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There is increasing evidence that citations to Chinese research publications are rising sharply. A series of reasons have been highlighted in previous studies. This research explores another possibility-whether there is a 'clubbing' effect in China's surge in research citations, in which a higher rate of internal citing takes place among influential Chinese researchers. Focusing on the most highly cited research articles in nanotechnology, we find that a larger proportion of Chinese nanotechnology research citations are localized within individual, institutional, and national networks within China. Both descriptive and statistical tests suggest that highly cited Chinese papers are more likely than similar U.S. papers to receive internal and localized citations. Tentative explanations and policy implications are discussed. [ABSTRACT FROM AUTHOR]

Revealing interdisciplinary patterns is a cornerstone for the continued evolution of research, education, and societal progress, providing a scaffold upon which to build a more collaborative and integrated approach to knowledge creation. This study presents a novel approach to identifying and analyzing the critical year for interdisciplinary citations (CYIC), which was defined as the year in which qualitative change in interdisciplinary knowledge flow occurred. We conducted two experiments using a Chinese paper dataset spanning 106 disciplines from 1992 to 2022, with the first to pinpoint the occurrence of CYICs and the second to examine three patterns of interdisciplinarity following these CYICs. Our findings revealed that 85% of disciplines exhibit CYICs, often corresponding with a transition from unidirectional output to reciprocal knowledge cooperation. Furthermore, we found that datasets after CYICs are generally characterized by increased interdisciplinarity of knowledge, albeit without a corresponding rise in the interdisciplinarity of disciplines or interdisciplinary diversity. Our results suggest that policy shifts and societal needs are pivotal in driving the formation of interdisciplinary collaborations, as exemplified by the surge in mutual interdisciplinary citations in response to China's poverty alleviation efforts and western development policies. [ABSTRACT FROM AUTHOR]

This paper investigates different uses of the Journal Impact Factor (JIF) in national journal rankings and discusses the merits of supplementing metrics with expert assessment. Our focus is national journal rankings used as evidence to support decisions about the distribution of institutional funding or career advancement. The seven countries under comparison are China, Denmark, Finland, Italy, Norway, Poland, and Turkey—and the region of Flanders in Belgium. With the exception of Italy, top‐tier journals used in national rankings include those classified at the highest level, or according to tier, or points implemented. A total of 3,565 (75.8%) out of 4,701 unique top‐tier journals were identified as having a JIF, with 55.7% belonging to the first Journal Impact Factor quartile. Journal rankings in China, Flanders, Poland, and Turkey classify journals with a JIF as being top‐tier, but only when they are in the first quartile of the Average Journal Impact Factor Percentile. Journal rankings that result from expert assessment in Denmark, Finland, and Norway regularly classify journals as top‐tier outside the first quartile, particularly in the social sciences and humanities. We conclude that experts, when tasked with metric‐informed journal rankings, take into account quality dimensions that are not covered by JIFs. [ABSTRACT FROM AUTHOR]

As a healthcare ICT4D solution, mobile health (mHealth) can potentially improve users' well‐being during pandemics, especially in developing countries with limited healthcare resources. Recent ICT4D research reveals that providing end‐users with access to ICT is insufficient for improving well‐being and, thus, understanding how mHealth empowers end‐users to enhance well‐being against stressful events is important. However, prior research has rarely discussed the issue of empowerment in the domain of mHealth or the context of major disruptive events. This paper contributes to the literature by conceptualizing the psychological empowerment of mHealth users (PEMU) and investigating its nomological network during pandemics. Drawing upon theories of psychological empowerment and event characteristics, we developed a research model and tested it through a mixed‐methods investigation, containing a quantitative study with 602 Chinese mHealth users during COVID‐19 and a follow‐up qualitative study of 326 online articles and reviews. We found that PEMU, driven by three technological characteristics (perceived response efficacy, ease of use, and mHealth quality), affects well‐being through both (a) a stress‐buffering effect, which counterbalances the detrimental, stress‐increasing effects of event criticality and disruption, and (b) a vitality‐stimulating effect, which is intensified by event criticality. These findings have important implications for ICT4D research and practice. [ABSTRACT FROM AUTHOR]

We collected research articles from Retraction Watch database, Scopus, and a major retraction announcement by Springer, to identify emails used by authors. Authors' emails can be institutional emails and noninstitutional emails. Data suggest that retracted articles are more likely to use noninstitutional emails, but it is difficult to generalize. The study put some focus on authors from China. [ABSTRACT FROM AUTHOR]

