Purpose： This study investigates how online user intention in searching health information is affected by problematic situations.Design/methodology/approach： Based on the Theory of Reasoned Action, the Technology Ac...Purpose： This study investigates how online user intention in searching health information is affected by problematic situations.Design/methodology/approach： Based on the Theory of Reasoned Action, the Technology Acceptance Model, and Sense-making theory, we propose two dimensions of problematic situations： urgency and severity of health issues being searched online. Data were collected through a questionnaire survey among 214 Wuhan University students and analyzed using hierarchical regression analysis.Findings： Perceived usefulness, perceived ease of use, and subjective norm can influence user intention to seek health information online. The urgency of problematic situations has a negative moderating effect on the relationship between perceived ease of use and user intention and the relationship between subjective norm and user intention. The severity of problematic situations has a negative moderating effect on the relationship between subjective norm and user intention.Research limitations： The respondents of the survey are limited to students in one Chinese university, so whether this study＇s results can be applied to another population or not remains to be verified. In addition, only two dimensions of problematic situations are considered in this study. Practical implications： The paper puts forward the moderating effect of problematic situations and verifies it, which is the compensation for online health information-seeking behavior research. Besides, our analyses have implications for professional design of health care systems and related consumer information searches, and improve their performance. Originality/value： Previous work has reported the effects of problematic situation on user intention to seek health information online, ignoring its influence on other factors. This empirical study extends that work to identify the influence of problematic situation when seeking intention-behavior data in two dimensions, urgency and severity.展开更多
Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to i...Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(about:blank Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.展开更多
Purpose: Taking Zhihu as the object for a case study, we intend to analyze the key factors that have affected users on adopting answers in social Q&A(SQA) websites.Design/methodology/approach: With information ado...Purpose: Taking Zhihu as the object for a case study, we intend to analyze the key factors that have affected users on adopting answers in social Q&A(SQA) websites.Design/methodology/approach: With information adoption model(IAM) as the theoretical foundation and widely accepted evaluation criteria for answer quality in SQA sites as variables, we constructed a factor model that has influenced SQA community users to adopt offered answers. With the partial least squares(PLS) technique, our model was then empirically tested through a sample of 311 Zhihu users.Findings: Our results showed that answer usefulness is the most effective variable, and answer interactivity and answer entertainment both have positive and significant impacts on users’ attitude to adopt answers in an SQA community. Except for novelty, other three components of answer quality, i.e. knowledge, reliability, and solution to the problem have all significant effect on answer usefulness.Research limitations: First, due to the limited sample size, it is still questionable if our research results based on Zhihu could be applied to other SQA communities. Second, our questionnaires were mainly designed to investigate how users felt about the answers in an SQA site, but did not differentiate the content of the answer itself.Practical implications: As a three-year-old SQA platform, Zhihu has developed very quickly with its high-quality answers and public intellectual users, and has been regarded as one of the representatives of fast emerging Chinese SQA communities in recent years. Our studycould help shed light on users’ information sharing and knowledge adoption behaviors in a Chinese SQA site, such as Zhihu. Originality/value: Compared with previous studies on answer quality assessments in SQA sites and on information adoption model, to the best of our knowledge, this is one of the pioneer studies which combined answer qualities with users’ intention of adopting SQA answers. Our study on user answer adoption in Zhihu community could further develop the theory of IAM. This study showed that answer usefulness is the most important motivation of Zhihu users in the process of adopting answers.展开更多
