作者机构：
[Wu, Ruiping; Lu, Xinyuan] Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;[Lu, Xinyuan] Cent China Normal Univ, Hubei E Commerce Res Ctr, Wuhan, Hubei, Peoples R China.;[Wu, RP; Wu, Ruiping] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Wu, RP ] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
关键词：
Rural digitization;rural enterprises' resilience;rural labour outflow;labour resource misallocation;R11;R58;O16
摘要：
Considerable research has focused on the question of how to better utilize the rural digitization to enhance rural enterprises' resilience. However, there has not been a unified conclusion reached on the influence of rural digitization on rural enterprises' resilience. To reconcile the existing inconclusive evidence, this paper aims to investigate the nonlinear impact of rural digitization on rural enterprises' resilience. We also hypothesize the mediating role of rural labour outflow in the relationship and explore the moderating role of rural social organization. Following a mixed research method, we employ the U-test method and 205 listed Chinese rural enterprises as the research objects to test the hypotheses. We then use a qualitative case study to offer unique insights for explaining the underlying mechanisms behind the quantitative results. The findings show that rural digitization and rural enterprises' resilience have a U-shaped relationship, and labour outflow plays a nonlinear mediating role in it. Moreover, rural labour outflow and rural enterprises' resilience show an inverted U-shaped relationship, which regulated by rural social organization. Together, the mixed methods research offers nuanced and scientific advice for enhancing rural enterprises' resilience.
作者机构：
[Gao, Ying; Huang, Yanmei; Zhang, Qiang; Meng, Fanshuang] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Wang, Xiaoran; Zhang, Qiang; Tao, Wan] Anhui Polytech Univ, Sch Comp & Informat, Wuhu, Peoples R China.
通讯机构：
[Zhang, Q ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;Anhui Polytech Univ, Sch Comp & Informat, Wuhu, Peoples R China.
关键词：
Tang tomb murals;Ontology;Knowledge graphs;Digital humanities;Geographic information systems
摘要：
Purpose
Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.
Design/methodology/approach
Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.
Findings
The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.
Originality/value
This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.
摘要：
DIGITAL HEALTH, Volume 10, Issue , January-December 2024. <br/>ObjectivesCyberchondria is increasingly recognized as the dark side of digital health, given the pervasive use of the internet as a main source of health information in people's daily lives. While previous studies have identified many factors contributing to cyberchondria, there is a dearth of research on the impact of health-related advertisements. Therefore, this study adopts the stressor–strain–outcome (SSO) model to investigate how health-related advertising interference is directly and indirectly related to cyberchondria.MethodsTo empirically validate the proposed research model, we conducted an online survey with 437 internet users with medical information seeking experience in China. Structural equation modeling (SEM) was employed to analyze the survey data.ResultsOur findings revealed a positive, direct association between health-related advertising interference and cyberchondria. Meanwhile, advertising interference was positively related to both information overload and information irrelevance, with the former further predicting cyberchondria. Moreover, doctor–patient communication weakened the positive effect of information overload on cyberchondria.ConclusionsThe study not only theoretically contributes to the literature by theorizing the relationship between health-related advertising interference and cyberchondria but also practically underlines the pivotal role of effective doctor–patient communication in reducing the development of cyberchondria.
期刊：
Information Processing & Management,2024年61(3):103649 ISSN：0306-4573
通讯作者：
Chi, MM
作者机构：
[Xia, Lixin; Zhai, Shanshan] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Chi, Maomao; Chi, MM] China Univ Geosci, Sch Econ & Management, Wuhan 430078, Peoples R China.;[Chi, Maomao; Chi, MM] Wuhan Technol & Business Univ, Inst Digital Commerce, Wuhan 430065, Peoples R China.;[Li, Xuguang] Shandong Univ Technol, Sch Informat Management, Zibo 255000, Peoples R China.