Although the open access citation advantage (OACA) has been discussed extensively, scholars lack a clear understanding of the mechanisms through which switching from subscription‐based model to open access (OA) model affects the citation impact of a scholarly journal. Many journals have switched from subscription to OA, yet they later also flipped their preswitching articles (i.e., those under subscription model) to OA, thus leaving no subscription article to be compared with their postswitching OA counterparts. To detect the switching effect, our study instead focused on 60 journals that "reverse flipped" from OA to subscription. We use a difference‐in‐difference (DiD) analytical framework to analyze two propositions related to OACA, based on the bibliographic and citation data of pre‐ and postswitching publications in these journals. Our findings indicate that reverse flipping is unlikely to affect the journals' impact through changing the visibility of their articles. Instead, it could lead to a systematical shift in the submissions to the journals and thus considerably affect their impact. Our findings have important theoretical and practical implications for subsequent studies, funding agencies, and scholarly journals considering a reverse flip. [ABSTRACT FROM AUTHOR]

Social influence has a great impact on human behavior, which has been widely investigated in various research fields. Even so, it has rarely been investigated in the online health community. In this paper, we focus on the multichannel access in online health communities, defining social influence as the average degree of multichannel access to a physician's colleagues. Based on the multinomial logistic regression model, we examined the direct effects of social influence and patients' rating to multichannel access. In addition, we explored the moderating effect of social influence on the relationship between patients' rating and multichannel access in online health communities. The results of the experiment and robustness testing support the propositions that social influence and patients' rating significantly and positively affect multichannel access in an online health community. The moderating effect of social influence is negative and significantly influences the accessible channels provided by the focal physician. This research contributes to the literature concerning online health communities, social influence, and multichannel access; it also has practical implications. [ABSTRACT FROM AUTHOR]

Opinion words are crucial information for sentiment analysis. In some text, however, opinion words are absent or highly ambiguous. The resulting implicit opinions are more difficult to extract and label than explicit ones. In this paper, cutting-edge machine-learning approaches - deep neural network and word-embedding - are adopted for implicit opinion mining at the snippet and clause levels. Hotel reviews written in Chinese are collected and annotated as the experimental data set. Results show the convolutional neural network models not only outperform traditional support vector machine models, but also capture hidden knowledge within the raw text. The strength of word-embedding is also analyzed. [ABSTRACT FROM AUTHOR]

With the information overload of user-generated content in microblogging, users find it extremely challenging to browse and find valuable information in their first attempt. In this paper we propose a microblogging recommendation algorithm, TSI-MR (Topic-Level Social Influence-based Microblogging Recommendation), which can significantly improve users' microblogging experiences. The main innovation of this proposed algorithm is that we consider social influences and their indirect structural relationships, which are largely based on social status theory, from the topic level. The primary advantage of this approach is that it can build an accurate description of latent relationships between two users with weak connections, which can improve the performance of the model; furthermore, it can solve sparsity problems of training data to a certain extent. The realization of the model is mainly based on Factor Graph. We also applied a distributed strategy to further improve the efficiency of the model. Finally, we use data from Tencent Weibo, one of the most popular microblogging services in China, to evaluate our methods. The results show that incorporating social influence can improve microblogging performance considerably, and outperform the baseline methods. [ABSTRACT FROM AUTHOR]

This paper proposes a diffusion model to measure the evolution of stakeholders' disaster perceptions by integrating a disaster message model, a stakeholder model, and a stakeholder memory model, which collectively describe the process of information flow. Simulation results show that the rate of forgetting has a significantly negative effect on stakeholders' perceptions and the incremental increase in the number of affected individuals has a positive effect on the maximum level of stakeholders' perceptions, but negative effect on the duration of stakeholders' perceptions. Additionally, a delay effect, a stagnation effect, and a cumulative effect exist in the evolution of stakeholders' perceptions. There is a spike at the beginning of the profile of stakeholders' perceptions in the Damped Exponential Model. An empirical test supports the validity of this model of stakeholders' disaster perceptions. [ABSTRACT FROM AUTHOR]