Purpose： We conducted an empirical study to find out the role of demographic variables in affecting information sharing behaviors of college student users of WeChat.Design/methodology/approach： A questionnaire surve...Purpose： We conducted an empirical study to find out the role of demographic variables in affecting information sharing behaviors of college student users of WeChat.Design/methodology/approach： A questionnaire survey was carried out to investigate the relationship between demographic variables （gender, grade level, dating status, and singleparent family background） and information sharing behaviors of WeChat users. The participants were college students and a total of 255 valid questionnaires were collected. Data was analyzed using descriptive statistics and multiple regression analysis.Findings： Grade level and single-parent family background were found to be significantly correlated with information sharing behaviors whereas no effect of gender was found on information sharing behaviors. Dating status had no significant impact on user browsing behavior, but was related to users＇ publishing posts and posting replies.Implications： The study will help understand individual differences in information sharing among WeChat users.Limitations： First, the relatively small sample size is a limitation in exploring the effects of demographic variables on user information sharing behaviors. Second, this study only used questionnaire surveys to collect data and more research methods such as interviews should be adopted to improve the accuracy of the study results.Originality/value： This paper is one of the first studies to explore the relationship between demographic variables and user information sharing behaviors on WeChat.展开更多
Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which inf...Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.展开更多
ChatGPT changes the way of knowledge production and information space structure of human society.In the healthcare industry,ChatGPT's powerful question-and-answer capability will drive its application in automated...ChatGPT changes the way of knowledge production and information space structure of human society.In the healthcare industry,ChatGPT's powerful question-and-answer capability will drive its application in automated question answering in online healthcare communities.However,because ChatGPT answers are limited by factors such as the quality of data sets,their authority and accuracy cannot be guaranteed,and they are prone to misdiagnosis and damage to life and health.Therefore,the identification of ChatGPT answers in online medical communities with physician answers is crucial.In this paper,we collected medical question-answering data generated by the Haodafu platform and ChatGPT,respectively,constructed feature vectors from semantic features,syntactic features,and the fusion of both,and combined different feature vectors with XGBoost models to construct BERT-XGBoost,POS-XGBoost and Merge-XGBoost models for identifying ChatGPT answers and physician answers in online medical communities.The three models achieved accuracy rates of 0.960,0.968,and 0.986,respectively.The difference in performance between the three models reflects the degrees of variation in different features of ChatGPT answers versus physician answers.The results indicate that the differences between ChatGPT and physicians in syntactic features,i.e.,linguistic expression habits,are greater than their differences in semantic features,i.e.,specific content suggestions.展开更多
基金supported in part by the Key Projects of Philosophy and Social Sciences Research supported by the Ministry of Education of the People’s Republic of China(Grant No.:15JJD870001)Luo Jia Youth Scholar of Wuhan University
文摘Purpose： This study investigates how online user intention in searching health information is affected by problematic situations.Design/methodology/approach： Based on the Theory of Reasoned Action, the Technology Acceptance Model, and Sense-making theory, we propose two dimensions of problematic situations： urgency and severity of health issues being searched online. Data were collected through a questionnaire survey among 214 Wuhan University students and analyzed using hierarchical regression analysis.Findings： Perceived usefulness, perceived ease of use, and subjective norm can influence user intention to seek health information online. The urgency of problematic situations has a negative moderating effect on the relationship between perceived ease of use and user intention and the relationship between subjective norm and user intention. The severity of problematic situations has a negative moderating effect on the relationship between subjective norm and user intention.Research limitations： The respondents of the survey are limited to students in one Chinese university, so whether this study＇s results can be applied to another population or not remains to be verified. In addition, only two dimensions of problematic situations are considered in this study. Practical implications： The paper puts forward the moderating effect of problematic situations and verifies it, which is the compensation for online health information-seeking behavior research. Besides, our analyses have implications for professional design of health care systems and related consumer information searches, and improve their performance. Originality/value： Previous work has reported the effects of problematic situation on user intention to seek health information online, ignoring its influence on other factors. This empirical study extends that work to identify the influence of problematic situation when seeking intention-behavior data in two dimensions, urgency and severity.
基金supported by Wuhan University Development Program for Researchers Born after the 1970s
文摘Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(about:blank Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.
