

Ramottaratapinyupanishat and its Invaluable Contribution of ‘Rama Taraka Mantra’ to Human Society

Purpose: This article reveals about “Ramottaratapinyupanishat”, which is a part of Atharva Veda. This Upanishad has contributed the invaluable “Rama-Taraka-Mantra” for the wellbeing of human society. In Sanatana Dharma, the ultimate abode of every human being is Moksha and this Mantra is the Key to open the door of Moksha. Methodology/Approach: Here, Rishis like Bruhaspathi, Bharadwaja and Atri who are the disciples always engaged in austerity for the prosperity of the whole Manu Kula, approach Yajnavalkya and pray him to explain about the ways and means to get relief from this non-stop wheel of Samsara chakra and to attain Mukti or Moksha. This paper is the outcome of practical approach after theoretical explanation. Findings: To their queries, Yajnavalkya unfolds the whole Upanishad by decoding the great ‘Rama Shadakshara Mantra’, its unique strengths, secret values of each and every syllable, methodologies to be followed during the Sadhana and its glorious outcomes. Originality/Value: The contents of this paper are the final prosedings of Upanishat Havana’s Vakyartha gosti conducted after the Havana on 1-11-2019. The value of the contents is highly merited and is evergreen. Paper Type: Practical research.

Impact of Socio- Economic Status on the Educational Achievement of Secondary School Students in Vadodara

With the onset of COVID-19 pandemic, most of the students and their families were affected by economic burden and became unemployed. Those who had business also suffered, unemployment in India effected the future of the students and their parents. Paying fees in schools became a problem for parents. Many students lost their father or mother. Research has shown that the effect of socio-economic status on the academic achievement of students was observed due to corona. Many parents are not educated. If the size of the family is large, then out of 4 children, one or two children are not able to get admission in the school. The present study will help us to know the importance of the situation of our country along with the academic achievement of students. The objective of this present study is to know the socio-economic status of secondary school students of Vadodara district and the problems faced by them in their academic achievement. There are many factors affecting academic achievement. psychological, social, economic and environmental etc. The objectives of the study were to identify the level educational achievement of secondary school students of Vadodara City and to examine the influence of socio-economic status on the educational achievement of secondary school students The descriptive survey method was used for the present study. 50-students and parents of the two Hindi medium schools namely Shri Krishna Hindi Vidyalaya and Adarsh Hindi Vidyalaya were selected as the sample for the present study. It has been found in the present study that the academic achievement of low-level students, average level students, high level students were investigated the level of all the students, mean scores of high-level students were 212 and the marks of average level students were 142 and the lowest low level of students is 57. To see the impact of socio-economic status on educational achievement, t-test was conducted, it was found that statistically there exists no significant difference in socioeconomic status and educational academic achievement It becomes important to be conclude that even the status of social or economic level is low but efforts can be made to attain expected educational achievement and lead to a totally developed personality for which education is aimed for.

Acculturation of Hindu and Buddhist Culture at Goa Giri Putri Temple Nusa Penida

The purpose of this study is to determine the process of Hindu-Buddhist cultural acculturation in Goa Giri Putri Temple, identifying the form and meaning contained in the cultural acculturation. This study uses the theory of cultural acculturation to analyse the process and forms of the cultural acculturation that occur in the temple and multiculturalism theory to analyse the meaning/values involved in the cultural acculturation. The method used in this research is qualitative. Data were collected through an in-depth interview and observation. The data were analysed using a descriptive-analytical technique. The findings show that the process of cultural acculturation in Goa Giri Putri temple is the openness of the community to the entry of outside culture (Chinese culture) into Hindu culture and the existence of community beliefs or faith. Acculturation can be seen in the form of Buddhist worship statues placed alongside the worship (pelinggih) of Hindu gods at the Goa Giri Putri Temple. The means of worship used also do not distinguish between Hindu and Buddhist beliefs. Hindu-Buddhist cultural acculturation in Goa Giri Putri Temple has the meaning of providing an understanding of multicultural values and socio-religious values for the people of Karangsari Hamlet, Suana Village, Nusa Penida.

English Language Supremacy in India: Where Literacy Rate is Check by If Person can Read or Right in Any Language

IN INDIA where different type of languages exist how any specific language can be supreme? Here literacy rate is check by if the person can read and write in any language no language is barrier to check literacy rate the why any specific language is barrier or even people judge the status and treat other person by the mode of communication {English}. Only 10% people in India who knows English. Around 20-30% of people don't know Hindi in India. The constitution of India states under Article 348(1)(a) that all proceedings in the Supreme Court and in every High Court, shall be in English language or Hindi language. Use of any language according to the place and tounge of the people living there or the language which is easy to understand by the people living there is still better that to use any specific language like English or Hindi. The people for whom the courts came in the existence or who file cases in courts for justice if they are not able to understand that what the judge and advocate is arguing or talking about then how they can understand immediately what is going on in their own case. Along with this so many advocates who have efficient knowledge but just because of the language barrier they can't be part of higher courts.

