-
Zhang, Y.: ¬The effect of open access on citation impact : a comparison study based on Web citation analysis (2006)
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- Abstract
- The academic impact advantage of Open Access (OA) is a prominent topic of debate in the library and publishing communities. Web citations have been proposed as comparable to, even replacements for, bibliographic citations in assessing the academic impact of journals. In our study, we compare Web citations to articles in an OA journal, the Journal of Computer-Mediated Communication (JCMC), and a traditional access journal, New Media & Society (NMS), in the communication discipline. Web citation counts for JCMC are significantly higher than those for NMS. Furthermore, JCMC receives significantly higher Web citations from the formal scholarly publications posted on the Web than NMS does. The types of Web citations for journal articles were also examined. In the Web context, the impact of a journal can be assessed using more than one type of source: citations from scholarly articles, teaching materials and non-authoritative documents. The OA journal has higher percentages of citations from the third type, which suggests that, in addition to the research community, the impact advantage of open access is also detectable among ordinary users participating in Web-based academic communication. Moreover, our study also proves that the OA journal has impact advantage in developing countries. Compared with NMS, JCMC has more Web citations from developing countries.
-
Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009)
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- Abstract
- In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.
- Date
- 22. 3.2009 17:49:11
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
-
Zhang, X.; Fang, Y.; He, W.; Zhang, Y.; Liu, X.: Epistemic motivation, task reflexivity, and knowledge contribution behavior on team wikis : a cross-level moderation model (2019)
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- Abstract
- A cross-level model based on the information processing perspective and trait activation theory was developed and tested in order to investigate the effects of individual-level epistemic motivation and team-level task reflexivity on three different individual contribution behaviors (i.e., adding, deleting, and revising) in the process of knowledge creation on team wikis. Using the Hierarchical Linear Modeling software package and the 2-wave data from 166 individuals in 51 wiki-based teams, we found cross-level interaction effects between individual epistemic motivation and team task reflexivity on different knowledge contribution behaviors on wikis. Epistemic motivation exerted a positive effect on adding, which was strengthened by team task reflexivity. The effect of epistemic motivation on deleting was positive only when task reflexivity was high. In addition, epistemic motivation was strongly positively related to revising, regardless of the level of task reflexivity involved.
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.5, S.448-461
-
Zhang, Y.: ¬The influence of mental models on undergraduate students' searching behavior on the Web (2008)
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- Abstract
- This article explores the effects of undergraduate students' mental models of the Web on their online searching behavior. Forty-four undergraduate students, mainly freshmen and sophomores, participated in the study. Subjects' mental models of the Web were treated as equally good styles and operationalized as drawings of their perceptions about the Web. Four types of mental models of the Web were identified based on the drawings and the associated descriptions: technical view, functional view, process view, and connection view. In the study, subjects were required to finish two search tasks. Searching behavior was measured from four aspects: navigation and performance, subjects' feelings about tasks and their own performances, query construction, and search patterns. The four mental model groups showed different navigation and querying behaviors, but the differences were not significant. Subjects' satisfaction with their own performances was found to be significantly correlated with the time to complete the task. The results also showed that the familiarity of the task to subjects had a major effect on their ways to start interaction, query construction, and search patterns.