Text mining has been widely used in multiple types of user-generated data to infer user opinion, but its application to microblogging is difficult because text messages are short and noisy, providing limited information about user opinion. Given that microblogging users communicate with each other to form a social network, we hypothesize that user opinion is influenced by its neighbors in the network. In this paper, we infer user opinion on a topic by combining two factors: the user's historical opinion about relevant topics and opinion influence from his/her neighbors. We thus build a topic-level opinion influence model (TOIM) by integrating both topic factor and opinion influence factor into a unified probabilistic model. We evaluate our model in one of the largest microblogging sites in China, Tencent Weibo, and the experiments show that TOIM outperforms baseline methods in opinion inference accuracy. Moreover, incorporating indirect influence further improves inference recall and f1-measure. Finally, we demonstrate some useful applications of TOIM in analyzing users' behaviors in Tencent Weibo. [ABSTRACT FROM AUTHOR]

This study explored users' criteria for citation decisions and investigated the effects on users' intention to cite using a mixed‐method approach. A qualitative study was conducted first, where 16 citing criteria were identified based on interviews and inductive analysis. The findings were then used to develop hypotheses and extend the information adoption model. A questionnaire was designed to collect data from users in Chinese universities to test the research model. The findings indicated that pleasure, topicality, and functionality significantly increased users' perceived information usefulness, while familiarity and accessibility significantly enhanced users' perceived ease of use. Information usefulness and information ease of use further contributed to users' intention to cite with adjusted R2 equaling 44.6%. It is also found that perceived academic quality based on 5 antecedents (i.e., reliability, comprehensiveness, novelty, author credibility, and source reputation) significantly increased users' pleasure. Implications and limitations were provided. [ABSTRACT FROM AUTHOR]

Characterizing the leadership in research is important to revealing the interaction pattern and organizational structure through research collaboration. This research defines the leadership role based on the corresponding author's affiliation, and presents the first quantitative research on the factors and evolution of 5 proximity dimensions (geographical, cognitive, institutional, social, and economic) of research leadership. The data to capture research leadership consist of a set of multi‐institution articles in the fields of "Life Sciences & Biomedicine," "Technology," "Physical Sciences," "Social Sciences," and "Humanities & Arts" during 2013–2017 from the Web of Science Core Citation Database. A Tobit regression‐based gravity model indicates that the mass of research leadership of both the leading and participating institutions and the geographical, cognitive, institutional, social, and economic proximities are important factors for the flow of research leadership among Chinese institutions. In general, the effect of these proximities for research leadership flow has been declining recently. The outcome of this research sheds light on the leadership evolution and flow among Chinese institutions, and thus can provide evidence and support for grant allocation policies to facilitate scientific research and collaborations. [ABSTRACT FROM AUTHOR]

Research collaboration is promoted by governments and research funders, but if the relative prevalence and merits of collaboration vary internationally then different national and disciplinary strategies may be needed to promote it. This study compares the team size and field normalized citation impact of research across all 27 Scopus broad fields in the 10 countries with the most journal articles indexed in Scopus 2008–2012. The results show that team size varies substantially by discipline and country, with Japan (4.2) having two‐thirds more authors per article than the United Kingdom (2.5). Solo authorship is rare in China (4%) but common in the United Kingdom (27%). While increasing team size associates with higher citation impact in almost all countries and fields, this association is much weaker in China than elsewhere. There are also field differences in the association between citation impact and collaboration. For example, larger team sizes in the Business, Management & Accounting category do not seem to associate with greater research impact, and for China and India, solo authorship associates with higher citation impact in this field. Overall, there are substantial international and field differences in the extent to which researchers collaborate and the extent to which collaboration associates with higher citation impact. [ABSTRACT FROM AUTHOR]

Live chat, which is embedded in some shopping websites, allows a retailer to communicate with its shoppers directly and respond to their inquiries promptly. We extended the Speech Act Theory (SAT) to this context by developing the Dialog Conversion Model (DCM) that elucidates the characteristics of online dialog between shoppers and retailers. We validated the DCM using quantitative and qualitative data. The quantitative analyses of 1,185 communication sessions and related purchase records reflect that shoppers' cognitive, rather than affective, expressions tend to indicate their purchase intentions, and retailers should emphasize cognitive expressions to the extent possible while being strategic in their choice of expressions. Furthermore, the affective expressions (in positive and negative forms) articulated by retailers have a considerable influence on purchase conversion. However, the same is not true for shoppers. Post‐hoc interviews were conducted with shoppers to gain additional insights. [ABSTRACT FROM AUTHOR]

