Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk o...Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic content.Tis study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie reviews.SGD allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language data.Tis adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better performance.Two distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for analysis.Te proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and efciency.Te SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both datasets.Tis indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English datasets.Tis study helps deepen the understanding of sentiments across various linguistic datasets.Unlike many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.展开更多
Objective:Heterogeneity in the evidence of association between lifestyle factors and breast cancer(BC)incidence hampers initiatives to modify BC risk.This overview aims to synthesise evidence from systematic reviews(S...Objective:Heterogeneity in the evidence of association between lifestyle factors and breast cancer(BC)incidence hampers initiatives to modify BC risk.This overview aims to synthesise evidence from systematic reviews(SRs)to inform lifestyle-related modifications for BC prevention.Methods:We systematically searched(MEDLINE,EMBASE,and CINAHL)from January 2013 to August 2023 for SRs of the association between lifestyle factors[alcohol consumption,physical activity(PA),body mass index(BMI),smoking,breastfeeding,oral contraception(OC),hormone replacement therapy(HRT),and sedentary behavior(SB)]and BC incidence.A narrative data synthesis was performed.Results:Sixty-six SRs met the eligibility criteria.Evidence from 40 SRs indicated consistent associations between the risk of BC and postmenopausal BMI increase(relative risk increase:2%-21%),use of HRT(risk increase:23%-33%),smoking(risk increase:4%-86%),and alcohol consumption(risk increase:4%-61%).Additionally,evidence from 23 SRs suggested protective associations with PA(risk decrease:10%-39%),breastfeeding(risk decrease:9%-53%),and healthy lifestyle scores(protective about 20%-26%).However,inconsistent and/or statistically non-significant associations were found between BC incidence and premenopausal BMI increase[relative risk(RR):0.78-1.08],SB(RR:1.01-1.20),and OC use[odds ratio(OR):1.01-1.35].Conclusions:This overview identifies lifestyle factors associated with BC incidence,highlighting both harmful and protective factors.Our summary findings can support information and interventions related to modifying these factors,including limiting alcohol and smoking,or avoiding postmenopausal BMI increase and HRT.展开更多
Against the backdrop of the strategies for rural revitalization and the integration of agriculture,culture,and tourism,farm stay,as a vital carrier,requires a systematic analysis of its resource integration effectiven...Against the backdrop of the strategies for rural revitalization and the integration of agriculture,culture,and tourism,farm stay,as a vital carrier,requires a systematic analysis of its resource integration effectiveness and the actual needs of tourists.Taking Chongqing City as an example,this study leverages tourist reviews from the Dianping platform(China’s leading consumer review site)and employs a combination of TF-IDF keyword extraction,SnowNLP sentiment analysis,and LDA topic modeling to dissect tourists’perception characteristics and latent demands for agritourism resources from the demand side.The findings reveal that agricultural and tourism elements garner significant attention,while cultural resources are notably underperceived,indicating an imbalanced integration structure.Sentiment is predominantly positive,yet negative feedback highlights issues in service management,transportation,and homogenized experiences.Latent demands converge on three dimensions:deepening agricultural experiences,enhancing cultural participation and interaction,and improving environmental and service quality.Based on these findings,this study proposes integration enhancement strategies,including agricultural branding,cultural vitalization,service intelligence,and multi-faceted collaboration,to drive experience upgrades and sustainable development in farm stays,offering theoretical references and practical pathways for rural tourism integration in similar regions.展开更多
Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clini...Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clinic and future research.Methods:Databases including Embase,Cochrane Library,CINAHL,CNKI,SinoMed,Wanfang,and Weipu were searched to collect systematic reviews(SRs)and meta-analyses on mHealth interventions for hypertension management.Two researchers independently screened the articles and extracted data,and the Assessment of Multiple Systematic Reviews(AMSTAR 2)was used to evaluate the methodological quality of the included reviews.Results:A total of 11 SRs were included:1 review was rated as high quality,3 as low quality,and 7 as critically low quality.The mobile phone was the most common intervention type,followed by the internet.Seven reviews performed meta-analyses and showed that mHealth was associated with a significant reduction in systolic blood pressure(SBP),from 2.28 mmHg(95%CI-3.90 to-0.66;I^(2)=40%)to 14.77 mmHg(95%CI 11.76-17.77;I^(2)=89.7%),and diastolic blood pressure(DBP),from 1.50 mmHg(95%CI-2.20 to-0.08;I^(2)=62%)to 8.17 mmHg(95%CI 5.67-10.67;I^(2)=86%).Self-management behaviors included medication adherence(MA),diet,smoking,alcohol drinking,physical activity,and BP monitoring.There were inconsistent results on the effectiveness of mHealth interventions.Conclusions:mHealth interventions can improve BP control,MA,diet,and smoking in patients with hypertension,but the evidence for the efficacy of mHealth on physical activity and alcohol drinking improvement is limited.The methodological quality of existing SRs on the management of BP in patients with hypertension was relatively low,and more well-designed SRs or meta-analyses were needed to provide more evidence.mHealth interventions are useful for improving BP control of patients with hypertension.展开更多
BACKGROUND Systematic reviews(SRs)synthesize and evaluate data,mainly from randomized trials,which then guides the development of clinical recommendations in evidence-based medicine.However,the data and methodological...BACKGROUND Systematic reviews(SRs)synthesize and evaluate data,mainly from randomized trials,which then guides the development of clinical recommendations in evidence-based medicine.However,the data and methodological information in the included papers can often be lacking or unclear,and reviewers usually need to contact the authors of included studies for clarifications.Contacting authors is recommended,but it is unclear how often SR teams do it,or what the level of response is.AIM To investigate how often reviewers undertake contact with the authors of included randomized controlled trials(RCTs)for clarification on data and risk of bias concerns,to explore the factors that influence whether SR authors contact or do not contact the authors,and the content and level of responses.METHODS We conducted a systematic electronic database search in MEDLINE using the search string“(systematic review)”AND“(RCT OR randomized OR trial)”for articles published between 1 January 2024 and 19 February 2024,without language restrictions.Screening and data extraction was done independently by two reviewers,and conflicts resolved by a senior author.Contact authors of included SRs were contacted for clarifications.RESULTS Of the 329 included SRs,38%(n=125)explicitly mentioned contact with the authors of included studies.The remaining 62%(n=204)did not.We attempted contact with all SR teams for clarifications and received 90 responses(19.4%).Of the 50 respondents who did not explicitly mention contact in their SRs,25(50%)replied that they did make contact.We received a total of 64 responses on the level and content of information sought.The mean±SD contacts SR teams made were 10(10),replies received 5(6.7),and response waiting time 10.1(28.3)weeks.Resources,time,poor previous experience,perceived likelihood of poor response and bias concerns were reported as barriers to attempting contact.CONCLUSION The majority of SRs published in 2024 did not confirm seeking clarifying or missing information from primary study authors.However,SR teams reported that 50%of contacted primary authors respond.Additional research can clarify this rate of response and establish methods to increase the integration of this core methodological element in SRs.展开更多
