Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

Additional comments on foot reflexology treatment for sensorineural hearing loss in infant

Currently,treatment options for infant sensorineural hearing loss(SNHL)are limited.This article describes a novel case of SNHL in an infant successfully treated with foot reflexology,along with observed brain activity changes before and after treatment,as indicated by functional magnetic resonance imaging.Hence,this commentary discusses the case and our viewpoints regarding foot reflexology for treating SNHL.

Emotional differences based on comments on doctor-patient disputes with varying levels of severity

BACKGROUND The risks associated with negative doctor-patient relationships have seriously hindered the healthy development of medical and healthcare and aroused wide-spread concern in society.The number of public comments on doctor-patient relationship risk events reflects the degree to which the public pays attention to such events.Thirty incidents of doctor-patient disputes were collected from Weibo and TikTok,and 3655 related comments were extracted.The number of comment sentiment words was extracted,and the comment sentiment value was calculated.The Kruskal-Wallis H test was used to compare differences between each variable group at different levels of incidence.Spearman’s correlation analysis was used to examine associations between variables.Regression analysis was used to explore factors influencing scores of comments on incidents.RESULTS The study results showed that public comments on media reports of doctor-patient disputes at all levels are mainly dominated by“good”and“disgust”emotional states.There was a significant difference in the comment scores and the number of partial emotion words between comments on varying levels of severity of doctor-patient disputes.The comment score was positively correlated with the number of emotion words related to positive,good,and happy)and negatively correlated with the number of emotion words related to negative,anger,disgust,fear,and sadness.CONCLUSION The number of emotion words related to negative,anger,disgust,fear,and sadness directly influences comment scores,and the severity of the incident level indirectly influences comment scores.

Enhancing User Security on Instagram: A Multifaceted AI System for Filtering Abusive Comments

Social media platforms like Instagram have increasingly become venues for online abuse and offensive comments. This study aimed to enhance user security to create a safe online environment by eliminating hate speech and abusive language. The proposed system employed a multifaceted approach to comment filtering, incorporating the multi-level filter theory. This involved developing a comprehensive list of words representing various types of offensive language, from slang to explicit abuse. Machine learning models were trained to identify abusive messages through sentiment analysis and contextual understanding. The system categorized comments as positive, negative, or abusive using sentiment analysis algorithms. Employing AI technology, it created a dynamic filtering mechanism that adapted to evolving online language and abusive behavior. Integrated with Instagram while adhering to ethical data collection principles, the platform sought to promote a clean and positive user experience, encouraging users to focus on non-abusive communication. Our machine-learned models, trained on a cleaned Arabic language dataset, demonstrated promising accuracy (75.8%) in classifying Arabic comments, potentially reducing abusive content significantly. This advancement aimed to provide users with a clean and positive online experience.

The Impact of Classroom Evaluation on Chinese Learning Motivation:A Comparative Study of Oral Feedback and Written Comments

Classroom evaluation plays a critical role in shaping students’learning experiences,influencing not only their academic performance but also their motivation and engagement.In the context of primary Chinese language learning,oral feedback and written comments are two prevalent evaluation methods.This paper explores how these different types of feedback impact students’motivation,learning outcomes,and participation.By comparing the immediacy of oral feedback with the systematic nature of written comments,this study seeks to provide insights into how educators can utilize classroom evaluations more effectively to foster motivation in Chinese language learners.The findings indicate that both feedback methods have unique strengths,and a balanced approach may optimize learning outcomes.

Syntax-Based Aspect Sentiment Quad Prediction by Dual Modules Neural Network for Chinese Comments

Aspect-Based Sentiment Analysis(ABSA)is one of the essential research in the field of Natural Language Processing(NLP),of which Aspect Sentiment Quad Prediction(ASQP)is a novel and complete subtask.ASQP aims to accurately recognize the sentiment quad in the target sentence,which includes the aspect term,the aspect category,the corresponding opinion term,and the sentiment polarity of opinion.Nevertheless,existing approaches lack knowledge of the sentence’s syntax,so despite recent innovations in ASQP,it is poor for complex cyber comment processing.Also,most research has focused on processing English text,and ASQP for Chinese text is almost non-existent.Chinese usage is more casual than English,and individual characters contain more information.We propose a novel syntactically enhanced neural network framework inspired by syntax knowledge enhancement strategies in other NLP studies.In this framework,part of speech(POS)and dependency trees are input to the model as auxiliary information to strengthen its cognition of Chinese text structure.Besides,we design a relation extraction module,which provides a bridge for the overall extraction of the framework.A comparison of the designed experiments reveals that our proposed strategy outperforms the previous studies on the key metric F1.Further experiments demonstrate that the auxiliary information added to the framework improves the final performance in different ways.

