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.

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.

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.

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.

Strategies for Effective Comments on Students’ Written Assignments

Abstract:Comments on students’assignments are important for English course.The loopholes in teachers’working schemes-comments of their students’written assignments are the clues around which the paper spreads.In the process of teaching,some English teachers pay so much attention to the contents taught in class but ignore the comments on students’written assignments.Consequently,it is not applicable for students to correct their mistakes in time and they probably make the same mistakes repeatedly.

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.

Impact of Online Comments on Purchase Intention of College Student Consumers under Online Shopping

With the rapid development of network technology,online shopping has been constantly growing,and how to make better use of the dissemination effect of online comment has become an imperative and practical issue. Based on review of the existing literature,this paper established the theoretical research model and used the literature research and empirical research combined method to analyze the impact of online comment on purchase intention of college student consumers under online shopping. The research results indicate that the quantity,quality,valence and timeliness of online comments exert a significant impact on the purchase intention of college student consumers.

Influence of Online Comments on Tourist' Purchase Intention Based on Questionnaire Survey among Tourists in Tai'an City

Taking tourists in Tai'an City—an outstanding tourism city of China for example, this paper explored the influence of online comments(word-of-mouth effect) on tourists' intention of purchasing services of accommodation facilities and restaurants through analyzing 502 valid questionnaires. Then measures and suggestions were proposed for tourist enterprises improving online word-of-mouth marketing.

Editor＇s comments

This review article entitled ＂Physiological approaches to understanding molecular actions on dorsolateral prefrontal cortical neurons underlying higher cognitive processing＂ examines the relationship between neurotransmitters and prefrontal cognitive function. The authors of this article are leading the field in such research.

Comments from Ambassadors to China

Belt and Rod Initiative Boosts Infrastructure Construction in Africa H.E.Edward Boateng Ghanaian Ambassador to ChinaChina’s Government Work Report is rich in information that not only summarizes development achievements from 2018, but also proposes detailed planning for further development in2019 and beyond. What’s particularly impressive is notion of socialism with Chinese characteristics in President Xi’s era. The Chinese government is attaching greater importance to on the people and have considerably raised the standard of living in the course of development.

Comments on PVPs,MPPs,NOWS,and Future Computer Architectures

Abstract Using 1995 results from the NASA Parallel Benchmarks, this paper compares the sustained performance (as opposed to peak performance) and cost per unit of sustained performance for state-of-the--art Parallel processing systems that use MicroProcessors(MPP) versus those that use Custom-designed Processors (PVP). This comparison shows that MPPs approach, but seldom surpass, PCPs with respect to either metric. This paper also discusses the merits and demerits of 'clusters' of workstations Ironically, recently introduced low--cost, parallel systems can also be viewed as 'virtual workstation clusters' that offer comparable, if not superior, capabilitics. Finally, this paper explores the question of whether it will be economically feasible for computer manut'acturers to continue building PVPs, or are MPPs the only economically viable option for building parallel systems?

Responses to the comments of Prof. Frederic Meunier

Thanks for your straightforward comments and constructive suggestions on our recent study on dual‐beam FT‐IR spectroscopy published in Chin.J.Catal.,2017,38,13?19.We are glad to reply your questions and to give some supplementary remarks concerning the dual beam FT‐IR spectrometer,its usage and application progress.The first question you posed is about the nature of the feed gas flow regime in sample cell(e.g.,plug flow or CSTR‐like).You worry about a non‐CSTR flow regime in the sample cell of our dual beam IR‐cell reactor,which will result in difference in the gas composition of sample cell and reference cell,and consequently an imperfect gas‐phase correction.

Your comments are welcome!

I am a press officer in the Embassy of Belarus in Beijing. Having studied in China for a couple of years, I can speak Chinese fluently and am very interested in Chinese culture and history. I was reading the June issue of China Today and was impressed with the smiling face of a Chinese lady holding a bunch of yellow and white chrysanthemums. It is in a special report titled “Who Will Triumph in the Horticulture Industry,” which gives a panoramic view of the 2019 Beijing International Horticulture Exhibition. It reminds me of a group of photos shot by my former colleague and his wife who is a famous journalist in Belarus. The couple plan to have an exhibition of their photos featuring all kinds of smiling faces of Chinese people taken during their stay in China for almost two decades.

Comments on “An ultrafast rechargeable aluminum ion battery”

Nature published an article'An ultrafast rechargeable aluminum ion battery'On April 6,2015.The authors used many new materials to compose the cell,such as three-dimensional graphitic-foam as the cathode,an ionic liquid electrolyte.The experimental cell has shown well-defined discharge voltage plateaus near 2 V.The cell is mechanically bendable and foldable without affecting its operation.

Case study of teachers＇ motivational comments

This paper aims at demonstrating what is motivational comments from teachers which can motivate students to participate in classroom activities and showing patterns of feedback occurring in real classroom teacher-student interaction by doing a case study of episodes of teacher＇s feedback in an English class.

Comments on Zeng's Paper “Variational Principle of Instability of Atmospheric Motions”

After my paper (Zeng, 1986b) was published and another (Zeng, 1989) was submitted to the journal, I found two papers written by Arnold (1966) and McIntyre et al. (1987) and received some reprints of Ripa’s papers (1983; 1984; 1987; 1988) in the same field. I thank Drs. Mu Mu and Pedro Ripa very much for showing and sending me these interesting papers.

Your comments are welcome!

I am the marketing and communications manager of British Council.We have a good relationship with China Today and have invited your reporters to cover some very big events,for example,the state visit of Prime Minister Theresa May in January 2018.China Today has also covered some of our big programs in China such as the first“U.K.-China Year of Cultural Exchange”in 2015,the“Shakespeare Lives,”a global celebration to mark the 400th anniversary of Shakespeare’s death in 2016,and cultural programs that we are proud of,like“Inspiring Women,”a year-long campaign that showcased leading female figures in the U.K.and China.All these programs threw a spotlight on people links,focusing on the shared interest of our young people.It also shows how the U.K.’s interest is in making a strong,broad,and deep relationship with China.This year 2019 marks the 40th anniversary of the establishment of British Council in China,thus we will have more opportunities to collaborate with each other to promote bilateral relations and enhance mutual understanding in the“golden era.”

Comments on “General solutions of plane problem for power function curved cracks”

An error has been found in Ref. [1]. In the case of n = 2, authors of Ref. [1] suggested the following conformal mapping function：

Hybrid Algorithm to Evaluate E-Business Website Comments

Online reviews are considered of an important indicator for users to decide on the activity they wish to do, whether it is watching a movie, going to a restaurant, or buying a product. It also serves businesses as it keeps tracking user feedback. The sheer volume of online reviews makes it difficult for a human to process and extract all significant information to make purchasing choices. As a result, there has been a trend toward systems that can automatically summarize opinions from a set of reviews. In this paper, we present a hybrid algorithm that combines an auto-summarization algorithm with a sentiment analysis (SA) algorithm, to offer a personalized user experiences and to solve the semantic-pragmatic gap. The algorithm consists of six steps that start with the original text document and generate a summary of that text by choosing the N most relevant sentences in the text. The tagged texts are then processed and then passed to a Naive Bayesian classifier along with their tags as training data. The raw data used in this paper belong to the tagged corpus positive and negative processed movie reviews introduced in [1]. The measures that are used to gauge the performance of the SA and classification algorithm for all test cases consist of accuracy, recall, and precision. We describe in details both the aspect of extraction and sentiment detection modules of our system.