-
Zhang, Y.; Sun, Y.; Xie, B.: Quality of health information for consumers on the web : a systematic review of indicators, criteria, tools, and evaluation results (2015)
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- Abstract
- The quality of online health information for consumers has been a critical issue that concerns all stakeholders in healthcare. To gain an understanding of how quality is evaluated, this systematic review examined 165 articles in which researchers evaluated the quality of consumer-oriented health information on the web against predefined criteria. It was found that studies typically evaluated quality in relation to the substance and formality of content, as well as to the design of technological platforms. Attention to design, particularly interactivity, privacy, and social and cultural appropriateness is on the rise, which suggests the permeation of a user-centered perspective into the evaluation of health information systems, and a growing recognition of the need to study these systems from a social-technical perspective. Researchers used many preexisting instruments to facilitate evaluation of the formality of content; however, only a few were used in multiple studies, and their validity was questioned. The quality of content (i.e., accuracy and completeness) was always evaluated using proprietary instruments constructed based on medical guidelines or textbooks. The evaluation results revealed that the quality of health information varied across medical domains and across websites, and that the overall quality remained problematic. Future research is needed to examine the quality of user-generated content and to explore opportunities offered by emerging new media that can facilitate the consumer evaluation of health information.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2071-2084
-
Zhang, Y.; Li, X.; Fan, W.: User adoption of physician's replies in an online health community : an empirical study (2020)
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- Abstract
- Online health question-and-answer consultation with physicians is becoming a common phenomenon. However, it is unclear how users identify the most satisfying reply. Based on the dual-process theory of knowledge adoption, we developed a conceptual model and empirical method to study which factors influence adoption of a reply. We extracted 6 variables for argument quality (Ease of understanding, Relevance, Completeness, Objectivity, Timeliness, Structure) and 4 for source credibility (Physician's online experience, Physician's offline expertise, Hospital location, Hospital level). The empirical results indicate that both central and peripheral routes affect user's adoption of a response. Physician's offline expertise negatively affects user's adoption decision, while physician's online experience positively affects it; this effect is positively moderated by user involvement.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.10, S.1179-1191
-
Zhang, Y.; Broussard, R.; Ke, W.; Gong, X.: Evaluation of a scatter/gather interface for supporting distinct health information search tasks (2014)
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- Abstract
- Web search engines are important gateways for users to access health information. This study explored whether a search interface based on the Bing API and enabled by Scatter/Gather, a well-known document-clustering technique, can improve health information searches. Forty participants without medical backgrounds were randomly assigned to two interfaces: a baseline interface that resembles typical web search engines and a Scatter/Gather interface. Both groups performed two lookup and two exploratory health-related tasks. It was found that the baseline group was more likely to rephrase queries and less likely to access general-purpose sites than the Scatter/Gather group when completing exploratory tasks. Otherwise, the two groups did not differ in behavior and task performance, with participants in the Scatter/Gather group largely overlooking the features (key words, clusters, and the recluster function) designed to facilitate the exploration of semantic relationships between information objects, a potentially useful means for users in the rather unfamiliar domain of health. The results suggest a strong effect of users' mental models of search on their use of search interfaces and a high cognitive cost associated with using the Scatter/Gather features. It follows that novel features of a search interface should not only be compatible with users' mental models but also provide sufficient affordance to inform users of how they can be used. Compared with the interface, tasks showed more significant impacts on search behavior. In future studies, more effort should be devoted to identify salient features of health-related information needs.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1028-1041
-
Xu, H.; Bu, Y.; Liu, M.; Zhang, C.; Sun, M.; Zhang, Y.; Meyer, E.; Salas, E.; Ding, Y.: Team power dynamics and team impact : new perspectives on scientific collaboration using career age as a proxy for team power (2022)
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- Abstract
- Power dynamics influence every aspect of scientific collaboration. Team power dynamics can be measured by team power level and team power hierarchy. Team power level is conceptualized as the average level of the possession of resources, expertise, or decision-making authorities of a team. Team power hierarchy represents the vertical differences of the possessions of resources in a team. In Science of Science, few studies have looked at scientific collaboration from the perspective of team power dynamics. This research examines how team power dynamics affect team impact to fill the research gap. In this research, all coauthors of one publication are treated as one team. Team power level and team power hierarchy of one team are measured by the mean and Gini index of career age of coauthors in this team. Team impact is quantified by citations of a paper authored by this team. By analyzing over 7.7 million teams from Science (e.g., Computer Science, Physics), Social Sciences (e.g., Sociology, Library & Information Science), and Arts & Humanities (e.g., Art), we find that flat team structure is associated with higher team impact, especially when teams have high team power level. These findings have been repeated in all five disciplines except Art, and are consistent in various types of teams from Computer Science including teams from industry or academia, teams with different gender groups, teams with geographical contrast, and teams with distinct size.