Translation and pilot validation of Hindi, Marathi, and Bangla translation of quality of life EORTC module (QLQ-SH-22) for assessing sexual health-related quality of life.

To translate and validate the European Organization for Research and Treatment for Cancer (EORTC) module for assessing the sexual health-related quality of life in cancer patients (QLQ-SH22), in Hindi, Marathi, and Bangla languages for clinical use. The EORTC QLQ-SH-22 was translated into Hindi, Marathi, and Bangla by adopting standard guidelines given by EORTC. Initially, the original questionnaire was forward translated by two separate translators, followed by the reconciliation of the forward translations by a third person. This was followed by two back translations of the reconciled version into English by two other translators. These back-translated questions were then compared with the original EORTC questions for accuracy, and once acceptable, a preliminary questionnaire was prepared in all three languages. These questionnaires were then pilot tested with 30 patients (10 for each language) diagnosed with any of the cancers in the pelvic region who are expected to be at risk of sexual quality of life due to tumor or treatment like pelvic radiotherapy. Participated patients had never seen or filled the questionnaire before, each patient was interviewed after filling the questionnaire for difficulty in answering, confusion, difficulty understanding, or if any of the questions were upsetting and if patients would have asked the question differently. None of the patients reported any changes or suggestions for all the three translations. All the translated questionnaires were well understood by all the patients. Pilot testing reports were sent to EORTC. After reviewing the entire report of Hindi, Marathi, and Bangla translations, these questionnaires were approved by the EORTC translation unit. The questionnaires are reliable with Cronbach's α for Hindi, Marathi, and Bangla being 0.69, 0.66, and 0.86, respectively. The final Hindi, Marathi, and Bangla translations of SH 22 have been approved by the EORTC and can be used to assess the sexual health of cancer patients in routine oncology practices and/or clinical studies.

Ensemble Classifier for Hindi Hostile Content Detection

Detection of hostile content from social media posts (Facebook, Twitter, etc.) is a demanding task in the field of Natural Language Processing. The increase of hostile content in different electronic media has opened up new challenges in language understanding. It becomes more difficult in regional languages. AI-based solutions are required to identify hostile content on a large scale. Although a satisfactory amount of research has been carried out in the English language, finding hostile content in regional languages is still under development due to the unavailability of suitable datasets and tools. In terms of the number of speakers, Hindi ranks third in the world and first on the Indian subcontinent. The objective of this article is to design a hostile content detection system in Hindi using coarse-grained (binary) classification and fine-grained (multi-class, multi-label) classification. We note that different baseline learning methods with different pre-trained language models perform differently. Using the Constraint 2021 Hindi Dataset, this research proposes a Bidirectional Encoder Representations from Transformers–(BERT) based contextual embedding technique with a concatenation of emoji2vec embeddings to classify social media posts in Hindi Devanagari script as hostile or non-hostile. Additionally, for the fine-grained tasks where hostile posts are sub-categorized as defamation, fake, hate, and offensive, we develop an ensemble classifier varying different learning methods and embedding models. With an F1-Score of 0.9721, it is found that our proposed Indic-BERT+emoji model outperforms the baseline model and other existing models for the coarse-grained task. We have also observed that our proposed ensemble method provides better results than the existing models and the baseline model for the fine-grained tasks with F1-Scores of 0.43, 0.82, 0.58, and 0.62 for the defamation, fake, hate, and offensive classes, respectively. The code and the data are available at https://github.com/skarifahmed/hostile .

End-to-end Multi-modal Low-resourced Speech Keywords Recognition Using Sequential Conv2D Nets

Advanced Neural Networks are widely used to recognize multi-modal conversational speech with significant improvements in accuracy automatically. Significantly, Convolutional Neural sheets have retreated cutting-edge performance in Automatic Voice Recognition (AVR) recently more appropriately in English; however, the Hindi language has not been explored and examined well on AVR systems. The work in this article has exposed a three-layered two-dimensional Sequential Convolutional neural architecture. The Sequential Conv2D is an end-to-end system that can instantaneously exploit speech signal spectral and temporal structures. The network has been trained and tested on different cepstral features such as Frequency and Time variant-Mel-Filters, Gamma-tone Filter Cepstral Quantities, Bark-Filter band Coefficients, and Spectrogram features of speech structures. The experiment was performed on two low-resourced speech command datasets; Hindi with 27,145 Speech Keywords developed by TIFR and 23,664 (1-s utterances) of English speech commands by Google TensorFlow and AIY English Speech Commands. The experimental outcome showed that the model achieves significant performance of Convolutional layers trained on spectrograms with 91.60% accuracy, compared to that achieved in other cepstral feature labels for English speech. However, the model achieved an accuracy of 69.65% for Hindi audio words in which bark-frequency cepstral coefficients features outperformed spectrogram features.

