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As an increasing number of users have acquired information across the web and mobile platforms for social question and answering (Q&A), it is of interest to explore whether there are differences in social Q&A usages between the two platforms. The purpose of this paper is to compare web and mobile platforms of a social Q&A service from the user’s perspective in terms of three dimensions, namely, demographics, individual-based constructs, and information-based constructs.

Because Zhihu.com is one of the most popular social Q&A sites in China, the authors used online questionnaires to investigate its users’ perceptions of these three dimensions. From January to March 2016, the authors obtained 278 valid responses in total through snowball and convenient sampling. Collected data are analyzed through descriptive statistics and inferential statistics.

The results indicate that there exist significant differences between web users and mobile users on Zhihu.com in terms of gender, affinity, and information seeking. More specifically, compared to the male users, more female users rely on the mobile platform to access the information service; mobile users perceive higher affinity with Zhihu.com than web users; and mobile users perceive higher information-seeking intention than web users do.

Regarding the theoretical aspect, this study proposes a conceptual framework for comparison between the web and mobile platforms of social Q&A from the user’s perspective. Regarding the practical aspect, the comparative results of this study could give social Q&A service providers useful information about users’ differences between web and mobile platforms of social Q&A services.

This paper aims to investigate the service demand of existing users and potential users for mobile information services provided by university libraries in China. The primary objective is to explore the impact of user experience on user needs, which is conducted by a comparison between two user groups over their needs from three aspects – service function, service mode and information content.

Data were collected from 353 library users from ten Chinese universities via questionnaires. Based on the user needs model, three dimensions of user needs were established for mobile information services and 26 measurement items were generated through a review of the literature. Furthermore, based on frequency analysis, independent samples t-test and the calculation of need rate, the demand differences in mobile information services between existing and potential users were explored.

Significant differences existed in the needs for service functions and service modes of mobile information services between existing users and potential users. Existing users cared more about such characteristics as intelligence, personalization and the variety of mobile services. Potential users, in contrast, concerned themselves more with the usability of mobile services and similarity to traditional information services. These two user groups showed little difference in the needs for information content, as they both have strict requirements for specialty, richness in and quality of information resources in mobile network environments.

Previous research on user needs for mobile libraries services has been primarily conducted from the perspectives of existing users. This study, however, compared the needs of existing and potential users based on their previous experiences, which can help libraries to know better what their users need and improve the quality of mobile information services to meet those needs. This can also make existing users more willing to use the services and cultivate the usage habits of potential users at the same time.

The purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user interaction behavior on social media and (2) examine whether social interaction data on social media platforms can predict user personality.

Social interaction data was collected from 198 users of Sina Weibo, a popular social media platform in China. Their personality traits were also measured via questionnaire. Machine learning techniques were applied to predict the personality traits based on the social interaction data.

The results demonstrated that the proposed classifiers had high prediction accuracy, indicating that our approach is reliable and can be used with social interaction data on social media platforms to predict user personality. “Reposting,” “being reposted,” “commenting” and “being commented on” were found to be the key interaction features that reflected Weibo users' personalities, whereas “liking” was not found to be a key feature.

The findings of this study are expected to enrich personality prediction research based on social media data and to provide insights into the potential of employing social media data for the purpose of personality prediction in the context of the Weibo social media platform in China.

Drawing on the Health Belief Model (HBM), this study aims to investigate the roles of health beliefs (i.e. perceived susceptibility, perceived severity, perceived benefits, perceived barriers, health self-efficacy and cues to action) in promoting college students’ smartphone avoidance intention.

Empirical data were collected through a cross-sectional survey questionnaire administered to 4,670 student smartphone users at a large university located in Central China. Further, a two-step Structural Equation Modeling was conducted using AMOS 22.0 software to test the hypothesized relationships in the research model.

Analytical results indicate that (1) perceived susceptibility, perceived severity, perceived benefits and health self-efficacy positively influence users’ smartphone avoidance intention; (2) perceived barriers negatively influence smartphone avoidance intention, while (3) cues to action reinforce the relationships between perceived susceptibility/perceived benefits and smartphone avoidance intention, but attenuate the relationships between perceived barriers/health self-efficacy and smartphone avoidance intention.

This study demonstrates that HBM is invaluable in explaining and promoting users’ smartphone avoidance intention, thereby extending extant literature on both HBM and smartphone avoidance.

Research on smartphone avoidance is still in a nascent stage. This study contributes to the field by offering a fresh theoretical lens for pursuing this line of inquiry together with robust empirical evidence.

This study aims to examine the factors influencing the adoption intention of information service mashup in digital library (DL). The study is an empirical study on DLs in China.

This paper employs the theory of information service mashup as its theoretical background and applies it to the field of DL to develop the measurement model which is based on technology acceptance model (TAM). A structured questionnaire was developed including the demographic information, the advantages of information service mashup in DL and the Likert evaluation of each construct. As a result, of 303 questionnaires distributed among DL users, 281 were remained as acceptable answers. The data were processed and analyzed with the aid of the SPSS 20.0 and SmartPLS 2.0.

The results show that beyond perceived usefulness and perceived ease of use, both perceived integration and perceived risk have direct impacts on user’s intention to adopt information service mashup in DL. Perceived integration has the dramatic positive effects, while perceived risk negatively correlates to adoption intention. Moreover, perceived integration and individualization have positive impacts on perceived ease of use, while network externality positively influences perceived usefulness.

Information service mashup is still a relatively new technology in DL. There were few theoretical and empirical studies that examine the user adoption behaviour of the service. This study contributes to existing information service mashup application studies by modifying and extending TAM. The results would help the DL gain a deeper understanding of the factors affecting DL user adoption of information service mashup.