通讯机构：
[Chi, MM ] C;China Univ Geosci, Sch Econ & Management, Wuhan 430078, Peoples R China.;Wuhan Technol & Business Univ, Inst Digital Commerce, Wuhan 430065, Peoples R China.
关键词：
Configuration perspective;National natural science foundation of China;Youth program;Library and information science
摘要：
While extensive research has delved into various facets of science funding outputs and the determinants of funding approval, prevailing methodologies predominantly rely on descriptive statistics or regression analyses. These approaches often miss a holistic view that integrates the interplay of multiple influential factors. In this study, we leverage the scientific research productivity model to introduce the Institution-Capability-Demographics framework, encompassing three pivotal dimensions: institutional characteristics, individual capabilities, and individual demographics. Adopting a configuration perspective, we scrutinize the synergistic effects of these dimensions on the time-to-win in science funding applications. Our empirical analysis draws from data of 72 young scholars affiliated with the Youth Program for Library and Information Science (LIS) of the NSFC, all of whom secured funding between 2003 and 2019. Through the fuzzy-set qualitative comparative analysis (fsQCA), this study delineates four distinct mechanisms that expedite the application process for the NSFC's Youth Program: demographic-capability-institution synergy, capability-centric balance, demographic-capability harmony, and capability-institution equilibrium. The findings elucidate the intricate interdependencies of factors influencing the time-to-win in science funding, offering valuable guidance for science fund managers and fostering the growth of emerging scholars.
摘要：
Users' search performance indicates the effectiveness and success with which users' information needs are met, which is calculated based on the relevance judgment by users themselves. This study proposed to explore the prediction of users' search performance in the context of cross-device search. A user experiment was performed to collect users' relevance judgments and search behaviors in cross-device search. Based on users' relevance judgments, users' search performance was evaluated by calculating the percentage of valid clicks, effective search time, nDCG@n, and satisfaction. A simple linear regression model was adopted to train the prediction model. The final results showed that a combination of users' search performance in pre-switch sessions and their search behavior in post-switch sessions can attain the best prediction accuracy. Important features to predict users' search performance in cross-device search shed light on improving search systems to aid users in completing the task efficiently.
作者：
Zhang, Min;Zhang, Dongxin;Zhang, Yin;Yeager, Kristin;Fields, Taylor N.
期刊：
Journal of Informetrics,2023年17(4) ISSN：1751-1577
通讯作者：
Zhang, Y
作者机构：
[Zhang, Min] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Zhang, Dongxin] Southwest Univ, Sch Comp & Informat Sci, Chongqing, Peoples R China.;[Zhang, Yin; Fields, Taylor N.; Zhang, Y] Kent State Univ, Sch Informat, Kent, OH 44242 USA.;[Yeager, Kristin] Kent State Univ, Univ Lib, Kent, OH USA.
通讯机构：
[Zhang, Y ] K;Kent State Univ, Sch Informat, Kent, OH 44242 USA.
摘要：
Influence plays a critical role in information communication, and the ubiquitous use of social media has made measuring influence on social media platforms a salient challenge. While previous studies have attempted to measure and investigate influence on Twitter, there is no consensus on its definition or relation to fundamental Twitter metrics. This study examined relationships between a composite influence measure of Twitter and fundamental social media metrics using a sample of tweets from a multi-year public campaign. Correlation analyses indicated that a user's number of followers had the strongest correlation with the composite measure. Principal components analysis was conducted for dimension reduction, and multiple regression analysis was performed using the resulting components. The findings revealed that a user's network was the most important predictor of the composite influence measure and that there was a negative relationship between campaign related activity and the composite measure. Implications of these findings are discussed. Overall, this study contributes to the understanding of and future efforts in the measurement of influence on social media.
作者：
Ye, Guanghui;Wang, Cancan;Wu, Chuan;Peng, Ze;Wei, Jinyu;...