Objective:This cross-sectional study assessed the methodological quality of systematic reviews(SRs)of Chinese herbal medicine(CHM)published in Chinese between Jan 2021 and Sep 2022.Methods:Chinese language CHM SRs wer...Objective:This cross-sectional study assessed the methodological quality of systematic reviews(SRs)of Chinese herbal medicine(CHM)published in Chinese between Jan 2021 and Sep 2022.Methods:Chinese language CHM SRs were identified through literature searches across 3 international and 4 Chinese databases.Methodological quality was appraised using A MeaSurement Tool to Assess systematic Reviews 2.Logistic regressions were used to explore associations between bibliographical characteristics and quality.Results:Analyses of methodological quality found that among the 213 sampled SRs,69.5%were of critically low quality,30.5%were of low quality,and none achieved high or moderate quality.Common shortcomings included the failure to identify the studies excluded from the analysis,failure to disclose funding sources,and limited evaluation of the potential impact of bias on conclusions.Logistic regressions revealed that SRs led by corresponding authors affiliated with universities or academic institutions tended to be of lower quality than SRs led by authors affiliated with hospitals or clinical facilities.Conclusion:Recent Chinese language CHM SRs exhibited limited methodological quality,making them unlikely to support the development of clinical practice guidelines.Urgent initiatives are needed to enhance training for researchers,peer-reviewers and editors involved in the preparation and publication of SRs.Adoption of Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines in Chinese language journals is crucial to improve the relevance of SRs for Chinese medicine development.Addressing deficiencies in methodology and reporting is essential for promoting evidence-based practices and informed clinical decisions in Chinese medicine.展开更多
Movies reviews provide valuable insights that can help people decide which movies are worth watching and avoid wasting their time on movies they will not enjoy.Movie reviews may contain spoilers or reveal significant ...Movies reviews provide valuable insights that can help people decide which movies are worth watching and avoid wasting their time on movies they will not enjoy.Movie reviews may contain spoilers or reveal significant plot details,which can reduce the enjoyment of the movie for those who have not watched it yet.Additionally,the abundance of reviews may make it difficult for people to read them all at once,classifying all of the movie reviews will help in making this decision without wasting time reading them all.Opinion mining,also called sentiment analysis,is the process of identifying and extracting subjective information from textual data.This study introduces a sentiment analysis approach using advanced deep learning models:Extra-Long Neural Network(XLNet),Long Short-Term Memory(LSTM),and Convolutional Neural Network-Long Short-Term Memory(CNN-LSTM).XLNet understands the context of a word from both sides,which is helpful for capturing complex language patterns.LSTM performs better in modeling long-term dependencies,while CNN-LSTM combines local and global context for robust feature extraction.Deep learning models take advantage of their ability to extract complex linguistic patterns and contextual information from raw text data.We carefully cleaned the IMDb movie reviews dataset with the goal of optimizing the results of models used in the experiment.This involves eliminating unnecessary punctuation,links,hashtags,stop words,and duplicate reviews.Lemmatization is also used for keeping consistent word forms.This cleaned IMDb dataset is evaluated on the proposed model for sentiment analysis in which XLNet performs well achieving an impressive 93.74%accuracy on the IMDb Dataset.The findings highlight the effectiveness of deep learning models in improving sentiment analysis,showing its potential for wider applications in natural language processing.展开更多
Objective:To summarize the characteristics and evaluate the quality of the methodology and evidence within systematic reviews(SRs)of Chinese herbal medicine(CHM)for Mycoplasma pneumoniae pneumonia(MPP)inchildren.Metho...Objective:To summarize the characteristics and evaluate the quality of the methodology and evidence within systematic reviews(SRs)of Chinese herbal medicine(CHM)for Mycoplasma pneumoniae pneumonia(MPP)inchildren.Methods:SRs of randomized controlled trials were searched using PubMed,the Cochrane Library,Embase,the Chinese National Knowledge Infrastructure Databases(CNKI),the Chinese Scientific Journals Database(VIP),Wanfang,and the SinoMed Database.SRs on the use of CHM alone or in combination with Western medications for MPP in children were included.The study compared the effects of Western medicine alone with those of CHM.The evidence quality using the A Measurement Tool to Assess Systematic Reviews(AMSTAR)2,the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)2020,and the Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)criteria.The primary indicators were the total effective rate,fever subsidence time,and cough disappearance time.The secondary outcomes were pulmonary rale disappearance time,average hospitalization time,lung X-ray infiltrate disappearance time,immunological indices,and inflammatory cytokine levels.Results:Twelve relevant SRs were included;75%(9/12)were assessed as very low quality,and 25%(3/12)Were rated as low quality using the AMSTAR 2 criteria.According to the PRISMA 2020 checklist,the average SR score was 20.3 out of a 27 point maximum.In all SRs,CHM demonstrated improvement in symptoms and signs among children with MPP.The evidence quality using the GRADE criteria ranged from"very low"(>50%)to"moderate"(<5%).The most common downgrading factor was imprecision,followed by publication bias and inconsistency.Conclusion:This overview highlights the limited quality of the methodology and evidence of the included SRs.Although the included studies showed the beneficial effects of CHM on MPP in children,it was difficult to draw firm conclusions owing to methodological flaws.展开更多
