AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Research on the Influence of Anchor Attributes on Consumers’Online Behaviors in Social E-Commerce Platforms:The Moderating Effect of Platform Contextual Factors

As e-commerce continues to mature,the advantages of live streaming within the industry have become increasingly apparent,offering significant growth opportunities.Social e-commerce platforms,which are user-centered,integrate social networks with e-commerce by leveraging social interactions to drive product sales and enhance the overall consumer shopping experience.This type of e-commerce fosters engagement and promotes products by merging online communities with shopping behavior,creating a more interactive and dynamic marketplace.It not only retains the traditional e-commerce trading and marketing functions but also adds a social dimension,making live stream anchors crucial figures connecting consumers with products.These anchors can attract consumers with their appearance and charm,and use their expertise on live streaming platforms to guide consumers by recommending live content.They can also interact with their audiences and potentially influence them to purchase the recommended goods.It is evident that the attributes of anchors in live streaming rooms significantly impact consumers’online behavior.Therefore,researching how platform contextual factors regulate consumers’online behavior is of great practical significance.This study employs multilevel regression analysis to support its hypotheses using data.The findings indicate that contextual factors of the platform significantly influence online behavior,enhancing the positive relationship between user attachment and online activities.

Study of The Technical Index of Online Learning Behavior Analysis of Nursing Majors on The Superstar Platform Based on The Kirkpatrick Evaluation Model

Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.

Behavior analysis and formative assessments in online oral medicine education during the COVID-19 pandemic

BACKGROUND During the coronavirus disease 2019(COVID-19)pandemic,traditional teaching methods were disrupted and online teaching became a new topic in education reform and informatization.In this context,it is important to investigate the necessity and effectiveness of online teaching methods for medical students.This study explored stomatology education in China to evaluate the development and challenges facing the field using massive open online courses(MOOCs)for oral medicine education during the pandemic.AIM To investigate the current situation and challenges facing stomatology education in China,and to assess the necessity and effectiveness of online teaching methods among medical students.METHODS Online courses were developed and offered on personal computers and mobile terminals.Behavioral analysis and formative assessments were conducted to evaluate the learning status of students.RESULTS The results showed that most learners had already completed MOOCs and achieved better results.Course behavior analysis and student surveys indicated that students enjoyed the learning experience.However,the development of oral MOOCs during the COVID-19 pandemic faced significant challenges.CONCLUSION This study provides insights into the potential of using MOOCs to support online professional learning and future teaching innovation,but emphasizes the need for careful design and positive feedback to ensure their success.

An Empirical Study of the Influence of Online Learning Behaviors on Learning Outcomes in Blended Teaching Mode—Taking College English Listening as an Example

Blended teaching, which integrates the advantages of online and offline teaching, has become the main direction of higher education teaching reform. In the era of education big data, research on the online learners’ behavior based on data mining has attracted more and more attention from higher education researchers. However, in the field of foreign language teaching, research on the relationship between online learning behaviors and learning outcomes in the blended teaching mode is still at an early stage. Taking the course College English Listening in Zhejiang Yuexiu University (ZYU) as an example, this study conducted a comprehensive data analysis of online learning behaviors of 152 students of ZYU to explore the influence of online learning behaviors on learning outcomes in the blended teaching mode by utilizing Microsoft Excel and SPSS.20 statistic software. The result shows that the number of course login, the quantity and the quality of forum replies, the number of note submission, the quality of the notes, the average score of vocabulary tests, the number of the times of taking listening tests and the average score of listening tests are all significantly and positively correlated with students’ learning outcomes, while the study does not find a correlation between students’ learning outcomes and the number of the times of taking vocabulary tests, the total length of online learning and the length of video viewing. Based on the study results, implications are put forward to give reference for the teaching design and the management of the foreign language blended courses.

Analyzing Student Behavior in Online Programming Courses

Rather than maintaining the classic teaching approach, a growing number of schools use the blended learning system in higher education. The traditional method of teaching focuses on the result of students' progress. However, many student activities are recorded by an online programming learning platform at present. In this paper, we focus on student behavior when completing an online open-ended programming task. First, we conduct statistical analysis to examine student behavior on the basis of test times and completed time. By combining these two factors, we then classify student behavior into four types by using k-means algorithm. The results are useful for teachers to enhance their understanding of student learning and for students to know their learning style in depth. The findings are also valuable to re-design the learning platform.