Tackling Faceless Killers: Toxic Comment Detection to Maintain a Healthy Internet Environment

According to BBC News,online hate speech increased by 20%during the COVID-19 pandemic.Hate speech from anonymous users can result in psychological harm,including depression and trauma,and can even lead to suicide.Malicious online comments are increasingly becoming a social and cultural problem.It is therefore critical to detect such comments at the national level and detect malicious users at the corporate level.To achieve a healthy and safe Internet environment,studies should focus on institutional and technical topics.The detection of toxic comments can create a safe online environment.In this study,to detect malicious comments,we used approxi-mately 9,400 examples of hate speech from a Korean corpus of entertainment news comments.We developed toxic comment classification models using supervised learning algorithms,including decision trees,random forest,a support vector machine,and K-nearest neighbors.The proposed model uses random forests to classify toxic words,achieving an F1-score of 0.94.We analyzed the trained model using the permutation feature importance,which is an explanatory machine learning method.Our experimental results confirmed that the toxic comment classifier properly classified hate words used in Korea.Using this research methodology,the proposed method can create a healthy Internet environment by detecting malicious comments written in Korean.

Critical Discourse Analysis Based on Halliday’s Systemic Functional Linguistics: Taking The Economist’s First Commentation on the End of China’s Zero-COVID Policy as an Example

Based on Halliday’s systemic functional grammar,especially the ideational function,this research aims at disclosing the hidden ideologies and values of the seemingly objective news reports on China’s COVID-19 policies in The Economist.Transitivity,voice,and nominalization are the major analytical subjects.After China lifted the zero-COVID policy,western media began criticizing China’s lack of data sharing,with some misinformation and misleading reports.The denouncement of inertness and reluctance to fight against the pandemic disclaim the Chinese government’s efforts and depreciate China’s image.China is portrayed as the villain and destroyer of people’s health worldwide.Meanwhile,they also hold a hesitant attitude toward China’s diplomacy.The re-engaging with foreign countries and travel restrictions have been described as imprudent and rushed actions.They also consider China as the fuse of contradiction in the United Nations.What is overt is their view of breaking up China.

Development of Comment Correlation Matrix for Mobile Application Recommendation

As the evolution of mobile technology, mobile devices have become an essential tool in people＇s daily life. Moreover, with the rapid growth of Internet and mobile networks, people can easily access various services provided by mobile platforms. Many services can be executed on the mobile devices with various mobile applications launched to mobile platforms. People can choose what they like to install in their mobile devices and hence make their life more convenient, entertaining, and productive. However, there are too many mobile applications for users to choose. The goal of this research is to propose a methodology which can recommend top-N lists for mobile applications. A comment correlation matrix is proposed. Furthermore, a recommendation algorithm for mobile applications based on user comments and key attributes is built. With the proposed method, it outperforms Google play and is closer to user real feelings.

Comment on Thackeray's Vanity Fair

William Makepeace Thackeray is a great critical realistic writer,whose works are very profound.And his masterpiece,Vanity Fair,has superb artistic accomplishment.Thackeray’s description and satirical criticism of the life of the bourgeoisie and aristocracy is sharp,penetrating and unique.His Vanity Fair fully embodies his viewpoint that a novel should reflect nature and reality,and transmit the real situation and true feelings.

An Analysis of Comment on English Majors＇ Writing in China＇s Teachers College

This paper investigates what English majors in China＇s teachers college think about their teachers＇ comments on their written work in order to find proper ways of commenting by teachers.

Comment on Approaches and Methods in Language Teaching

The advantages and the disadvantages of 7 teaching methods are obvious in this paper through a brief comment.The contrast between the similar methods is also presented.In practice,it is a better measure to synthesizing several teaching methods in a lesson.

Reply to the Comment by Tan Mingxuan et al.(2017), on “A new Discovery of the Early Cretaceous Supercritical Hyperpycnal Flow Deposits on the Lingshan Island, East China”

We thank Tan Mingxuan et al. （2017） for their comments stimulated by our short paper in the recent Acta Geologica Sinica （English edition）. We are grateful for the opportunity to expand on the model of the supercritical hyperpycnal flow deposits in the Beilaishi section on the Lingshan Island, and to explain why the model proposed by Tan Mingxuan et al. （2017） cannot explain the bulk of the deposits in the Beilaishi section. We do not dispute that the recognition of supercritical flow deposits remains ambiguous （Ono and Plink-Bjorklund, 2017）. To some extent, the morphology of deep-water supercritical flow deposits is similar to hummocky and swaley cross- stratification （Ono and Plink-Bjorklund, 2017）. Besides, distinguishing the deposits laid down by gravity flows in deep-water systems from those produced by storm-related combined flows in continental shelf systems is not an easy task （Ono and Plink-Bjorklund, 2017）. However, a correct interpretation is crucial for understanding the paleogeographic and depositional model.