OBJECTIVE:To evaluate and summarise the evidence from published Meta-analyses/systematic reviews(MAs/SRs)of Traditional Chinese Medicine(TCM)in the treatment of recurrent respiratory tract infections(RRTIs)and to prov...OBJECTIVE:To evaluate and summarise the evidence from published Meta-analyses/systematic reviews(MAs/SRs)of Traditional Chinese Medicine(TCM)in the treatment of recurrent respiratory tract infections(RRTIs)and to provide a scientific basis for the clinical treatment of RRTIs with TCM.METHODS:Studies were retrieved from Chinese and English databases including the China National Knowledge Infrastructure,Wanfang database,China Science and Technology Journal Database,SinoM ed,PubM ed,Web of Science,the Cochrane Library and EMbase from their establishment date to March 2023.Involved studies were screened,extracted,and evaluated for quality by two researchers independently.The a measurement tool to assess systematic reviews(AMSTAR)2 scale was used for methodological quality evaluation,as well as the preferred reporting items for systematic reviews and Meta-analyses(PRISMA)2020 statement for report quality evaluation,the risk of bias in systematic reviews(ROBIS)tool for risk of bias,and the grading of recommendations,assessment,development and evaluation(GRADE)quality assessment tool for evidence quality.RESULTS:Twenty MAs/SRs studies were included,including analyses of 274 original studies involving 38335 patients with RRTIs.The AMSTAR 2 scale evaluation results showed that 19 studies were of very low quality and one of moderate quality.The ROBIS evaluation results showed that 11 MAs/SRs were at high risk and nine at low risk of bias.The PRISMA 2020 report quality showed the included studies had scores between 23.5 and 35.5,among them one with high quality,17 with moderate quality and two with low quality.The GRADE system results showed that among 126 outcome indicators,only 17 had moderate quality of evidence,27 had low quality,82 had very low quality,and none had high quality.CONCLUSIONS:The MAs/SRs methodological quality of using TCM for treatment RRTIs is generally poor,the quality of reports as well as of evidence is generally low,and the risk of bias is high;therefore we should treat these results with caution.展开更多
This umbrella review aimed to summarize and provide a general evaluation of the effectiveness of current treatments for male infertility and assess the quality of evidence and possible biases.An umbrella review of sys...This umbrella review aimed to summarize and provide a general evaluation of the effectiveness of current treatments for male infertility and assess the quality of evidence and possible biases.An umbrella review of systematic reviews and meta-analyses available in PubMed,Web of Science,and Scopus,covering studies published up to October 2023,was conducted.Sperm concentration,morphology,and motility were used as endpoints to evaluate the effectiveness of the treatments.Of 2998 studies,18 published meta-analyses were extracted,yielding 90 summary effects on sperm concentration(n=36),sperm morphology(n=26),and sperm motility(n=28)on 28 interventions.None of the meta-analyses were classified as having low methodological quality,whereas 12(66.7%)and 6(33.3%)had high and moderate quality,respectively.Of the 90 summary effects,none were rated high-evidence quality,whereas 53.3%(n=48),25.6%(n=23),and 21.1%(n=19)were rated moderate,low,and very low,respectively.Significant improvements in sperm concentration,morphology,and motility were observed with pharmacological interventions(N-acetyl-cysteine,antioxidant therapy,aromatase inhibitors,selective estrogen receptor modulators,hormones,supplements,and alpha-lipoic acid)and nonpharmacological interventions(varicocele repair and redo varicocelectomy).In addition,vitamin supplementation had no significant positive effects on sperm concentration,motility,or morphology.Treatments for male infertility are increasingly diverse;however,the current evidence is poor because of the limited number of patients.Further well-designed studies on single treatment and high-quality meta-analysis of intertreatment comparisons are recommended.展开更多
Topometric auscultation is used to monitor the durability of structures, measure deformations linked to the structure of a structure or to the movement of the ground over a part of the globe, set up warning systems, e...Topometric auscultation is used to monitor the durability of structures, measure deformations linked to the structure of a structure or to the movement of the ground over a part of the globe, set up warning systems, etc. It first appeared as a visual method and rapidly evolved through the various techniques used. Some of these techniques using topography are used in several fields (civil engineering, geodesy, topography, mechanics, nuclear engineering, hydraulics, physics, etc.). These topometric techniques have undergone major changes as a result of technological advances, growing needs in the monitoring of movements or deformations, increased requirements and new challenges. The methodology adopted depends on the measuring instrument used, the parameters to be estimated and access to the area to be measured. There are two types of methods: destructive and non-destructive. In addition to the visual method, they can also be classified as mechanical, physico-chemical, dynamometric, electrophysical and geometric. The estimated parameter varies according to the methodology adopted. It can be defined by coordinates, distances, potential, electrical resistance, etc.展开更多
This article examines the current status,research methodologies,and content of scoping review studies conducted by Chinese nursing scholars.Through comprehensive computer searches in nine Chinese and English databases...This article examines the current status,research methodologies,and content of scoping review studies conducted by Chinese nursing scholars.Through comprehensive computer searches in nine Chinese and English databases,a total of 204 scoping review articles authored by Chinese nursing scholars were identified.The application of scoping reviews is still in its early developmental stages,with the number of studies increasing rapidly each year,primarily focusing on clinical nursing practice.While awareness of evidence-based practices among nursing researchers has improved,challenges related to research methodology and reporting quality persist.Therefore,nursing researchers should enhance their knowledge and strictly adhere to established reporting standards and methodological frameworks for scoping reviews to elevate the quality of nursing research.展开更多
Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-com...Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-commerce provides a facility for customers to post reviews and comment about the product or service when purchased.New customers usually go through the posted reviews or comments on the website before making a purchase decision.However,the current challenge is how new individuals can distinguish truthful reviews from fake ones,which later deceives customers,inflicts losses,and tarnishes the reputation of companies.The present paper attempts to develop an intelligent system that can detect fake reviews on ecommerce platforms using n-grams of the review text and sentiment scores given by the reviewer.The proposed methodology adopted in this study used a standard fake hotel review dataset for experimenting and data preprocessing methods and a term frequency-Inverse document frequency(TF-IDF)approach for extracting features and their representation.For detection and classification,n-grams of review texts were inputted into the constructed models to be classified as fake or truthful.However,the experiments were carried out using four different supervised machine-learning techniques and were trained and tested on a dataset collected from the Trip Advisor website.The classification results of these experiments showed that na飗e Bayes(NB),support vector machine(SVM),adaptive boosting(AB),and random forest(RF)received 88%,93%,94%,and 95%,respectively,based on testing accuracy and tje F1-score.The obtained results were compared with existing works that used the same dataset,and the proposed methods outperformed the comparable methods in terms of accuracy.展开更多