Buying Behavior Under Coronavirus Disease(COVID-19)Pandemic Situation:A Online Perspective Case in Bangladeshi Shoppers

Coronavirus disease(COVID-19)is an highly infectious respiratory disease caused by a newly discovered coronavirus.Most people infected by the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment;a portion of infected people may die.Under coronavirous disease pandemic situation,human normal life,movement and business has been disturbed due to lockdown and closing of shopping malls and business centers in the city.Nowadays,e-commerce is a vigorous tool for diminishing streaming business processes,cycle time,organizational costs,stay at home,maintain social distancing,protect from virus,and enlightening associations with both shoppers and business partners.The research investigated the buying behavior of Bangladeshi shoppers under coronavirus disease(COVID-19)pandemic situation in case of online perspective.The research reconnoitered the impact of five aspects:health aspect,price aspect,product aspect,trust aspect,and place aspect on online buying behavior under coronavirus disease(COVID-19)pandemic situation in Bangladesh.Data were collected through a structured questionnaire by online survey method from 155 samples which encompass online shoppers in country.Simple random sampling technique were used.Data were analyzed using factor analysis,reliability analysis,and multiple regression analysis.Findings revealed that four out of five aspects:health aspect,price aspect,product aspect,and place aspect had a positive and significant influence on online buying behavior under coronavirus disease(COVID-19)pandemic situation in the perspective of Bangladesh.The assessment generates responsiveness among online practicing companies,researchers,managers,shoppers,and prospects online buyers.Online functioning businesses could be a successful leading aspects for explaining online buying behavior under coronavirus disease(COVID-19)pandemic situation in the context of Bangladesh.

How does an individual’s default behavior on an online peer-to-peer lending platform influence an observer’s default intention?

Previous studies indicate that individuals’default behaviors on online peer-to-peer(P2P)lending platforms greatly influence other borrowers’default intentions.However,the mechanism of this impact is not clear.Moreover,there is scarce research in regard to which factors influence the relationship between an individual’s default behavior and an observer’s default intention.These important questions are yet to be resolved;hence,we conducted two experiments using the scenario-based research method,focusing on Chinese online P2P lending platforms.Our results indicate that an individual’s default behavior can trigger an observer’s default intention as a result of the imperfect punitive measures as they currently exist on Chinese online P2P lending platforms.Both the observer’s moral disengagement level and pragmatic self-activation level serve as mediating variables.In situations where an observer knows an individual’s default behavior,the level of intimacy between the defaulter and observer positively affects the relationship between their default behavior and intention.The intimacy level also positively influences the relationship between the individual’s default behavior and the two mediator variables.Based on the findings,we provide management suggestions in the context of online P2P lending.Our study sets a foundation for future research to utilize other methods to extend the present research findings to other regions and domains.

How Perceived Benefits and Barriers Affect Millennial Professionals’ Online Security Behaviors

Over the past decade, there has been an increase in cybersecurity breaches through identity theft, hacking, phishing attacks, and the use of malware such as viruses, worms, or trojans. The breaches have triggered an increase in investment in information security in organizations. As technology continues to improve, the risks of having cybersecurity incidents also increase. Cybersecurity firms reported that in 2016, there were 1209 total breaches with 1.1 billion identities exposed. Most experts agree that human vulnerability is a significant factor in cybersecurity. Most issues related to advanced threats come from human nature and ignorance. For the study, the researcher examined the relationship between Millennial professionals’ perceptions of cybersecurity risks and users’ online security behaviors. The study focused on two elements of perception which are perceived benefits and perceived barriers. The researcher administered a survey to 109 participants randomly selected among Survey Monkey audience members. The Spearman’s correlation test performed supported the analysis of the strength of the relationship and the level of significance between each of the independent variables and the dependent variable. The results from the statistical test provided enough evidence to reject each of the null hypothesis tested in this study. There were significant correlations between each of the independent variables, Perceived Benefits (PBE) and Perceived Barriers (PBA) and the dependent variable Online Security Behaviors (OSB).

