Highlights
Users with a high level of eHealth literacy are more likely to share positive health articles when they have extreme confirmation bias.
Users with a high level of eHealth literacy are more likely to share negative health articles when they have moderate confirmation bias or no confirmation bias.
Users with a low level of eHealth literacy are more likely to share health articles regardless of positive or negative content valence when they have moderate positive confirmation bias.
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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 seeks to depict online rumor retransmission using three main constructs, namely, message characteristics, user characteristics and retransmission outcomes. In particular, it teases retransmission outcomes into volume, immediacy and lifespan of rumor tweets. The dataset was drawn from 322 original Twitter messages which generated some 5,700 retweets about the rumored death of Lee Kuan Yew (LKY). Content analysis and statistical tests were conducted. The results confirm the robustness of the research model. Specifically, rumor message characteristics affect retransmission in terms of volume, immediacy and lifespan. Additionally, user characteristics are positively related to volume and immediacy. Finally, user characteristics have a moderating effect on the relationships between rumor message characteristics and retransmission outcomes. This paper illustrates the applicability of the information diffusion model on online rumor retransmission which hitherto has yet to be attempted. Moreover, it granularizes the concept of online rumor retransmission into three important outcomes, namely, volume, immediacy and lifespan. On the practical front, this paper has implications for organizations seeking to combat rumors.
PurposeThis study explores identity signaling used by an emerging class of knowledge celebrities in China – Knowledge Wanghong – who sell knowledge products on online platforms. Because identity signaling may involve constructing unique online identities and controlling over product-related and seller-related characteristics, the purpose of this study is two-fold: (1) to uncover different online identities of knowledge celebrities; and (2) to examine the extent to which the online identity type is associated with their product-related characteristics, seller-related characteristics and sales performance.Design/methodology/approachA unique data set was collected from a Chinese leading pay-for-knowledge platform – Zhihu – which featured the online profiles of tens of thousands of knowledge celebrities. Online identity types were derived from their self-edited content using Latent Dirichlet Allocation (LDA) topic modeling. Thereafter, their product-related characteristics, seller-related characteristics and respective sales performance were analyzed across different identity types using analysis of variance (ANOVA) and multiple-group linear regression.FindingsKnowledge celebrities are clustered into four distinctive online identities: Mentor, Broker, Storyteller and Geek. Product-related characteristics, sell-related characteristics and sales performance varied across four different identities. Additionally, the online identity type moderated the relationships among their product-related characteristics, sell-related characteristics and sales performance.Originality/valueAs emerging-phenomenon-based research, this study extends related literature by using the notion of identity signaling to analyze a peculiar group of online celebrities who are setting an important trend in the pay-for-knowledge model in China.
Cyberchondria describes excessive or repeated health‐related information seeking on the Internet that is associated with increased emotional distress. Research on cyberchondria is still nascent. This study aims to propose a moderated mediation model to examine the relationships among intolerance of uncertainty, affective responses, e‐health literacy, and cyberchondria. Based on an online survey of 426 participants in China, the results suggest that intolerance of uncertainty is positively associated with cyberchondria, and affective responses partially mediate this association. Additionally, e‐health literacy negatively moderates the effect of affective responses on cyberchondria. Implications and limitations of this study are discussed.
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