The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking Guilin University of Electronic Technology as an Example

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in China.The study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective students.By employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at Guilin University of Electronic Technology.The aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective students.Social media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in China.Students tend to obtain school information through social media platforms and use this information as an important reference in their decision-making process.Higher education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive information.It is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective students.Simultaneously,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student enrollment.This study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making process.This has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

Exploration and Practice of Big Data Introductory Courses for Big Data Management and Application Majors

As an introductory course for the emerging major of big data management and application,“Introduction to Big Data”has not yet formed a curriculum standard and implementation plan that is widely accepted and used by everyone.To this end,we discuss some of our explorations and attempts in the construction and teaching process of big data courses for the major of big data management and application from the perspective of course planning,course implementation,and course summary.After interviews with students and feedback from questionnaires,students are highly satisfied with some of the teaching measures and programs currently adopted.

Integrating Multiple Linear Regression and Infectious Disease Models for Predicting Information Dissemination in Social Networks

Social network is the mainstream medium of current information dissemination,and it is particularly important to accurately predict its propagation law.In this paper,we introduce a social network propagation model integrating multiple linear regression and infectious disease model.Firstly,we proposed the features that affect social network communication from three dimensions.Then,we predicted the node influence via multiple linear regression.Lastly,we used the node influence as the state transition of the infectious disease model to predict the trend of information dissemination in social networks.The experimental results on a real social network dataset showed that the prediction results of the model are consistent with the actual information dissemination trends.

Prediction of Online Consumers’Repeat Purchase Behavior via BERT-MLP Model

It is an effective means for merchants to carry out precision marketing and improve ROI by using historical user behavior data obtained from promotional activities in order to build a model to predict the repeat purchase behavior of users after promotional activities.Most of the existing prediction models are supervised learning,which does not work well with a small amount of labeled data.This paper proposes a BERT-MLP prediction model that uses“large-scale data unsupervised pre-training+small amount of labeled data fine-tuning.”The experimental results on Alibaba real dataset show that the accuracy of the BERT-MLP model is better than the baseline model.

A customized zeolitic imidazolate framework enabling bionic preconcentration of ultralow CO_(2)

Advancing our understanding of global climate,particularly in polar regions,requires accurate detection of carbon dioxide(CO_(2))in ice cores and deep sea environments.However,detecting trace levels of CO_(2)in these areas presents significant challenges.We introduce a novel preconcentration approach using functionalized zeolitic imidazolate framework,ZIF-8(CN),for the detection of ultra-low CO_(2).ZIF-8(CN)has small pores(4.4■and cyano groups(–CN),enabling highly selective adsorption of CO_(2)(36.2 cm^(3)g^(−1))over N_(2)(1.6 cm^(3)g^(−1))at 298 K.The mechanism involves unique–CN···CO_(2)···–CN interactions within the pore structure.When cast into a film on an aluminum substrate,ZIF-8(CN)demonstrates exceptional CO_(2)preconcentration capability(1 ppm in N_(2))with an extraordinary preconcentration factor of 748,outperforming traditional ZIF and zeolite materials.Additionally,a ZIF-8(CN)preconcentrator is designed and fabricated with bionic gas flow of fractal structure which optimizes the gas-film contact,and thus its performance is further improved by 115%.

Synthetic subnanochannels in porous aromatic frameworks accelerate selective water permeation in membrane desalination

Creation of freeways in a membrane accelerates water transport for efficient desalination;however,the synthesis of target membrane materials is very challenging.In the present study,the molecular-design strategy is developed for the synthesis of porous aromatic framework(PAF)membranes with rigid and open networks to regulate water transport.Nitrile-based monomers in triangle shape are designed for the construction of PAF-98 and its sister frameworks,and these PAF membranes are formed through trifluoromethanesulfonic acid catalysis.The rigidity and geometry of the monomers endow PAFs with unique structures of connected pores with edging size(4.5–6.7Å)between water(2.8Å)and hydrated sodium molecules(7.2Å),enabling effective differentiation of water and salt.The fabricated membranes with high flexibility and continuity are ideal for water desalination,and reverse osmosis experiments demonstrate that the three PAF membranes are selective for permeation of water molecules over hydrated sodium cations.Unprecedented water flux of 547.1 L m^(-2) h^(-1) and high rejection degree of 90%are obtained on a representative membrane of PAF-98-E;and the desalination performance is superior to currently available membrane materials.Furthermore,PAF-98-E membrane is capable of rejecting various cations with high efficiency in real seawater,holding great promise in practical water desalination application.