This study aims to examine why users search for images, how users describe their image needs and what the images are used for by analysing questions obtained from two Chinese social Q&A sites, Zhihu and Baidu Zhidao.

A total of 1,402 image questions were collected from Zhihu and Baidu Zhidao. Both quantitative analysis and qualitative content analysis were performed to identify user image needs and the potential differences on the two social Q&A sites.

Question-asker’s intention varies in different platforms. Zhihu users asked questions mainly aiming at a promotion of subsequent discussion, whereas users of Baidu Zhidao often did so to seek information. Syntactic attributes were not frequently used in both two sites. Zhihu users were more likely to express subjective evaluations on images (concept, emotion, theme and style) in their questions than users of Baidu Zhidao. In contrast, questions from Baidu Zhidao showed a tendency to more frequently include descriptive metadata (rights, format, size, quality and authenticity) and semantic attributes (generic activity, specific people, fashion and text) of the images than questions from Zhihu. Learning was an important use on social Q&A sites, especially on Baidu Zhidao. In addition, the images were primarily used to trigger emotion or served a persuasive purpose in Zhihu.

This study contributes to a better understanding of user image search behaviour, and the findings could be used to develop better image services on social Q&A sites. Meanwhile, the image attributes extracted from the questions are conducive to the improvement of image retrieval systems.

This study explored the features of image needs on social Q&A sites, especially considering image use specified in the question. The difference of image needs between two Chinese social Q&A sites (Zhihu and Baidu Zhidao) was identified.

In the era of big data, people are more likely to pay attention to privacy protection with facing the risk of personal information leakage while enjoying the convenience brought by big data technology. Furthermore, people’s views on personal information leakage and privacy protection are varied, playing an important role in the legal process of personal information protection. Therefore, this paper aims to propose a semi-qualitative method based framework to reveal the subjective patterns about information leakage and privacy protection and further provide  practical implications for interested party.

Q method is a semi-qualitative methodology which is designed for identifying typologies of perspectives. In order to have a comprehensive understanding of users’ viewpoints, this study incorporates LDA & TextRank method and other information extraction technologies to capture the statements from large-scale literature, app reviews, typical cases and survey interviews, which could be regarded as the resource of the viewpoints.

By adopting the Q method that aims for studying subjective thought patterns to identify users’ potential views, the authors have identified three categories of stakeholders’ subjectivities: macro-policy sensitive, trade-offs and personal information sensitive, each of which perceives different risk and affordance of information leakage and importance and urgency of privacy protection. All of the subjectivities of the respondents reflect the awareness of the issue of information leakage, that is, the interested parties like social network sites are unable to protect their full personal information, while reflecting varied resistance and susceptibility of disclosing personal information for big data technology applications.

The findings of this study provide an overview of the subjective patterns on the information leakage issue. Being the first to incorporate the Q method to study the views of personal information leakage and privacy protection, the research not only broadens the application field of the Q method but also enriches the research methods for personal information protection. Besides, the proposed LDA & TextRank method in this paper alleviates the limitation of statements resource in the Q method.

This paper aims to understand Social Questions & Answers (SQA) users’ perceptions of library reference services.

The authors examined the postings on the largest SQA site, Yahoo! Answers, regarding library reference services and identified the major themes.

Three themes emerged in library reference-related discussions: reference librarians and their services are well and positively recognized, reference services are less recognized and understood and Yahoo! Answers is recognized as a helpful service. Those who have used both library reference services and Yahoo! Answers are fully aware of the differences between the two services.

This study provides new insights on how library reference services are perceived by SQA users. The results are helpful for libraries to position reference services to better serve users in today’s information environment.

The purpose of this paper is to identify the driving factors of web based question‐answer services (WBQAS) adoption. As an emerging knowledge acquisition method and service there are currently few studies addressing the antecedents of the service's acceptance, in particular concerning Chinese users.

This paper employs the unified theory of acceptance and use of technology as its theoretical background and applies it to the field of WBQAS. A survey was conducted.

Based on 169 useful questionnaires the results show that both performance expectancy and effort expectancy are significant predictors of the intention to use WBQAS. Additionally behavioural intention, together with facilitating intention, significantly influences the actual use of WBQAS. Social influence has no significant impact on the intention to use the service.

As research on WBQAS is in its infancy this paper is among the first in the field, in particular regarding Chinese users. In addition the research applied the unified theory of acceptance and use of technology model to the context of WBQAS and validated the adoption model using structural equation modelling.

The purpose of this study is to seek to quantify how unique service resources and consumer habit affect e-service loyalty (e-loyalty) in a highly competitive market. This study is grounded on Chinese social networking service (SNS) industry. A resource-based view is introduced as an alternative perspective to understand building consumer loyalty in e-service contexts.

A research framework is developed by reviewing prior literature. An online survey is conducted to collect research data. Based on 221 valid responses, the research model is tested by using partial least squares path modeling technique.

The features of market environments affects the loyalty of consumers to e-service providers. Consumers become mercenary in highly competitive and low differentiation e-service markets like Chinese SNS industry. The interaction of satisfaction and switching cost affects loyalty. Satisfied consumers can be either loyal or not loyal to a service provider depending on their level of switching cost, but unsatisfied consumers will have no loyalty. In addition, users are loyal to a SNS partly because it is their habit to use the service. Our study suggests that relying on consumer satisfaction to build e-loyalty may be problematic and risky.

The study represents an attempt to introduce the resource-based view to e-loyalty research. The research highlights the importance of habit in building consumers’ e-service satisfaction and loyalty and contributes to new insights on the importance of industry environment in determining e-service satisfaction–loyalty relationship based on studying consumers in a highly competitive market.