Movies are the better source of entertainment.Every year,a great percentage of movies are released.People comment on movies in the form of reviews after watching them.Since it is difficult to read all of the reviews f...Movies are the better source of entertainment.Every year,a great percentage of movies are released.People comment on movies in the form of reviews after watching them.Since it is difficult to read all of the reviews for a movie,summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews.Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data.Opinion mining involves identifying and extracting the opinions of individuals,which can be positive,neutral,or negative.The task of opinion mining also called sentiment analysis is performed to understand people’s emotions and attitudes in movie reviews.Movie reviews are an important source of opinion data because they provide insight into the general public’s opinions about a particular movie.The summary of all reviews can give a general idea about the movie.This study compares baseline techniques,Logistic Regression,Random Forest Classifier,Decision Tree,K-Nearest Neighbor,Gradient Boosting Classifier,and Passive Aggressive Classifier with Linear Support Vector Machines and Multinomial Naïve Bayes on the IMDB Dataset of 50K reviews and Sentiment Polarity Dataset Version 2.0.Before applying these classifiers,in pre-processing both datasets are cleaned,duplicate data is dropped and chat words are treated for better results.On the IMDB Dataset of 50K reviews,Linear Support Vector Machines achieve the highest accuracy of 89.48%,and after hyperparameter tuning,the Passive Aggressive Classifier achieves the highest accuracy of 90.27%,while Multinomial Nave Bayes achieves the highest accuracy of 70.69%and 71.04%after hyperparameter tuning on the Sentiment Polarity Dataset Version 2.0.This study highlights the importance of sentiment analysis as a tool for understanding the emotions and attitudes in movie reviews and predicts the performance of a movie based on the average sentiment of all the reviews.展开更多
With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after ...With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.展开更多
This study aims to study the effectiveness of online English movie reviews for improving university students’English writing in China.English movie reviews can be profitably undertaken to improve university students...This study aims to study the effectiveness of online English movie reviews for improving university students’English writing in China.English movie reviews can be profitably undertaken to improve university students’writing ability by reading English movie reviews online,discussing topics related to English movie reviews and writing English movie reviews collaboratively.University students have easy access to English movie reviews massively available on the Internet,which renders it possible and feasible for English teachers to use them to improve students’English writing.Online English movie reviews provide students with enough input of model texts,hence they can acquire some appropriate expressions before writing within a short period of time.In addition,discussion on English movie reviews through Emails and QQ platform can activate students’critical thinking to stimulate their original ideas for English movie review writing.Writing English movie reviews collaboratively with the help of Internet can develop students’confidence in writing because of peer feedback and less pressure.展开更多
At present online shopping is very popular as it is very convenient for the customers.However,selecting smartphones from online shops is bit difficult only from the pictures and a short description about the item,and ...At present online shopping is very popular as it is very convenient for the customers.However,selecting smartphones from online shops is bit difficult only from the pictures and a short description about the item,and hence,the customers refer user reviews and star rating.Since user reviews are represented in human languages,sometimes the real semantic of the reviews and satisfaction of the customers are different than what the star rating shows.Also,reading all the reviews are not possible as typically,a smartphone gets thousands of reviews in popular online shopping platform like Amazon.Hence,this work aims to develop a recommended system for smartphones based on aspects of the phones such as screen size,resolution,camera quality,battery life etc.reviewed by users.To that end we apply hybrid approach,which includes three lexicon-based methods and three machine learning modals to analyze specific aspects of user reviews and classify the reviews into six categories--best,better,good or somewhat for positive comments and for negative comments bad or not recommended--.The lexicon-based tool called AFINN together with Random Forest prediction model provides the best classification F1-score 0.95.This system can be customized according to the required aspects of smartphones and the classification of reviews can be done accordingly.展开更多
Objective:To assess the reliability of the methodological quality and outcome measures of systematic reviews(SR)/meta-analysis of premature ovarian insufficiency(POI) treated with acupuncture.Methods:SR/meta-analysis ...Objective:To assess the reliability of the methodological quality and outcome measures of systematic reviews(SR)/meta-analysis of premature ovarian insufficiency(POI) treated with acupuncture.Methods:SR/meta-analysis of POI treated with acupuncture were searched on POI from the databases including PubMed,Web of Science,EMBase,the Cochran Library,Chinese biomedical literature database(SinoMed),China journal full-text database(CNKI),Wanfang data knowledge service platform(Wanfang)and VIP information Chinese periodical service platform(VIP),from inception to 1 st May 2021.Using A Measurement Tool to Assess Systematic Reviews 2(AMSTAR 2) scale and Grades of Recommendations Assessment,Development and Evaluation(GRADE) system,the methodological quality and outcome measures of the included studies were appraised.Results:Ten articles of SR/meta-analysis were included,published from 2015 to 2020.Using AMSTAR 2,5 articles of SR/meta-analysis were rated as critical low quality in methods,3 articles as low quality,and2 articles as moderate quality.The results of GRADE showed that among the 50 outcomes the quality of evidence of 22 outcomes was very low,that of 25 outcomes was low and that of 3 outcomes was moderate.Conclusion:The methodological quality and the reliability of outcome measures were not high in existing SR/meta-analysis on POI treated with acupuncture,which may affect the translation of the SR/metaanalysis findings into clinical practice.It is necessary to further strengthen the methodological quality and reporting standard of SR/meta-analysis,as well as the robustness of design and implementation of randomized controlled trials(RCTs),in order to generate high quality evidences for clinical decision-making and practice.展开更多
文摘Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic content.Tis study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie reviews.SGD allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language data.Tis adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better performance.Two distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for analysis.Te proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and efciency.Te SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both datasets.Tis indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English datasets.Tis study helps deepen the understanding of sentiments across various linguistic datasets.Unlike many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.