期刊：
Journal of Informetrics,2023年17(3):101421 ISSN：1751-1577
通讯作者：
Wu, C
作者机构：
[Wu, Chuan; Peng, Ze; Wu, C; Tan, Qitao; Wu, Lanqi; Ye, Guanghui; Wei, Jinyu; Song, Xiaoying; Wang, Cancan] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
通讯机构：
[Wu, C ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
关键词：
Research front detection;Research grant information;Evolution analysis;Health informatics
摘要：
Identifying research fronts is an essential aspect of promoting scientific development. Many re-searchers choose their research directions and topics by analyzing their field's current research fronts. Many previous researchers have used academic papers or patents to identify research fronts; however, this is potentially outdated and reduces the prospective value of the research front detection. Considering this, this work proposes adapted indicators to conduct research front topic detection based on research grant data, which aims to identify research front topics and fore-cast trends using path analysis. First, research topics were identified using topic modeling, and then the mapping relations from topics to both fund projects and cross-domain categories were built. Then, research front topics were detected by multi-dimensional measurements, and the evo-lution of research topics was analyzed using topic evolution visualization to predict development trends. Finally, the Brillouin index was used to measure the cross-domain degree. Our method was evaluated using a dataset from the field of health informatics and was shown to be effective in research front identification. We found that the proposed adapted indicators were informative in identifying the evolutional trends in the health informatics field. In addition, research grants with higher cross-domain degrees are more likely to receive a high amount of funding.
摘要：
Accurate and effective container throughput forecasting plays an essential role in economic dispatch and port operations, especially in the complex and uncertain context of the global Covid-19 pandemic. In light of this, this research proposes an effective multi-step ahead forecasting model called EWT-TCN-KMSE. Specifically, we initially use the empirical wavelet transform (EWT) to decompose the original container throughput series into multiple components with varying frequencies. Subsequently, the state-of-the-art temporal convolutional network is utilized to predict the decomposed components individually, during which an improved loss function that combines mean square error (MSE) and kernel trick is employed. Eventually, the deduced prediction results can be obtained by integrating the predicted values of each component. In particular, this research introduces the MIMO (multi-input and multi-output) strategy to conduct multi-step ahead container throughput forecasting. Based on the experiments in Shanghai port and Ningbo-Zhoushan port, it can be found that the proposed model shows its superiority over benchmark models in terms of accuracy, stability, and significance in container throughput forecasting. Therefore, our proposed model can assist port operators in their daily management and decision making.
期刊：
Information Processing & Management,2023年60(4):103348 ISSN：0306-4573
通讯作者：
Duantengchuan Li<&wdkj&>Yan Zhang
作者机构：
[Li, Zhifei; Zhang, Yan] Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan 430062, Hubei, Peoples R China.;[Zhang, Qi] Cent China Normal Univ, Sch Informat Management, Wuhan 430072, Hubei, Peoples R China.;[Zhu, Fangfang] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Hubei, Peoples R China.;[Zheng, Chao; Li, Duantengchuan] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Hubei, Peoples R China.
通讯机构：
[Duantengchuan Li; Yan Zhang] S;School of Computer Science, Wuhan University, Wuhan, Hubei 430072, China<&wdkj&>School of Computer Science and Information Engineering, Hubei University, Wuhan, Hubei 430062, China
作者机构：
[Xiong, Huixiang; Ye, Jiaxin; Meng, Xuan] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Guo, Jinpeng] Cent China Normal Univ, Sch Polit & Int Studies, Wuhan, Peoples R China.
关键词：
Group recommendation;Comment function classification;Comment role classification;Book
摘要：
Purpose
The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.
Design/methodology/approach
The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.
Findings
Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.
Originality/value
Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.
