Optimization and Innovation of the Operation Model of Mobile Social E-commerce under AI Empowerment:Taking the Female Community Platform“Little Red Book”as an Example

This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.

Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning

With the continuous development of artificial intelligence technology,its application field has gradually expanded.To further apply the deep reinforcement learning technology to the field of dynamic pricing,we build an intelligent dynamic pricing system,introduce the reinforcement learning technology related to dynamic pricing,and introduce existing research on the number of suppliers(single supplier and multiple suppliers),environmental models,and selection algorithms.A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions.The first step is to analyze the pricing strategies of e-commerce platforms in mature markets,analyze the optimal pricing and profits of various enterprises under different strategy combinations,compare different market equilibriums and solve the Nash equilibrium.Then,assuming that all consumers are naive in the market,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations,the subgame refined Nash equilibrium is solved.Finally,assuming that the market includes all experienced consumers,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.

A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT

In the era of big data,E-commerce plays an increasingly important role,and steel E-commerce certainly occupies a positive position.However,it is very difficult to choose satisfactory steel raw materials from diverse steel commodities online on steel E-commerce platforms in the purchase of staffs.In order to improve the efficiency of purchasers searching for commodities on the steel E-commerce platforms,we propose a novel deep learning-based loss function for named entity recognition(NER).Considering the impacts of small sample and imbalanced data,in our NER scheme,the focal loss,the label smoothing,and the cross entropy are incorporated into a lite bidirectional encoder representations from transformers(BERT)model to avoid the over-fitting.Moreover,through the analysis of different classic annotation techniques used to tag data,an ideal one is chosen for the training model in our proposed scheme.Experiments are conducted on Chinese steel E-commerce datasets.The experimental results show that the training time of a lite BERT(ALBERT)-based method is much shorter than that of BERT-based models,while achieving the similar computational performance in terms of metrics precision,recall,and F1 with BERT-based models.Meanwhile,our proposed approach performs much better than that of combining Word2Vec,bidirectional long short-term memory(Bi-LSTM),and conditional random field(CRF)models,in consideration of training time and F1.

Socialization, Traffic Distribution and E-Commerce Trends:An Interpretation of the “Pinduoduo” Phenomenon

The article takes China’s e-commerce as the research object.Starting from the macro level of e-commerce development and taking the rapid rise of“Pinduoduo”as an example,it discusses the“traffic dilemma”and its influence in the traditional e-commerce platform.This discovers the internal mechanism of mobile e-commerce to solve the problem of traffic distribution mechanism by socialization.After that,this study compares the difference between traditional e-commerce and social-commerce systematically,and concludes that traditional e-commerce platform is a necessary process of the development of social-commerce.Socialization is an important trend of the development of traditional e-commerce and social-commerce will promote the realization of C2B model.

Effects of E-Commerce Platforms on Firm Export——Evidence from China’s Industrial Enterprises

With deepening digital technology applications in international trade, e-commerce platforms have become a major avenue for firm export. Based on a multicountry, multi-product heterogeneous firms trade theory model, this paper investigates the firm export effects of e-commerce platforms, and empirically tests the inferences from the model using data from Alibaba China Station, China industrial enterprises data, and China customs data from 2000 to 2009. Our estimation result shows that overall, e-commerce platforms significantly increase firm export probability and volume;e-commerce platforms enable firms to export products of different types to more countries by reducing the cost of information and export markets threshold while raising trade efficiency. Further analysis of enterprise heterogeneity reveals that SMEs, firms in China's eastern region, and general exporters benefit more from e-commerce platforms than other types of firms do.

Application of the E-commerce Platform in the International Trade

E-commerce is a new consumption mode, which develops rapidly and is welcomed by consumers. It also plays an important role in promoting the international trade. Through this analysis, we can understand that the influence of the e-commerce on the international market has both positive and negative aspects. We need to be aware of our shortcomings, understand the gap between them and the developed countries, and formulate the relevant policies. Let China's e-commerce continue to improve and innovate in the international trade, and find a suitable strategy for its own development. Relevant Chinese departments should actively and effectively participate in the construction of e-commerce. On the one hand, they can stabilize the status of e-commerce in the international trade, and on the other hand, they can expand the consumer groups and make the electronic goods better.

Research on Communication Mechanism and Effect of Social E-Commerce in China

With the popularization of the Internet and the change of residents' consumption concept, e-commerce brings convenience to people's life and work, and network consumption has become a mainstream consumption mode. With the continuous expansion of e-commerce business, social network has become the main mode of Internet economic development with a rapid trend. Social network has abundant customer resources, which continuously influences people's life and work style. The advent of network economy era has an important impact on the development of global e-commerce industry. As a product of the development of the network economy era, electronic commerce, with its unique advantages, has played a decisive role in the form of global economic growth and commodity trading mode. In this paper, through the perspective of social network, the domestic e-commerce industry was actively explored, hoping to provide a theoretical reference for the rapid development of related industries in China.

Assumption of E-commerce Platform of Agricultural Products Based on F2C2B Mode

This paper proposes the assumption of E-commerce platform of the agricultural products based on the F2C2B mode. The whole e-commerce model is guided by the idea of the supply chain management from the perspective of the modern system, and the e-commerce integration model from customer to supplier is implemented, and the whole is optimized. E-commerce to cloud computing as the basic environment, the construction of public cloud services and private cloud resources, based on public cloud to the SaaS way to provide services to customers, focus on business search and business collaboration, make full use of the lnternet, modern communications technology to provide the real- service. The development of agricultural economy, no longer depends only on the number of some traditional agricultural resources, but also depends on the modern technology, information access and use. Through the development of basic network technology, by virtue of some modern electronic information technology and some other means that can improve the intelligence of agricultural use of the information resources, the proposed model provides the new methodology of the solution.