The Research Comment on Organic Food Consumer Behavior

Since the development of organic food,to a great extent,depends on the needs of consumers,the studies on the consumer behavior of organic food would have far-reaching significance to the development of the whole organic food industry. The recent studies in this field mainly include the following four aspects: the consumers' recognition of organic food; the consumers' attitude towards organic food; the consumers' purchase of organic food; the consumers' willingness to pay. The paper would review the recent domestic and foreign studies on the four aspects mentioned above,aiming to provide references to the researches in this field.

Technical comments on rodent spinal cord injuries models

Spinal cord injuries （SCI） in rodents have been created by laceration, contusion, compression, or intramedullary injection of toxic agents. The choice of an appropriate SCI model should be made for each study based on the experimental design, with care taken to avoid unintended complications such as hemorrhage. Technical comments will be made in this communication describing the 1） importance of vertebral stabi- lization, 2） injury preparation, and 3） landmarks to improve the preci- sion and reproducibility of the SCI.

Commenting On "The Secret Life of Walter Mitty"

'The Secret Life of Walter Mitty'is written by James Thurber, who is the best known humorist in modern times. Thurber is famous both for his writing and his cartoon.Many critics consider him the finest American humorist since Mark Twain and like Twain, his humor takes the form of ironic satire.

Comment on "p38 MAPK inhibition alleviates experimental acute pancreatitis in mice"

To the Editor：I read with great interest the article by Cao et al[1] re- porting a potential therapeutic utility of p38 inhibitors for acute pancreatitis. Using a preclinical mouse model where acute pancreatitis was induced by administra- tion of cerulein （a cholecystokinin analog derived from the tree frog Litoria caerulea）, the authors reported that the p38 MAPK inhibitor SB203580, administered intra- peritoneally before and after the first administration of cerulein, relieved signs associated with acute pancreatitis, including decreased HSP60 and HSP70 expression, and serum IL-6, amylase and lipase activities. Although the study remains descriptive and pharmacodynamic aspects were not examined in depth, it still has a merit as it undoubtedly provides a basis for further investigation into the potential utility of targeting p38 signaling for acute pancreatitis, a common serious condition that can be life-threatening.

AN EFFICIENT APPROACH TO COMMENT SPAM IDENTIFICATION

This paper proposes a novel approach to comment spam identification based on content analysis. Three main features including the number of links, content repetitiveness, and text similarity are used for comment spam identification. In practice, content repetitiveness is determined by the length and frequency of the longest common substring. Furthermore, text similarity is calculated using vector space model. The precisions of preliminary experiments on comment spam identification conducted on Chinese and English are as high as 93% and 82% respectively. The results show the validity and language independency of this approach. Compared with conventional spam filtering approaches, our method requires no training, no rule sets and no link relationships. The proposed approach can also deal with new comments as well as existing comments.

Comment on profitability analysis of a femtosecond laser system for cataract surgery using a fuzzy logic approach

Dear Editor,We read with interest the recently published study by Trigueros et al（[1]）,highlighting the financial and management conditions of femtosecond laser-assisted cataract surgery（FLACS）.The authors derived a simulation to estimate.

Response to Comment on "The role of wildlife (wild birds) in the global transmission of antimicrobial resistance genes"

DEAR EDITOR,Since our first identification of plasmid-mediated colistin resistance gene mcr-1 in 2015 （Liu et al., 2016）, it has been described in human clinics, domestic animals, foods, and the environment worldwide （Schwarz ＆ Johnson, 2016）. Although it is still rare, the emergence of mcr-I in wild animals is of great concern. We summarized two previous reports on mcr-1 in wild birds from Lithuania and Argentina to describe its emergence and characteristics in wildlife and highlight the potentially important role of wild animals, particularly birds, in its global transmission （Wang et al., 2017）. The first detection of mcr-1 in wildlife in Asia was identified in an extended-spectrum β- lactamase-producing Escherichia coil strain isolated from Eurasian coot （Fulica atra）,