期刊：
DIGITAL HEALTH,2023年9:20552076231208559 ISSN：2055-2076
通讯作者：
Cao, GH
作者机构：
[Gong, Hongcun; Deng, Sanhong; Wang, Hao] Nanjing Univ, Sch Informat Management, Nanjing, Peoples R China.;[Gong, Hongcun; Deng, Sanhong; Wang, Hao] Nanjing Univ, Int Joint Informat Lab, Nanjing, Peoples R China.;[Cao, Gaohui] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Cao, Gaohui; Cao, GH] Cent China Normal Univ, Sch Informat Management, 152 Luoyu Rd, Wuhan, Hubei, Peoples R China.
通讯机构：
[Cao, GH ] C;Cent China Normal Univ, Sch Informat Management, 152 Luoyu Rd, Wuhan, Hubei, Peoples R China.
关键词：
ABC theory of emotion;Health anxiety;health information-seeking behavior;rural population
摘要：
OBJECTIVE: The aim of the current study was to explore the relationship between online and offline health information-seeking behaviors, as antecedents and consequences, and health anxiety and related belief factors in rural residents. METHODS: Based on the ABC theory of emotions (ABC model), this study developed two theoretical models of the association between health anxiety and health information-seeking behavior: Placing health information-seeking behavior (both online and offline) as an outcome and antecedent, respectively, and setting three belief factors of the perceived health threat, intolerance of uncertainty, and catastrophic misinterpretations. We collected 730 self-reported data points from 20 June to 5 July 2022 for rural residents in China and empirically tested the research model and hypotheses using partial least squares-based structural equation modeling. RESULTS: The perceived health threat and intolerance of uncertainty are significant motivators of health anxiety, and health anxiety has a direct beneficial effect on both online and offline health information-seeking behaviors. Health anxiety is influenced either directly or indirectly by catastrophic misinterpretations resulting from online health information-seeking, while offline health information-seeking behavior does not contribute as strongly to health anxiety directly but mainly reinforces it through the mediating influence of catastrophic misinterpretations. CONCLUSIONS: Rural residents' health anxiety promotes their online and offline health information behaviors. And both their online and offline health information-seeking behaviors may promote health anxiety directly and through catastrophic misinterpretations. Comparing the two, online health information-seeking behaviors primarily exacerbate health anxiety through direct effects, whereas offline health information-seeking behaviors primarily affect health anxiety through catastrophic misinterpretations. We provide suggested guidelines for alleviating health anxiety and regulating health information behaviors among rural residents.
期刊：
Transportmetrica A: Transport Science,2023年19(2):Article: 1980131 ISSN：2324-9935
通讯作者：
Chen, Anthony
作者机构：
[Wang, Guangchao; Tong, Kebo] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Chen, Anthony] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Peoples R China.;[Qi, Hang] Hubei Univ Econ, Inst Adv Studies Finance & Econ, Wuhan 430000, Peoples R China.;[Xu, Xiangdong] Tongji Univ, Key Lab Rd & Traff Engn, Shanghai 201804, Peoples R China.;[Ma, Shoufeng] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China.
通讯机构：
[Chen, Anthony] H;Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hung Hom, Kowloon, Hong Kong, Peoples R China.
关键词：
Stochastic user equilibrium;least perceived travel cost;Weibit model;location parameter;relative variability
摘要：
This study investigates the impacts of the least perceived travel cost on the stochastic user equilibrium (SUE) problem. The Weibit SUE models are considered since they have a location parameter that naturally capture the least perceived travel cost. Considering a positive location parameter enhances the behavioral reality by attaching a positive lower-bound to the perceived travel cost distributions. It reduces the perception variances route-specifically and causes route-specific coefficients of variation (CVs). The CVs reduce proportionally slower for shorter routes, thus contributing to resolving the scale insensitivity issue in the Weibit SUE models. In the meantime, the route-specific CVs cause better discrimination between short and long routes in terms of relative variability; more travelers shift to the shortest route between each origin-destination pair. Numerical results confirm the analytical results regarding the effects of the least perceived travel costs and demonstrate the efficiency and robustness of the proposed solution algorithm.