基金jointly supported by National Social Science Foundation of China(Grant No.14BTQ044)Wuhan University Academic Development Plan for Scholars after 1970s
文摘Purpose: Taking Zhihu as the object for a case study, we intend to analyze the key factors that have affected users on adopting answers in social Q&A(SQA) websites.Design/methodology/approach: With information adoption model(IAM) as the theoretical foundation and widely accepted evaluation criteria for answer quality in SQA sites as variables, we constructed a factor model that has influenced SQA community users to adopt offered answers. With the partial least squares(PLS) technique, our model was then empirically tested through a sample of 311 Zhihu users.Findings: Our results showed that answer usefulness is the most effective variable, and answer interactivity and answer entertainment both have positive and significant impacts on users’ attitude to adopt answers in an SQA community. Except for novelty, other three components of answer quality, i.e. knowledge, reliability, and solution to the problem have all significant effect on answer usefulness.Research limitations: First, due to the limited sample size, it is still questionable if our research results based on Zhihu could be applied to other SQA communities. Second, our questionnaires were mainly designed to investigate how users felt about the answers in an SQA site, but did not differentiate the content of the answer itself.Practical implications: As a three-year-old SQA platform, Zhihu has developed very quickly with its high-quality answers and public intellectual users, and has been regarded as one of the representatives of fast emerging Chinese SQA communities in recent years. Our studycould help shed light on users’ information sharing and knowledge adoption behaviors in a Chinese SQA site, such as Zhihu. Originality/value: Compared with previous studies on answer quality assessments in SQA sites and on information adoption model, to the best of our knowledge, this is one of the pioneer studies which combined answer qualities with users’ intention of adopting SQA answers. Our study on user answer adoption in Zhihu community could further develop the theory of IAM. This study showed that answer usefulness is the most important motivation of Zhihu users in the process of adopting answers.
基金jointly supported by the National Social Science Foundation of China(Grant No.:14BTQ044)Wuhan University Academic Development Plan for Scholars born after the 1970s for the project of"research on Internet user behavior"Wuhan University Postgraduate English Course on Internet User Behavior and Luo Jia Youth Scholar of Wuhan University
文摘Purpose： We conducted an empirical study to find out the role of demographic variables in affecting information sharing behaviors of college student users of WeChat.Design/methodology/approach： A questionnaire survey was carried out to investigate the relationship between demographic variables （gender, grade level, dating status, and singleparent family background） and information sharing behaviors of WeChat users. The participants were college students and a total of 255 valid questionnaires were collected. Data was analyzed using descriptive statistics and multiple regression analysis.Findings： Grade level and single-parent family background were found to be significantly correlated with information sharing behaviors whereas no effect of gender was found on information sharing behaviors. Dating status had no significant impact on user browsing behavior, but was related to users＇ publishing posts and posting replies.Implications： The study will help understand individual differences in information sharing among WeChat users.Limitations： First, the relatively small sample size is a limitation in exploring the effects of demographic variables on user information sharing behaviors. Second, this study only used questionnaire surveys to collect data and more research methods such as interviews should be adopted to improve the accuracy of the study results.Originality/value： This paper is one of the first studies to explore the relationship between demographic variables and user information sharing behaviors on WeChat.
基金supported by the National Social Science Foundation of China(Grant Nos.:10CTQ010 and 11CTQ038)Wuhan University Development Program for Researchers Born after the 1970s
文摘Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.
基金supported in part by National Natural Science Foundation,PR China(Grant No.72374158)。
文摘ChatGPT changes the way of knowledge production and information space structure of human society.In the healthcare industry,ChatGPT's powerful question-and-answer capability will drive its application in automated question answering in online healthcare communities.However,because ChatGPT answers are limited by factors such as the quality of data sets,their authority and accuracy cannot be guaranteed,and they are prone to misdiagnosis and damage to life and health.Therefore,the identification of ChatGPT answers in online medical communities with physician answers is crucial.In this paper,we collected medical question-answering data generated by the Haodafu platform and ChatGPT,respectively,constructed feature vectors from semantic features,syntactic features,and the fusion of both,and combined different feature vectors with XGBoost models to construct BERT-XGBoost,POS-XGBoost and Merge-XGBoost models for identifying ChatGPT answers and physician answers in online medical communities.The three models achieved accuracy rates of 0.960,0.968,and 0.986,respectively.The difference in performance between the three models reflects the degrees of variation in different features of ChatGPT answers versus physician answers.The results indicate that the differences between ChatGPT and physicians in syntactic features,i.e.,linguistic expression habits,are greater than their differences in semantic features,i.e.,specific content suggestions.