International students face various challenges in their new countries, but research is less clear about their challenges in information behaviors. This article fills this gap by examining information behaviors of international newcomer students during adjustment to local environments, that is, local information behavior (LIB). Drawing on prior work, we focus on the local co‐national context—the degree to which there are co‐nationals available in one's local environments—to analyze the LIBs of 149 first‐year graduate students and 57 follow‐up interviewees, who were classified into: International‐common group (students from China, India, and Korea—with many local co‐nationals), International‐less‐common group (students from other countries—with fewer local co‐nationals), and Domestic‐out‐of‐state group (students from other U.S. states; control group). We identify differences in international newcomer students' use of information sources during adjustment and the role that local co‐national contexts play in these differences. These results suggest ways that information scholars and practitioners might account for the influences of local co‐national contexts when examining information behaviors of internationally mobile students and designing systems and services for newcomers from around the world. [ABSTRACT FROM AUTHOR]

With the significant development of China's economy and scientific activity, its scientific publication activity is experiencing a period of rapid growth. However, measuring China's research output remains a challenge because Chinese scholars may publish their research in either international or national journals, yet no bibliometric database covers both the Chinese and English scientific literature. The purpose of this study is to compare Web of Science (WoS) with a Chinese bibliometric database in terms of authors and their performance, demonstrate the extent of the overlap between the two groups of Chinese most productive authors in both international and Chinese bibliometric databases, and determine how different disciplines may affect this overlap. The results of this study indicate that Chinese bibliometric databases, or a combination of WoS and Chinese bibliometric databases, should be used to evaluate Chinese research performance except in the few disciplines in which Chinese research performance could be assessed using WoS only. [ABSTRACT FROM AUTHOR]

Information from microblogs is gaining increasing attention from researchers interested in analyzing fluctuations in stock markets. Behavioral financial theory draws on social psychology to explain some of the irrational behaviors associated with financial decisions to help explain some of the fluctuations. In this study we argue that social media users who demonstrate an interest in finance can offer insights into ways in which irrational behaviors may affect a stock market. To test this, we analyzed all the data collected over a 3‐month period in 2011 from Tencent Weibo (one of the largest microblogging websites in China). We designed a social influence (SI)‐based Tencent finance‐related moods model to simulate investors' irrational behaviors, and designed a Tencent Moods‐based Stock Trend Analysis (TM_STA) model to detect correlations between Tencent moods and the Hushen‐300 index (one of the most important financial indexes in China). Experimental results show that the proposed method can help explain the data fluctuation. The findings support the existing behavioral financial theory, and can help to understand short‐term rises and falls in a stock market. We use behavioral financial theory to further explain our findings, and to propose a trading model to verify the proposed model. [ABSTRACT FROM AUTHOR]

In recent years, millions of households have shifted from traditional TVs to smart TVs for viewing online videos on TV screens. In this article, we perform extensive analyses on a large‐scale online video viewing log on smart TVs. Because time influences almost every aspect of our lives, our aim is to understand temporal patterns of the online video viewing behavior of smart TV viewers at the crowd level. First, we measure the amount of time per hour spent in watching online videos on smart TV by each household on each day. By applying clustering techniques, we identify eight daily patterns whose peak hours occur in different segments of the day. The differences among households can be characterized by three types of temporal habits. We also uncover five periodic weekly patterns. There seems to be a circadian rhythm at the crow level. Further analysis confirms that there exists a holiday effect in the online video viewing behavior on smart TVs. Finally, we investigate the popularity variations of different video categories over the day. The obtained insights shed light on how we can partition a day to improve the performance of time‐aware video recommendations for smart TV viewers. [ABSTRACT FROM AUTHOR]