期刊：
Information Processing & Management,2023年60(4):103350 ISSN：0306-4573
通讯作者：
Li, DTC;Shi, FB
作者机构：
[Zheng, Chao; Wang, Jian; Li, Duantengchuan; Wang, Jingxiong; Li, Bing] Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China.;[Zhang, Qi] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Shi, Fobo; Shi, FB] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Cai, Yuefeng] ZTE Corp, Wuhan 430223, Peoples R China.;[Wang, Xiaoguang; Zhang, Zhen] Wuhan Univ, Sch Informat Management, Wuhan, Peoples R China.
通讯机构：
[Li, DTC ] W;[Shi, FB ] C;Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China.;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
摘要：
Knowledge graphs are sizeable graph-structured knowledge with both abstract and concrete concepts in the form of entities and relations. Recently, convolutional neural networks have achieved outstanding results for more expressive representations of knowledge graphs. However, existing deep learning-based models exploit semantic information from single-level feature interaction, potentially limiting expressiveness. We propose a knowledge graph embedding model with an attention-based high-low level features interaction convolutional network called ConvHLE to alleviate this issue. This model effectively harvests richer semantic information and generates more expressive representations. Concretely, the multilayer convolutional neural network is utilized to fuse high-low level features. Then, features in fused feature maps interact with other informative neighbors through the criss-cross attention mechanism, which expands the receptive fields and boosts the quality of interactions. Finally, a plausibility score function is proposed for the evaluation of our model. The performance of ConvHLE is experimentally investigated on six benchmark datasets with individual characteristics. Extensive experimental results prove that ConvHLE learns more expressive and discriminative feature representations and has outperformed other state-of-the-art baselines over most metrics when addressing link prediction tasks. Comparing MRR and Hits@1 on FB15K-237, our model outperforms the baseline ConvE by 13.5% and 16.0%, respectively.
期刊：
Technological and Economic Development of Economy,2023年29(6):1728-1752 ISSN：2029-4913
通讯作者：
Gao, MY
作者机构：
[Xiao, Qinzi; Chen, Lin; Jiang, Juncheng] Wuhan Inst Technol, Sch Management, Wuhan, Peoples R China.;[Gao, Mingyun] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
通讯机构：
[Gao, MY ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
关键词：
digital economy evaluation;grey relational degree;fuzzy integral;grey information coverage;normal cloud matrix
摘要：
This study aims to reflect the grey information coverage and complex interactions effect in digital economy development. Therefore, a multi-attribute decision making method based on the grey interaction relational degree of the normal cloud matrix (GIRD-NCM) model is pro-posed. First, the original information coverage grey numbers are transformed into normal cloud matrixes, and then a novel Minkowski distance between normal clouds is proposed by using different information principles. Second, the GIRD-NCM model is established according to the Choquet fuzzy integral and grey relational degree. Finally, the dynamic comprehensive evaluation of digital economy development in China from 2013 to 2020 is conducted. The implementation, availability, and feasibility of the GIRD-NCM model are verified by comparative analysis with three existing evaluation models. The empirical findings reveal a stable growth trend in China's digital economy, with an annual growth rate of 7.87%, however, there are notable regional devel-opment disparities. The change in interaction degree has no effect on the rankings of provinces that are in the lead or have a moderately high level of digital economy development, but has a positive and negative impact on the rankings of these provinces with high and low levels of digital economy development, respectively.
期刊：
Journal of Information Science,2023年 ISSN：0165-5515
通讯作者：
Wu, D;Liu, XZ
作者机构：
[Dong, Jing] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Kang, Yangyang; Sun, Changlong] Alibaba Grp, Shanghai, Peoples R China.;[Liu, Jiawei; Wu, Dan] Wuhan Univ, Sch Informat Management, Wuhan, Peoples R China.;[Fan, Shu] Sichuan Univ, Sch Publ Adm, Sichuan, Peoples R China.;[Jin, Huchong] Indiana Univ, Luddy Sch Informat Comp & Engn, Bloomington, IN USA.