基金funding via a National Breast Cancer Foundation(NBCF)Chair in Breast Cancer Prevention grant(No.EC-21-001)a National Health and Medical Research Council(NHMRC)Investigator(Leader)grant(No.1194410)supported by funding from a NBCF Investigator Initiated Research Scheme grant(No.2023/IIRS0028)。
文摘Objective:Heterogeneity in the evidence of association between lifestyle factors and breast cancer(BC)incidence hampers initiatives to modify BC risk.This overview aims to synthesise evidence from systematic reviews(SRs)to inform lifestyle-related modifications for BC prevention.Methods:We systematically searched(MEDLINE,EMBASE,and CINAHL)from January 2013 to August 2023 for SRs of the association between lifestyle factors[alcohol consumption,physical activity(PA),body mass index(BMI),smoking,breastfeeding,oral contraception(OC),hormone replacement therapy(HRT),and sedentary behavior(SB)]and BC incidence.A narrative data synthesis was performed.Results:Sixty-six SRs met the eligibility criteria.Evidence from 40 SRs indicated consistent associations between the risk of BC and postmenopausal BMI increase(relative risk increase:2%-21%),use of HRT(risk increase:23%-33%),smoking(risk increase:4%-86%),and alcohol consumption(risk increase:4%-61%).Additionally,evidence from 23 SRs suggested protective associations with PA(risk decrease:10%-39%),breastfeeding(risk decrease:9%-53%),and healthy lifestyle scores(protective about 20%-26%).However,inconsistent and/or statistically non-significant associations were found between BC incidence and premenopausal BMI increase[relative risk(RR):0.78-1.08],SB(RR:1.01-1.20),and OC use[odds ratio(OR):1.01-1.35].Conclusions:This overview identifies lifestyle factors associated with BC incidence,highlighting both harmful and protective factors.Our summary findings can support information and interventions related to modifying these factors,including limiting alcohol and smoking,or avoiding postmenopausal BMI increase and HRT.
基金Chongqing University of Science and Technology Graduate Innovation Program Project(YKJCX2420802)。
文摘Against the backdrop of the strategies for rural revitalization and the integration of agriculture,culture,and tourism,farm stay,as a vital carrier,requires a systematic analysis of its resource integration effectiveness and the actual needs of tourists.Taking Chongqing City as an example,this study leverages tourist reviews from the Dianping platform(China’s leading consumer review site)and employs a combination of TF-IDF keyword extraction,SnowNLP sentiment analysis,and LDA topic modeling to dissect tourists’perception characteristics and latent demands for agritourism resources from the demand side.The findings reveal that agricultural and tourism elements garner significant attention,while cultural resources are notably underperceived,indicating an imbalanced integration structure.Sentiment is predominantly positive,yet negative feedback highlights issues in service management,transportation,and homogenized experiences.Latent demands converge on three dimensions:deepening agricultural experiences,enhancing cultural participation and interaction,and improving environmental and service quality.Based on these findings,this study proposes integration enhancement strategies,including agricultural branding,cultural vitalization,service intelligence,and multi-faceted collaboration,to drive experience upgrades and sustainable development in farm stays,offering theoretical references and practical pathways for rural tourism integration in similar regions.
基金supported by Chongqing Science and Technology Bureau Technology Innovation and Application Development Project(No.cstc2019jscx-msxmX0170)Chongqing Science and Health Joint Medical Research Project(No.2021MSXM208).
文摘Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clinic and future research.Methods:Databases including Embase,Cochrane Library,CINAHL,CNKI,SinoMed,Wanfang,and Weipu were searched to collect systematic reviews(SRs)and meta-analyses on mHealth interventions for hypertension management.Two researchers independently screened the articles and extracted data,and the Assessment of Multiple Systematic Reviews(AMSTAR 2)was used to evaluate the methodological quality of the included reviews.Results:A total of 11 SRs were included:1 review was rated as high quality,3 as low quality,and 7 as critically low quality.The mobile phone was the most common intervention type,followed by the internet.Seven reviews performed meta-analyses and showed that mHealth was associated with a significant reduction in systolic blood pressure(SBP),from 2.28 mmHg(95%CI-3.90 to-0.66;I^(2)=40%)to 14.77 mmHg(95%CI 11.76-17.77;I^(2)=89.7%),and diastolic blood pressure(DBP),from 1.50 mmHg(95%CI-2.20 to-0.08;I^(2)=62%)to 8.17 mmHg(95%CI 5.67-10.67;I^(2)=86%).Self-management behaviors included medication adherence(MA),diet,smoking,alcohol drinking,physical activity,and BP monitoring.There were inconsistent results on the effectiveness of mHealth interventions.Conclusions:mHealth interventions can improve BP control,MA,diet,and smoking in patients with hypertension,but the evidence for the efficacy of mHealth on physical activity and alcohol drinking improvement is limited.The methodological quality of existing SRs on the management of BP in patients with hypertension was relatively low,and more well-designed SRs or meta-analyses were needed to provide more evidence.mHealth interventions are useful for improving BP control of patients with hypertension.