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.

Thalassemia Screening by Sentiment Analysis on Social Media Platform Twitter

Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival.Therefore,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia carriers.Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health affairs.Exploring individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the public.An effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main tools.VADER represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social media.The contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform Twitter.In this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,respectively.The tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.

Does communication increase investors’trading frequency?Evidence from a Chinese social trading platform

This study examines the impact of communication on investors’trading frequency based on a unique dataset drawn from a Chinese social trading platform.We find robust evidence that real-account portfolio owners on the platform trade more frequently under the influence of the comments posted by their leaders(the owners of portfolios they have followed).Moreover,portfolio owners are more sensitive to the quantity than to the tone of leaders’comments.Finally,both trading frequency and leaders’comments negatively impact portfolio owners’future performance.Our find-ings support the notion that social interaction promotes active investment strategies.

Research on the Development Model ofE - commerce Finance： A Case Study of the Cross-border Cooperation in Finance between banks and E-commerce companies

This purpose of this article is to provide an overview of the research situation and the development model of the E-commerce finance. This article takes the cross-border cooperation in finance between banks and E-commerce companies. This paper introduces three development models of E-commerce finance. Banks set up their own E-commerce platform. The banks take advantage of E-commerce platform. The E-commerce companies run financial business. The theoretical findings reported in this paper pave the way for embarking on the promising and relevant future research.

Foreign E-commerce Practitioners in “Taobao Village”: Isolation and Integration

This research mainly analyzes the actual situation of social integration of migrant E-commerce practitioners in Xintang Town of Guangdong Province through field survey.According to the survey,the overall level of social integration is relatively low,and there are three isolation barriers,namely time,space and psychology.Regarding the influencing factors of social integration level,it is concluded through the principal component analysis that five main factors impacting the social integration of migrant E-commerce practitioners are life factor,business factor,housing factor,social factor and individual factor.By establish a multiple logistic analysis model,it is found that type of friends,interest protection and frequency of recreational activities would impact the social integration of migrant E-commerce practitioners most significantly among all factors.

The Development and Operation Mechanism of the Colleges’E-class Network Ideological and Political Education Platform——Based on post-95 college students’social behavior characteristics

Based on the investigation and analysis of the social behavior characteristics of post-95undergraduates, this paper puts forward the principle of sharing and building e-class platform and analyzes thedevelopment of the functions of the four platforms such as the teacher-student service system, instant interactionsystem, SNS community system and vertical segmental pushing system and the realization of the function of modularoperation. Finally, in order to ensure the stable operation of the E-class platform, four measures are put forward suchas the systematic construction of the system, the innovation of team work, the assessment of key performances and thecomprehensive guarantee, thus providing an external guarantee for the stable operation of the E-class platform.

Leveling the Playing Field China’s first e-commerce law takes effect in an effort to regulate the industry

Gao Difan,27,was overjoyed with the Givenchy lipstick she bought herself as a Christmas gift via a daigou.on Taobao,one of the most famous e-commerce platforms in China.A daigou is the name given to an intermediary who travels or lives abroad and buys products on behalf of people in China.

Social Rights and Work on Digital Platforms in Brazil:The Case of“Breque dos Apps”

The movement known as“Breque dos Apps”was a social movement of a striker nature,which took place in Brazil in July 2020.Such movement was organized by workers which provided services to delivery apps(like iFood,Loggi,Uber Eats and Rappi).They demanded better working conditions and social protection measures,since they were out of the protection of the Brazilian legal system.The reason for this lies in the fact that there is a debate about the classification of these workers-the maximum expression of the gig economy-as employees under Brazilian legislation.As a result,and with the exponential growth in the use of these applications due to the Covid-19 pandemic,thousands of workers were left on the fringes of any social protection.This study aims to analyze the aforementioned movement and its demands within the paradigm of social rights,especially the ones regarding collective representation,which are guaranteed by the Brazilian Constitution.In terms of methodology,the content analysis method will be applied,considering that the established objective presupposes the study of theoretical and legal texts that allow the structuring of concepts applicable to the theme.The research technique to be adopted will be the analysis of indirect documentation,that is,literature review,to be carried out through bibliographic and documentary research,focused on literature and legal texts related to the topic.

Cyber Development of Government Service Platform in Social Public Administration

The cyber development of government service platform is just to integrate all the superiorities of the government to strengthen its roles such as service,performance and function to drive the social development actively.Hence,the social public administration will take this opportunity to optimize the cyber information service platform to make the civic administration oriented to the social development to maximize its functions of organization,coordination and service to protrude the ascendancy of the web era so as to lay a solid foundation for the leap development of the public administration.

Digital Marketing and B2B Cross-Border E-Commerce: A Case Study of Alibaba International Station in China

The rapid development of the“Internet+”has ushered in a new era of global digital technology innovation.Concurrent with the deepening trends of economic globalization and integration,international trade is progressively undergoing extensive digitization,with cross-border e-commerce emerging as a significant manifestation of this transformation.Within this landscape,the cross-border e-commerce B2B platform is anticipated to become a pivotal driver for China’s cross-border trade growth,representing a strategic opportunity for trade transformation.This paper provides a comprehensive examination of the concepts,characteristics,and development status of cross-border e-commerce and B2B platforms,considering both global and Chinese perspectives.Focusing on a prominent case study,Alibaba International Station,a B2B cross-border e-commerce platform,the paper delves into its business model and core competencies,offering a thorough analysis of its role in the intricacies of international e-commerce and its contribution to the field.Drawing on insights gained,the paper concludes by presenting targeted recommendations from both the platform and government perspectives.These suggestions are informed by a nuanced understanding of the development opportunities and challenges facing China’s cross-border e-commerce B2B platforms.