通讯机构：
[Wu, D ] W;[Liu, XZ ] I;Wuhan Univ, Sch Informat Management, 299 Bayi Rd, Wuhan 430072, Hubei, Peoples R China.;Indiana Univ Bloomington, 107 S Indiana Ave, Bloomington, IN 47405 USA.
关键词：
Active learning;annotation cost;crowdsourcing;ground truth labels;human annotations;human-centred design
摘要：
Active learning in machine learning is an effective approach to reducing the cost of human efforts for generating labels. The iterative process of active learning involves a human annotation step, during which crowdsourcing could be leveraged. It is essential for organisations adopting the active learning method to obtain a high model performance. This study aims to identify effective crowdsourcing interaction designs to promote the quality of human annotations and therefore the natural language processing (NLP)-based machine learning model performance. Specifically, the study experimented with four human-centred design techniques: highlight, guidelines, validation and text amount. Based on different combinations of the four design elements, the study developed 15 different annotation interfaces and recruited crowd workers to annotate texts with these interfaces. Annotated data under different designs were used separately to iteratively train a machine learning model. The results show that the design techniques of highlight and guideline play an essential role in improving the quality of human labels and therefore the performance of active learning models, while the impact of validation and text amount on model performance can be either positive in some cases or negative in other cases. The 'simple' designs (i.e. D1, D2, D7 and D14) with a few design techniques contribute to the top performance of models. The results provide practical implications to inspire the design of a crowdsourcing labelling system used for active learning.
期刊：
JOURNAL OF DOCUMENTATION,2023年79(2):442-467 ISSN：0022-0418
作者机构：
[Li, Xuguang; Zhang, Yao] Nankai Univ, Dept Informat Resources Management, Tianjin, Peoples R China.;[Li, Xuguang] Shandong Univ Technol, Inst Informat Management, Zibo, Peoples R China.;[Luo, Xiaoying] Lib Shenzhen MSU BIT Univ, Shenzhen, Peoples R China.;[Cox, Andrew] Univ Sheffield, Informat Sch, Sheffield, S Yorkshire, England.;[Lu, Yingying] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
关键词：
University students;Mental health information;Online information resources;Mental well-being;Information need
摘要：
Purpose
This research aims to explore the nature of Chinese students' mental health information needs and to identify the online resources they use to meet those needs.
Design/methodology/approach
Data was collected from three Chinese research-oriented universities using semi-structured interviews and a survey. Twenty-five university students with varied backgrounds were selected for semi-structured interviews to explore the triggers and nature of their needs. Then, printed and online questionnaires were distributed to undergraduate and postgraduate students and 541 valid responses were processed for descriptive statistical analysis and variance analysis.
Findings
The following findings were incurred. First, the triggers of university students' mental health information needs mainly are mental health being in the news, personal interest in gaining mental health knowledge, mental health issues, required formal learning and preparation for mental health counselling. Second, eleven types of information are used, with an emphasis on employment pressure, study stress and self-understanding. Third, mental health information needs differ with mental health status and some social-demographic factors (including gender, urban or rural origin and educational stage). Fourth, information needs can be characterized as dynamic; complex and diverse but concentrated on a few types; ambiguous and hard for participants to define; private; stigmatized; self-dependent and substitutable. Fifth, Internet sources used to meet such needs are mainly search engines, Question and Answer platforms, public social media platforms. Finally, a model of mental health information needs was built based on the above findings to map the whole process from what triggers a need, to the content and characteristics of information need, and online resources used to meet those needs.
Practical implications
The paper provides suggestions for university mental health services in developing more tailored knowledge contents via effective delivery methods to meet diverse needs of student groups.
Originality/value
This research is novel in using empirical data to build a holistic model that captures the context and the nature of mental health information needs of university students.