文摘BACKGROUND Systematic reviews(SRs)synthesize and evaluate data,mainly from randomized trials,which then guides the development of clinical recommendations in evidence-based medicine.However,the data and methodological information in the included papers can often be lacking or unclear,and reviewers usually need to contact the authors of included studies for clarifications.Contacting authors is recommended,but it is unclear how often SR teams do it,or what the level of response is.AIM To investigate how often reviewers undertake contact with the authors of included randomized controlled trials(RCTs)for clarification on data and risk of bias concerns,to explore the factors that influence whether SR authors contact or do not contact the authors,and the content and level of responses.METHODS We conducted a systematic electronic database search in MEDLINE using the search string“(systematic review)”AND“(RCT OR randomized OR trial)”for articles published between 1 January 2024 and 19 February 2024,without language restrictions.Screening and data extraction was done independently by two reviewers,and conflicts resolved by a senior author.Contact authors of included SRs were contacted for clarifications.RESULTS Of the 329 included SRs,38%(n=125)explicitly mentioned contact with the authors of included studies.The remaining 62%(n=204)did not.We attempted contact with all SR teams for clarifications and received 90 responses(19.4%).Of the 50 respondents who did not explicitly mention contact in their SRs,25(50%)replied that they did make contact.We received a total of 64 responses on the level and content of information sought.The mean±SD contacts SR teams made were 10(10),replies received 5(6.7),and response waiting time 10.1(28.3)weeks.Resources,time,poor previous experience,perceived likelihood of poor response and bias concerns were reported as barriers to attempting contact.CONCLUSION The majority of SRs published in 2024 did not confirm seeking clarifying or missing information from primary study authors.However,SR teams reported that 50%of contacted primary authors respond.Additional research can clarify this rate of response and establish methods to increase the integration of this core methodological element in SRs.
基金supported by Chinese Medicine Development Fund of the Hong Kong SAR(No.21B2/018A)。
文摘Objective:This cross-sectional study assessed the methodological quality of systematic reviews(SRs)of Chinese herbal medicine(CHM)published in Chinese between Jan 2021 and Sep 2022.Methods:Chinese language CHM SRs were identified through literature searches across 3 international and 4 Chinese databases.Methodological quality was appraised using A MeaSurement Tool to Assess systematic Reviews 2.Logistic regressions were used to explore associations between bibliographical characteristics and quality.Results:Analyses of methodological quality found that among the 213 sampled SRs,69.5%were of critically low quality,30.5%were of low quality,and none achieved high or moderate quality.Common shortcomings included the failure to identify the studies excluded from the analysis,failure to disclose funding sources,and limited evaluation of the potential impact of bias on conclusions.Logistic regressions revealed that SRs led by corresponding authors affiliated with universities or academic institutions tended to be of lower quality than SRs led by authors affiliated with hospitals or clinical facilities.Conclusion:Recent Chinese language CHM SRs exhibited limited methodological quality,making them unlikely to support the development of clinical practice guidelines.Urgent initiatives are needed to enhance training for researchers,peer-reviewers and editors involved in the preparation and publication of SRs.Adoption of Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines in Chinese language journals is crucial to improve the relevance of SRs for Chinese medicine development.Addressing deficiencies in methodology and reporting is essential for promoting evidence-based practices and informed clinical decisions in Chinese medicine.
文摘Movies reviews provide valuable insights that can help people decide which movies are worth watching and avoid wasting their time on movies they will not enjoy.Movie reviews may contain spoilers or reveal significant plot details,which can reduce the enjoyment of the movie for those who have not watched it yet.Additionally,the abundance of reviews may make it difficult for people to read them all at once,classifying all of the movie reviews will help in making this decision without wasting time reading them all.Opinion mining,also called sentiment analysis,is the process of identifying and extracting subjective information from textual data.This study introduces a sentiment analysis approach using advanced deep learning models:Extra-Long Neural Network(XLNet),Long Short-Term Memory(LSTM),and Convolutional Neural Network-Long Short-Term Memory(CNN-LSTM).XLNet understands the context of a word from both sides,which is helpful for capturing complex language patterns.LSTM performs better in modeling long-term dependencies,while CNN-LSTM combines local and global context for robust feature extraction.Deep learning models take advantage of their ability to extract complex linguistic patterns and contextual information from raw text data.We carefully cleaned the IMDb movie reviews dataset with the goal of optimizing the results of models used in the experiment.This involves eliminating unnecessary punctuation,links,hashtags,stop words,and duplicate reviews.Lemmatization is also used for keeping consistent word forms.This cleaned IMDb dataset is evaluated on the proposed model for sentiment analysis in which XLNet performs well achieving an impressive 93.74%accuracy on the IMDb Dataset.The findings highlight the effectiveness of deep learning models in improving sentiment analysis,showing its potential for wider applications in natural language processing.
基金supported by the Evidence-based Capacity Building Project of Traditional Chinese medicine of the National Administration of Traditional Chinese Medicine(60102)the Fundamental Research Funds for the Central Public Welfare Research Institutes(49425).
文摘Objective:To summarize the characteristics and evaluate the quality of the methodology and evidence within systematic reviews(SRs)of Chinese herbal medicine(CHM)for Mycoplasma pneumoniae pneumonia(MPP)inchildren.Methods:SRs of randomized controlled trials were searched using PubMed,the Cochrane Library,Embase,the Chinese National Knowledge Infrastructure Databases(CNKI),the Chinese Scientific Journals Database(VIP),Wanfang,and the SinoMed Database.SRs on the use of CHM alone or in combination with Western medications for MPP in children were included.The study compared the effects of Western medicine alone with those of CHM.The evidence quality using the A Measurement Tool to Assess Systematic Reviews(AMSTAR)2,the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)2020,and the Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)criteria.The primary indicators were the total effective rate,fever subsidence time,and cough disappearance time.The secondary outcomes were pulmonary rale disappearance time,average hospitalization time,lung X-ray infiltrate disappearance time,immunological indices,and inflammatory cytokine levels.Results:Twelve relevant SRs were included;75%(9/12)were assessed as very low quality,and 25%(3/12)Were rated as low quality using the AMSTAR 2 criteria.According to the PRISMA 2020 checklist,the average SR score was 20.3 out of a 27 point maximum.In all SRs,CHM demonstrated improvement in symptoms and signs among children with MPP.The evidence quality using the GRADE criteria ranged from"very low"(>50%)to"moderate"(<5%).The most common downgrading factor was imprecision,followed by publication bias and inconsistency.Conclusion:This overview highlights the limited quality of the methodology and evidence of the included SRs.Although the included studies showed the beneficial effects of CHM on MPP in children,it was difficult to draw firm conclusions owing to methodological flaws.