Batik as a traditional art is well regarded due to its high aesthetic quality and cultural heritage values. It is not uncommon to reuse versatile decorative shape patterns across batiks. General‐purpose image retrieval methods often fail to pay sufficient attention to such a frequent reuse of shape patterns in the graphical compositions of batiks, leading to suboptimal retrieval results, in particular for identifying batiks that use copyrighted shape patterns without proper authorization for law‐enforcement purposes. To address the lack of an optimized image retrieval method suited for batiks, this study proposes a new method for retrieving salient shape patterns in batiks using a rich combination of global and local features. The global features deployed were extracted according to the Zernike moments (ZMs); the local features adopted were extracted through curvelet transformations that characterize shape contours embedded in batiks. The method subsequently incorporated both types of features via matching a weighted bipartite graph to measure the visual similarity between any pair of batik shape patterns through supervised distance metric learning. The derived similarity metric can then be used to detect and retrieve similar shape patterns appearing across batiks, which in turn can be employed as a reliable similarity metric for retrieving batiks. To explore the usefulness of the proposed method, the performance of the new retrieval method is compared against that of three peer methods as well as two variants of the proposed method. The experimental results consistently and convincingly demonstrate that the new method indeed outperforms the state‐of‐the‐art methods in retrieving salient shape patterns in batiks. [ABSTRACT FROM AUTHOR]

Prior research has discovered that groups tend to discuss shared information while failing to discuss unique information in decision‐making processes. In our study, we conducted a lab experiment to examine the effect of prediscussion note‐taking on this phenomenon. The experiment used a murder‐mystery hidden profile task. In all, 192 undergraduate students were recruited and randomly assigned into 48 four‐person groups with gender being the matching variable (i.e., each group consisted of four same‐gender participants). During the decision‐making processes, some groups were asked to take notes while reading task materials and had their notes available in the following group discussion, while the other groups were not given this opportunity. Our analysis results suggest that (a) the presence of an information piece in group members' notes positively correlates with its appearance in the subsequent discussion and note‐taking positively affects the group's information repetition rate; (b) group decision quality positively correlates with the group's information sampling rate and negatively correlates with the group's information sampling/repetition bias; and (c) gender has no statistically significant moderating effect on the relationship between note‐taking and information sharing. These results imply that prediscussion note‐taking could facilitate information sharing but could not alleviate the biased information pooling in hidden profile tasks. [ABSTRACT FROM AUTHOR]

Music mood recognition (MMR) has attracted much attention in music information retrieval research, yet there are few MMR studies that focus on non-Western music. In addition, little has been done on connecting the 2 most adopted music mood representation models: categorical and dimensional. To bridge these gaps, we constructed a new data set consisting of 818 Chinese Pop (C-Pop) songs, 3 complete sets of mood annotations in both representations, as well as audio features corresponding to 5 distinct categories of musical characteristics. The mood space of C-Pop songs was analyzed and compared to that of Western Pop songs. We also explored the relationship between categorical and dimensional annotations and the results revealed that one set of annotations could be reliably predicted by the other. Classification and regression experiments were conducted on the data set, providing benchmarks for future research on MMR of non-Western music. Based on these analyses, we reflect and discuss the implications of the findings to MMR research. [ABSTRACT FROM AUTHOR]

It has been demonstrated that online consumer reviews are an important source of information that affect individuals' purchase decision making. To understand the influence of online reviews, this study extends prior research on information adoption by incorporating the perspective of herd behavior. We develop and empirically test a research model using data collected from an existing book review site. We report 2 major findings. First, argument quality and source credibility predict information usefulness, which affects the adoption of online reviews. Second, we determine that the adoption of online reviews is also influenced by 2 herd factors, namely, discounting own information and imitating others. We further identify the key determinants of these herd factors, including background homophily and attitude homophily. The theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Having reflected on the theoretical tradition of previous information inequality research that treats society's information rich/poor as identical with its socioeconomic rich/poor, this study examines the informational structure of contemporary Chinese urban society through a cluster analysis of a sample of 3,361 urban residents measured by a holistic informational measurement developed around the concept of 'an individual's information world.' It finds that, first, 4 groups, instead of a binary 'haves versus have-nots,' best characterize Chinese urban society informationally; second, the distribution of people among these groups conforms to normal distribution, in striking contrast with the pyramid-shaped socioeconomic structure of Chinese society; third, although the demographic characteristics of these groups suggest a significant correlation between people's informational and socioeconomic statuses, the 2 are far from identical; fourth, although the 4 groups differ in all aspects investigated, they differ most notably in information assets and the range and type of materials they choose as their regular information resources; fifth, although the 4 groups vary significantly, each differs from the others in its own way. This study concludes that society's informational and socioeconomic structures are 2 related but distinctive structures, and that the informational structure is characterized by highly complicated textures of inequality. [ABSTRACT FROM AUTHOR]