A textual question answering and handwritten answer evaluation system for hindi language

Textual Question Answering targets answering questions defined in natural language. Question Answering Systems offer an automated approach to procuring answers to queries expressed in natural language. The need for Multilingual Question Answering without performing machine translation is ever existing. Besides that, automating tasks with the help of technology to assist humans, has been the main aim of research in recent years. This paper presents an automated answer evaluation system for reading comprehension-based questions in the Hindi language without requiring translation in any other language. The system accepts text, question, and handwritten answer of a student in the form of an image for answer evaluation. This is accomplished by developing a textual question-answering system for reading comprehension. It is an extractive approach that utilizes RoBERTa transformer model and fine-tunes it for Hindi question-answering. The answer to the question is extracted as a span from the provided text. Further, a handwritten text recognizer model is developed employing a Convolutional Recurrent Neural Network with Connectionist Temporal Classification module along with two layers of Bidirectional LSTM. Experimentation is performed using existing as well as self-created datasets to show the effectiveness of the proposed approach. An accuracy of 98.69% is obtained on the self-created Hindi-QA dataset and the proposed system outperformed the other existing methods. The paper also discusses potential research directions in the field.

A Legal Analysis of Cyber-Enabled Wildlife Offences in India: A Qualitative Case Study of Sea Fans (Gorgonia spp.) on YouTube

With the advent of the Internet, offences against threatened species have transitioned online. Such species are directly or indirectly traded on social media despite being protected under Indian wildlife law. A qualitative case study was undertaken to assess the preparedness of national law and policy in prohibiting such offences. Sixty-three YouTube links on sea fans in the Hindi language were accessed over 8 weeks, and the information generated by both content creators and audiences was gathered and categorized for analysis. The legal provisions were then interpreted and applied to assess the extent to which the parties involved could be held liable. Our investigation shows that of these video links, the content creators directly offered specimens for sale in 15.87% of instances, demonstrated physical possession of wild specimens in 23.81% of these posts, and were involved in both activities in 20.63% of the links, which in our analysis is explicitly prohibited under national law. The remaining 39.68% of video links merely disseminated information on the relevance or usage of species in occult or religious practices, for which no express legal provision currently exists. Certain indirect legal provisions were found to be relevant; however, there were challenges associated with their implementation. Even the liability of a social media company was found to be limited if it can be demonstrated that the company exercised due diligence. Therefore, there is a need to explicitly regulate online content that has the potential to drive an unlawful demand for protected species alongside the imposition of enhanced liability on social media companies. Such measures, coupled with community awareness, can reduce cyber-enabled wildlife offences committed through social media channels.

Spider Monkey Optimization with Deep Learning-based Hindi Short Text Sentiment Analysis

Sentiment analysis (SA) intends to categorize a text respective to sentimental polarity of individual opinions, like neutral, positive, or negative. The study of Hindi is limited because of the grammatical and morphological complexities of the Hindi language while many research work concentrates on drawing features from English text. The hindi languages make the sentiment classification procedure for Hindi short text a tedious process. The Hindi language has complicated morphology and variation based on phonetics, spelling, and vocabulary; the common usage of numerous dialects between Hindi in India produces a massive volume of glossaries. In this study, we introduce a Spider Monkey Optimization with stacked recurrent neural network (SMO-SRNN) for short text SA on Hindi Corpus. The proposed SMO-SRNN technique mainly aims to identify and categorize the Hindi short text into three distinct classes, namely negative, positive, and neutral. In the presented SMO-SRNN method, the SRNN approach is exploited for the investigation and classification of sentiment. Moreover, the SMO model is employed to finetune the hyperparameter related to the SRNN model. A detailed set of experiments is applied to ensure the high efficiency of the SMO-SRNN algorithm. The comparative outcome highlighted the enhancement of the SMO-SRNN technique over other methods.

Comparative Assessment of Online Written Health Information on Treatment of Erectile Dysfunction in English and Hindi Language Webpages

Objectives: To assess and compare the overall quality of online written information on the treatment of erectile dysfunction (ED) in English and Hindi language webpages. Also, correlates of the quality of online health information were explored. Methods: First 50 links obtained on Google search in both English and Hindi language were screened, and a total of 86 (45 English, 41 Hindi) webpages providing patient-oriented information on the treatment of ED were analysed. Content quality and reliability were assessed using the DISCERN scale and the JAMA benchmark criteria respectively. Additionally, aesthetics, interactivity, and readability were evaluated. Results: The DISCERN score indicative of content quality was significantly higher for English webpages compared to Hindi webpages. English webpages were more likely to meet disclosure and attribution JAMA criteria for the reliability of medical information. English webpages with HONcode certification were more likely to have better content quality than those without it. However, none of the Hindi web pages analyzed were HONcode certified. Conclusion: English language webpages provided better overall quality of information on treatment of ED as compared to Hindi language. HONcode label might be used as a proxy indicator of better content quality for online resources informing on ED treatment by laypersons. There is a need to develop and popularize the usage of HONcode or other similar online health information quality accreditation systems for webpages in non-English languages like Hindi.