基金the National Natural Science Foundation of China:Study on the Mechanisms of Multi-target Immunomodulation by Hydrolyzed Nanzhu Tablets in Children with RRTI Based on scRNAseq Technology(No.82060825)Huang Danian-type Teacher Team of National Universities-Teacher Team of Basic Course of Chinese and Western Medicine(Ministry of Education Teacher Letter[2022]No.2)+2 种基金Guangxi Famous Chinese Medicine Doctor Lin Jiang Inheritance Studio(Gui TCM Science and Education Development[2021]No.6)Guangxi First-class Discipline of Chinese Medicine(Gui Textbook Research[2022]No.1)Guangxi Interdisciplinary Innovation Team of Chinese Medicine(GZKJ2302)。
文摘OBJECTIVE:To evaluate and summarise the evidence from published Meta-analyses/systematic reviews(MAs/SRs)of Traditional Chinese Medicine(TCM)in the treatment of recurrent respiratory tract infections(RRTIs)and to provide a scientific basis for the clinical treatment of RRTIs with TCM.METHODS:Studies were retrieved from Chinese and English databases including the China National Knowledge Infrastructure,Wanfang database,China Science and Technology Journal Database,SinoM ed,PubM ed,Web of Science,the Cochrane Library and EMbase from their establishment date to March 2023.Involved studies were screened,extracted,and evaluated for quality by two researchers independently.The a measurement tool to assess systematic reviews(AMSTAR)2 scale was used for methodological quality evaluation,as well as the preferred reporting items for systematic reviews and Meta-analyses(PRISMA)2020 statement for report quality evaluation,the risk of bias in systematic reviews(ROBIS)tool for risk of bias,and the grading of recommendations,assessment,development and evaluation(GRADE)quality assessment tool for evidence quality.RESULTS:Twenty MAs/SRs studies were included,including analyses of 274 original studies involving 38335 patients with RRTIs.The AMSTAR 2 scale evaluation results showed that 19 studies were of very low quality and one of moderate quality.The ROBIS evaluation results showed that 11 MAs/SRs were at high risk and nine at low risk of bias.The PRISMA 2020 report quality showed the included studies had scores between 23.5 and 35.5,among them one with high quality,17 with moderate quality and two with low quality.The GRADE system results showed that among 126 outcome indicators,only 17 had moderate quality of evidence,27 had low quality,82 had very low quality,and none had high quality.CONCLUSIONS:The MAs/SRs methodological quality of using TCM for treatment RRTIs is generally poor,the quality of reports as well as of evidence is generally low,and the risk of bias is high;therefore we should treat these results with caution.
基金supported by the National Natural Science Foundation of China(grant No.81500522)the Science and Technology Department of Sichuan Province(No.2020YFS0090 and No.2020YFS0046).
文摘This umbrella review aimed to summarize and provide a general evaluation of the effectiveness of current treatments for male infertility and assess the quality of evidence and possible biases.An umbrella review of systematic reviews and meta-analyses available in PubMed,Web of Science,and Scopus,covering studies published up to October 2023,was conducted.Sperm concentration,morphology,and motility were used as endpoints to evaluate the effectiveness of the treatments.Of 2998 studies,18 published meta-analyses were extracted,yielding 90 summary effects on sperm concentration(n=36),sperm morphology(n=26),and sperm motility(n=28)on 28 interventions.None of the meta-analyses were classified as having low methodological quality,whereas 12(66.7%)and 6(33.3%)had high and moderate quality,respectively.Of the 90 summary effects,none were rated high-evidence quality,whereas 53.3%(n=48),25.6%(n=23),and 21.1%(n=19)were rated moderate,low,and very low,respectively.Significant improvements in sperm concentration,morphology,and motility were observed with pharmacological interventions(N-acetyl-cysteine,antioxidant therapy,aromatase inhibitors,selective estrogen receptor modulators,hormones,supplements,and alpha-lipoic acid)and nonpharmacological interventions(varicocele repair and redo varicocelectomy).In addition,vitamin supplementation had no significant positive effects on sperm concentration,motility,or morphology.Treatments for male infertility are increasingly diverse;however,the current evidence is poor because of the limited number of patients.Further well-designed studies on single treatment and high-quality meta-analysis of intertreatment comparisons are recommended.
文摘Topometric auscultation is used to monitor the durability of structures, measure deformations linked to the structure of a structure or to the movement of the ground over a part of the globe, set up warning systems, etc. It first appeared as a visual method and rapidly evolved through the various techniques used. Some of these techniques using topography are used in several fields (civil engineering, geodesy, topography, mechanics, nuclear engineering, hydraulics, physics, etc.). These topometric techniques have undergone major changes as a result of technological advances, growing needs in the monitoring of movements or deformations, increased requirements and new challenges. The methodology adopted depends on the measuring instrument used, the parameters to be estimated and access to the area to be measured. There are two types of methods: destructive and non-destructive. In addition to the visual method, they can also be classified as mechanical, physico-chemical, dynamometric, electrophysical and geometric. The estimated parameter varies according to the methodology adopted. It can be defined by coordinates, distances, potential, electrical resistance, etc.
文摘This article examines the current status,research methodologies,and content of scoping review studies conducted by Chinese nursing scholars.Through comprehensive computer searches in nine Chinese and English databases,a total of 204 scoping review articles authored by Chinese nursing scholars were identified.The application of scoping reviews is still in its early developmental stages,with the number of studies increasing rapidly each year,primarily focusing on clinical nursing practice.While awareness of evidence-based practices among nursing researchers has improved,challenges related to research methodology and reporting quality persist.Therefore,nursing researchers should enhance their knowledge and strictly adhere to established reporting standards and methodological frameworks for scoping reviews to elevate the quality of nursing research.