Research on Online Education Consumer Choice Behavior Path Based on Informatization

The application of information and communications technology(ICT)in the education industry is becoming more and more extensive,and online education realized through ICT is developing in full swing.The influence of ICT on online education consumer's choice behavior is the core issue of online education industry development research.The research on the interactive path and methods of information and online education consumer choice behavior is worth exploring and revealing.This study introduces the word-of-mouth factor as a new research variable under the framework of the Rational Choice Theory model(RCT)and the structural equation method to conduct empirical research and theoretical analysis to verify the validity of the hypothesis and model.The fifthGeneration mobile communication system(5 G)analyses the factors affecting online education consumer behavior choices based on the premise of ICT.Research on the path between ICT and choice behavior provides new ideas for online education consumer choice behavior research and ICT and content and provides a new scenario.This article is a cross-disciplinary research content in theory,and its innovation opens up a new path for the management of ICT research.The research results have innovative significance and value at both the theoretical and practical levels.

Effects of Negative Online Reviews on Consumers＇ Attitudes and Behavioral Intentionstoward Online Products

Online shopping has become an important new channel because of its rapid development and broad application of the Internettechnology. As consumer information search and release gradually shift from offline to online, online reviews of products havebecome more valuable. Research shows that most online shoppers view online reviews from product users before purchasing. Asone of the most important forms of spreading awareness, online product reviews has an increasing impact on customer purchasedecisions and has gradually become an urgent issue in network marketing research. This phenomenon impels businesses to realizethat online reviews significantly affect trading volume. Businesses have attempted to manipulate online reviews by providing asignificant number of positive comments that could lead to consumer confidence and purchase of products. Internet users inChina are more interested in reading negative comments compared with the rest of the global Internet users. Thus, the effects ofstructural characteristics of potential customers, negative attitudes, and behavioral intentions have not yet aroused global concernbecause this phenomenon has been limited to the local scale.Based on literature, the main objective of negative online reviews is the positioning of fashion products. The perception ofnegative online reviews, purchase attitudes, and behaviors are the factors considered in the present study. Negative online reviewsof clothing and accessories sold online and their influence on consumer purchase intention and attitudes are analyzed. The studyaims to confirm that negative online reviews have an effect on consumer purchase intention, attitudes, and behaviors. Moreover,buying attitudes influence behavior intention.

VisQAC: Visual Analytics for Online Q&A Communities

Online question and answer(Q&A)communities,which allow users to exchange knowledge by asking and answering questions,have become increasingly popular.As a result of user active participation,these communities store overwhelming volumes of information.However,existing related methods are unable to meet community operators’needs for analyzing multi-dimensional Q&A sequences and understanding user behavior.In this paper,collaborating with domain experts in online community,we present a system,VisQAC,which explores the patterns of Q&A sequence and user behavior.In the system,a novel visual design is proposed,which is combined with flexible mapping measures for analyzing critical characteristics of sequence data.Moreover,a timeline visualization method is designed to visualize data with categorical attributes and its correlation can be displayed flexibly by choosing time mode and time granularity.The usefulness and effectiveness of the system are demonstrated with several case studies of VisQAC with community operators based on the Zhihu dataset.Our evaluation shows that VisQAC is beneficial to the understanding of Q&A sequence and associated user behavior.

Empirical Effects of Online Retailing Recommendations

Online recommendation solves the current information overload problem in the online retailing businesses. Given relevant products by adopting recommendation algorithms, online shoppers can save time on searching and browsing for contents that they are interested in. Hence, in the increasing interests of online retailers, an empirical study was conducted to light the effectiveness of different entitled recommendations reflect on online shoppers. Working with a simulated online shopping establishment, the findings provide online retailers important guidelines regarding online customers’ behaviors.

Selling Luxury Brands in Online Private Sales Multibrand Retailers--An Exploratory Study of Consumers’Perspective

With Internet changing the luxury business landscape,new players have emerged such as the Online Private Sales Retailers(OPSRs).These offer online buyers with a choice of limited-time sales to help companies get rid of their overstocks.Luxury brands are no exception.No research has been conducted about how luxury consumers relate with such websites,hence this paper.In an exploratory fashion,interviews with luxury buyers who also buy online on OPSRs,are conducted to get insights on consumers’perceptions and luxury brand equity that selling through OPSRs may have.We find that appropriate product and brand help consumers forget that they are buying brands’unsold stocks,that transferring the luxury webmospheres would be positively perceived,that consumers from these websites are looking for benefits such as freedom of use and brand discovery,rather than personalized offers,that multiple discounts on several OPSRs may damage the luxury-perception of a brand,that the private sales members consider the service to be good enough for the demanded price,and that personalized invitations can help increase online consumers’feelings of desirability and exclusivity.The paper concludes with practical recommendations for both luxury companies and OPSRs.

Online Shopping: What Factors Determine Consumers to Buy?