文摘Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-commerce provides a facility for customers to post reviews and comment about the product or service when purchased.New customers usually go through the posted reviews or comments on the website before making a purchase decision.However,the current challenge is how new individuals can distinguish truthful reviews from fake ones,which later deceives customers,inflicts losses,and tarnishes the reputation of companies.The present paper attempts to develop an intelligent system that can detect fake reviews on ecommerce platforms using n-grams of the review text and sentiment scores given by the reviewer.The proposed methodology adopted in this study used a standard fake hotel review dataset for experimenting and data preprocessing methods and a term frequency-Inverse document frequency(TF-IDF)approach for extracting features and their representation.For detection and classification,n-grams of review texts were inputted into the constructed models to be classified as fake or truthful.However,the experiments were carried out using four different supervised machine-learning techniques and were trained and tested on a dataset collected from the Trip Advisor website.The classification results of these experiments showed that na飗e Bayes(NB),support vector machine(SVM),adaptive boosting(AB),and random forest(RF)received 88%,93%,94%,and 95%,respectively,based on testing accuracy and tje F1-score.The obtained results were compared with existing works that used the same dataset,and the proposed methods outperformed the comparable methods in terms of accuracy.
文摘Movies are the better source of entertainment.Every year,a great percentage of movies are released.People comment on movies in the form of reviews after watching them.Since it is difficult to read all of the reviews for a movie,summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews.Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data.Opinion mining involves identifying and extracting the opinions of individuals,which can be positive,neutral,or negative.The task of opinion mining also called sentiment analysis is performed to understand people’s emotions and attitudes in movie reviews.Movie reviews are an important source of opinion data because they provide insight into the general public’s opinions about a particular movie.The summary of all reviews can give a general idea about the movie.This study compares baseline techniques,Logistic Regression,Random Forest Classifier,Decision Tree,K-Nearest Neighbor,Gradient Boosting Classifier,and Passive Aggressive Classifier with Linear Support Vector Machines and Multinomial Naïve Bayes on the IMDB Dataset of 50K reviews and Sentiment Polarity Dataset Version 2.0.Before applying these classifiers,in pre-processing both datasets are cleaned,duplicate data is dropped and chat words are treated for better results.On the IMDB Dataset of 50K reviews,Linear Support Vector Machines achieve the highest accuracy of 89.48%,and after hyperparameter tuning,the Passive Aggressive Classifier achieves the highest accuracy of 90.27%,while Multinomial Nave Bayes achieves the highest accuracy of 70.69%and 71.04%after hyperparameter tuning on the Sentiment Polarity Dataset Version 2.0.This study highlights the importance of sentiment analysis as a tool for understanding the emotions and attitudes in movie reviews and predicts the performance of a movie based on the average sentiment of all the reviews.
文摘With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.
文摘This study aims to study the effectiveness of online English movie reviews for improving university students’English writing in China.English movie reviews can be profitably undertaken to improve university students’writing ability by reading English movie reviews online,discussing topics related to English movie reviews and writing English movie reviews collaboratively.University students have easy access to English movie reviews massively available on the Internet,which renders it possible and feasible for English teachers to use them to improve students’English writing.Online English movie reviews provide students with enough input of model texts,hence they can acquire some appropriate expressions before writing within a short period of time.In addition,discussion on English movie reviews through Emails and QQ platform can activate students’critical thinking to stimulate their original ideas for English movie review writing.Writing English movie reviews collaboratively with the help of Internet can develop students’confidence in writing because of peer feedback and less pressure.
文摘At present online shopping is very popular as it is very convenient for the customers.However,selecting smartphones from online shops is bit difficult only from the pictures and a short description about the item,and hence,the customers refer user reviews and star rating.Since user reviews are represented in human languages,sometimes the real semantic of the reviews and satisfaction of the customers are different than what the star rating shows.Also,reading all the reviews are not possible as typically,a smartphone gets thousands of reviews in popular online shopping platform like Amazon.Hence,this work aims to develop a recommended system for smartphones based on aspects of the phones such as screen size,resolution,camera quality,battery life etc.reviewed by users.To that end we apply hybrid approach,which includes three lexicon-based methods and three machine learning modals to analyze specific aspects of user reviews and classify the reviews into six categories--best,better,good or somewhat for positive comments and for negative comments bad or not recommended--.The lexicon-based tool called AFINN together with Random Forest prediction model provides the best classification F1-score 0.95.This system can be customized according to the required aspects of smartphones and the classification of reviews can be done accordingly.
基金Supported by National Key R&D Program of China2019YFC1712200International standards research on clinical research and service of AcupunctureMoxibustion2019YFC1712205。
文摘Objective:To assess the reliability of the methodological quality and outcome measures of systematic reviews(SR)/meta-analysis of premature ovarian insufficiency(POI) treated with acupuncture.Methods:SR/meta-analysis of POI treated with acupuncture were searched on POI from the databases including PubMed,Web of Science,EMBase,the Cochran Library,Chinese biomedical literature database(SinoMed),China journal full-text database(CNKI),Wanfang data knowledge service platform(Wanfang)and VIP information Chinese periodical service platform(VIP),from inception to 1 st May 2021.Using A Measurement Tool to Assess Systematic Reviews 2(AMSTAR 2) scale and Grades of Recommendations Assessment,Development and Evaluation(GRADE) system,the methodological quality and outcome measures of the included studies were appraised.Results:Ten articles of SR/meta-analysis were included,published from 2015 to 2020.Using AMSTAR 2,5 articles of SR/meta-analysis were rated as critical low quality in methods,3 articles as low quality,and2 articles as moderate quality.The results of GRADE showed that among the 50 outcomes the quality of evidence of 22 outcomes was very low,that of 25 outcomes was low and that of 3 outcomes was moderate.Conclusion:The methodological quality and the reliability of outcome measures were not high in existing SR/meta-analysis on POI treated with acupuncture,which may affect the translation of the SR/metaanalysis findings into clinical practice.It is necessary to further strengthen the methodological quality and reporting standard of SR/meta-analysis,as well as the robustness of design and implementation of randomized controlled trials(RCTs),in order to generate high quality evidences for clinical decision-making and practice.