This study analyzed factors influencing consumers in the process of making a decision in online shopping. The findings could inspire suggestions for online marketers in developing either media or infrastructures accordingly. The variables in the study involved product information, price, service, transaction safety, environment, age, gender, educational background, and income rate as independent variables, while the process of purchasing decision served as a dependent variable. Primary data were gathered in 10 locations within Jabodetabek areas involving 270 respondents which were analyzed using multiple regression analysis. The study revealed that price, information product, and service as significant variables influencing consumers in online shopping. Service became the most important factor for marketers to be considered as it emerged as the most dominant variable influencing the process of making a decision in online shopping.

TELF-PSPOC: Three-layer Ensemble Learning Framework for Predicting Student Performance of Online Courses

Virtual learning environment(VLE)MOOC provides large-scale data of resources,activities,and interactions within a course structure for predicting student performance.But it is challenging to extract and learn efficient features from student behaviors.In this paper,a three-layer ensemble learning framework for predicting student performance of online courses(TELF-PSPOC)at an early phase is proposed to analyze data collected from Open University Learning Analytics Dataset(OULAD).First,feature augmentation of student behavior is proposed to enrich current features of student performance,including pass rate and grades of all staged tests,daily clicks of online resources.Second,three-layer ensemble feature learning with heterogeneous classifiers(TEFL-HC)is proposed to benefit the integration of tree model and neural network.Compared with current two-layer ensemble learning,pretraining of features prevents overfitting while using nonlinear regression.The experiment shows that our TELF-PSPOC performs better than several baseline models.Besides,the relationship of the learning results and student behavior via VLE is further discovered.

快时尚服装基于Online定制设计意愿的影响因素分析

随着人们追求快时尚服饰的个性化、流行时尚化和平价化,基于互联网线上定制设计正成为当下热点。文中针对快时尚服装品类特点,以线上定制(Online-Tailored)设计为出发点,探讨快时尚服装消费者使用在线定制设计服务的影响因素和内在机理,为快时尚企业和电商提供相关的管理建议。研究中通过技术接受模型(TAM)为基础,以对在线定制设计有了解的学生人群为调研对象,利用SPSS对数据进行分析和模型检验,分析影响消费者对快时尚服装在线定制设计的接受态度。分析结果发现:成本感知、个性感知、速度感知、感知易用性以及流行时尚的影响是消费者接受快时尚服装在线定制设计的关键因素;同时心理态度起到中介作用,进而影响消费者购买在线定制设计快时尚服装的行为。

Analyzing Differences between Online Learner Groups during the COVID-19 Pandemic through K-Prototype Clustering

Online learning is a very important means of study, and has been adopted in many countries worldwide. However, only recently are researchers able to collect and analyze massive online learning datasets due to the COVID-19 epidemic. In this article, we analyze the difference between online learner groups by using an unsupervised machine learning technique, i.e., k-prototypes clustering. Specifically, we use questionnaires designed by domain experts to collect various online learning data, and investigate students’ online learning behavior and learning outcomes through analyzing the collected questionnaire data. Our analysis results suggest that students with better learning media generally have better online learning behavior and learning result than those with poor online learning media. In addition, both in economically developed or undeveloped regions, the number of students with better learning media is less than the number of students with poor learning media. Finally, the results presented here show that whether in an economically developed or an economically undeveloped region, the number of students who are enriched with learning media available is an important factor that affects online learning behavior and learning outcomes.

Positive study on the construction of consumption online platforms in colleges ＆ universities

Currently, online shopping has become an option in people＇s daily consumption, especially for large groups of college students. Based on the practical research of consumers groups of college students, this paper analyzes the affecting factors on consumers＇ satisfaction among groups of college students, and also tests the affecting factors. Thus, the authors give their proposals on how to build the consumer online platforms in colleges and universities, and the prospects forecast on the campus online market.

Online Shopping:Antecedents of Attitude,Intention and Use

Consumer behavior in electronic commerce has been the theme of hundreds of studies conducted by researchers of many nationalities in the past twenty years.The purpose of this study was to review and classify the concepts used in papers published between 2003 and 2014 to explain the consumer behavior in electronic commerce.A systematic search of the literature in nine databases was performed and 136 papers published in double-blind peer reviewed journals were selected.Reference models were prepared based on a classification of the concepts found.This article reports only the concepts that displayed statistical significance in the studies analyzed.Finally,we suggest new studies that can be conducted.