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1489-1505
-
Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023)
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- Abstract
- Predicting a researcher's knowledge trajectories beyond their current foci can leverage potential inter-/cross-/multi-disciplinary interactions to achieve exploratory innovation. In this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation. The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer. A novel link prediction approach with a diffusion strategy is then used to capture the interactions between social elements (e.g., collaboration) and knowledge elements (e.g., technological similarity) in the process of exploratory innovation. This diffusion strategy differentiates the interactions occurring among homogeneous and heterogeneous nodes in the heterogeneous bibliometric network and weights the strengths of these interactions. Two sets of experiments-one with a local dataset and the other with a global dataset-demonstrate that the proposed method is prior to 10 selected baselines in link prediction, recommender systems, and upstream graph representation learning. A case study recommending knowledge trajectories of information scientists with topical hierarchy and explainable mediators reveals the proposed method's reliability and potential practical uses in broad scenarios.
- Date
- 22. 6.2023 18:07:12
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.7, S.775-790
-
Zhang, Y.: ¬The impact of Internet-based electronic resources on formal scholarly communication in the area of library and information science : a citation analysis (1998)
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- Abstract
- Internet based electronic resources are growing dramatically but there have been no empirical studies evaluating the impact of e-sources, as a whole, on formal scholarly communication. reports results of an investigation into how much e-sources have been used in formal scholarly communication, using a case study in the area of Library and Information Science (LIS) during the period 1994 to 1996. 4 citation based indicators were used in the study of the impact measurement. Concludes that, compared with the impact of print sources, the impact of e-sources on formal scholarly communication in LIS is small, as measured by e-sources cited, and does not increase significantly by year even though there is observable growth of these impact across the years. It is found that periodical format is related to the rate of citing e-sources, articles are more likely to cite e-sources than are print priodical articles. However, once authors cite electronic resource, there is no significant difference in the number of references per article by periodical format or by year. Suggests that, at this stage, citing e-sources may depend on authors rather than the periodical format in which authors choose to publish
- Date
- 30. 1.1999 17:22:22
- Source
- Journal of information science. 24(1998) no.4, S.241-254
-
Zhang, Y.; Liu, J.; Song, S.: ¬The design and evaluation of a nudge-based interface to facilitate consumers' evaluation of online health information credibility (2023)
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- Abstract
- Evaluating the quality of online health information (OHI) is a major challenge facing consumers. We designed PageGraph, an interface that displays quality indicators and associated values for a webpage, based on credibility evaluation models, the nudge theory, and existing empirical research concerning professionals' and consumers' evaluation of OHI quality. A qualitative evaluation of the interface with 16 participants revealed that PageGraph rendered the information and presentation nudges as intended. It provided the participants with easier access to quality indicators, encouraged fresh angles to assess information credibility, provided an evaluation framework, and encouraged validation of initial judgments. We then conducted a quantitative evaluation of the interface involving 60 participants using a between-subject experimental design. The control group used a regular web browser and evaluated the credibility of 12 preselected webpages, whereas the experimental group evaluated the same webpages with the assistance of PageGraph. PageGraph did not significantly influence participants' evaluation results. The results may be attributed to the insufficiency of the saliency and structure of the nudges implemented and the webpage stimuli's lack of sensitivity to the intervention. Future directions for applying nudges to support OHI evaluation were discussed.
- Date
- 22. 6.2023 18:18:34
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.7, S.828-845
-
Zhang, Y.; Ren, P.; Rijke, M. de: ¬A taxonomy, data set, and benchmark for detecting and classifying malevolent dialogue responses (2021)
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- Abstract
- Conversational interfaces are increasingly popular as a way of connecting people to information. With the increased generative capacity of corpus-based conversational agents comes the need to classify and filter out malevolent responses that are inappropriate in terms of content and dialogue acts. Previous studies on the topic of detecting and classifying inappropriate content are mostly focused on a specific category of malevolence or on single sentences instead of an entire dialogue. We make three contributions to advance research on the malevolent dialogue response detection and classification (MDRDC) task. First, we define the task and present a hierarchical malevolent dialogue taxonomy. Second, we create a labeled multiturn dialogue data set and formulate the MDRDC task as a hierarchical classification task. Last, we apply state-of-the-art text classification methods to the MDRDC task, and report on experiments aimed at assessing the performance of these approaches.
- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.12, S.1477-1497
-
Zhang, Y.: Toward a layered model of context for health information searching : an analysis of consumer-generated questions (2013)
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- Abstract
- Designing effective consumer health information systems requires deep understanding of the context in which the systems are being used. However, due to the elusive nature of the concept of context, few studies have made it a focus of examination. To fill this gap, we studied the context of consumer health information searching by analyzing questions posted on a social question and answer site: Yahoo! Answers. Based on the analysis, a model of context was developed. The model consists of 5 layers: demographic, cognitive, affective, situational, and social and environmental. The demographic layer contains demographic factors of the person of concern; the cognitive layer contains factors related to the current search task (specifically, topics of interest and information goals) and users' cognitive ability to articulate their needs. The affective layer contains different affective motivations and intentions behind the search. The situational layer contains users' perceptions of the current health condition and where the person is in the illness trajectory. The social and environmental layer contains users' social roles, social norms, and various information channels. Several novel system functions, including faceted search and layered presentation of results, are proposed based on the model to help contextualize and improve users' interactions with health information systems.
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1158-1172
-
Zhang, M.; Zhang, Y.: Professional organizations in Twittersphere : an empirical study of U.S. library and information science professional organizations-related Tweets (2020)
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- Abstract
- Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.4, S.491-496
-
Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020)
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- Abstract
- Millions of messages are produced on microblog platforms every day, leading to the pressing need for automatic identification of key points from the massive texts. To absorb salient content from the vast bulk of microblog posts, this article focuses on the task of microblog keyphrase extraction. In previous work, most efforts treat messages as independent documents and might suffer from the data sparsity problem exhibited in short and informal microblog posts. On the contrary, we propose to enrich contexts via exploiting conversations initialized by target posts and formed by their replies, which are generally centered around relevant topics to the target posts and therefore helpful for keyphrase identification. Concretely, we present a neural keyphrase extraction framework, which has 2 modules: a conversation context encoder and a keyphrase tagger. The conversation context encoder captures indicative representation from their conversation contexts and feeds the representation into the keyphrase tagger, and the keyphrase tagger extracts salient words from target posts. The 2 modules were trained jointly to optimize the conversation context encoding and keyphrase extraction processes. In the conversation context encoder, we leverage hierarchical structures to capture the word-level indicative representation and message-level indicative representation hierarchically. In both of the modules, we apply character-level representations, which enables the model to explore morphological features and deal with the out-of-vocabulary problem caused by the informal language style of microblog messages. Extensive comparison results on real-life data sets indicate that our model outperforms state-of-the-art models from previous studies.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.5, S.553-567
-
Zhang, Y.; Salaba, A.: What do users tell us about FRBR-based catalogs? (2012)
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- Abstract
- FRBR user research has been the least addressed area in FRBR research and development. This article addresses the research gap in evaluating and designing catalogs based on FRBR user research. It draws from three user studies concerning FRBR-based catalogs: (1) user evaluation of three FRBR-based catalogs, (2) user participatory design of a prototype catalog based on the FRBR model, and (3) user evaluation of the resulting FRBR prototype catalog. The major findings from the user studies are highlighted and discussed for future development of FRBR-based catalogs that support various user tasks.
- Content
- Contribution to a special issue "The FRBR family of conceptual models: toward a linked future"
-
Zhang, Y.: Beyond quality and accessibility : source selection in consumer health information searching (2014)
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- Abstract
- A systematic understanding of factors and criteria that affect consumers' selection of sources for health information is necessary for the design of effective health information services and information systems. However, current studies have overly focused on source attributes as indicators for 2 criteria, source quality and accessibility, and overlooked the role of other factors and criteria that help determine source selection. To fill this gap, guided by decision-making theories and the cognitive perspective to information search, we interviewed 30 participants about their reasons for using a wide range of sources for health information. Additionally, we asked each of them to report a critical incident in which sources were selected to fulfill a specific information need. Based on the analysis of the transcripts, 5 categories of factors were identified as influential to source selection: source-related factors, user-related factors, user-source relationships, characteristics of the problematic situation, and social influences. In addition, about a dozen criteria that mediate the influence of the factors on source-selection decisions were identified, including accessibility, quality, usability, interactivity, relevance, usefulness, familiarity, affection, anonymity, and appropriateness. These results significantly expanded the current understanding of the nature of costs and benefits involved in source-selection decisions, and strongly indicated that a personalized approach is needed for information services and information systems to provide effective access to health information sources for consumers.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.911-927
-
Ku, Y.; Chiu, C.; Zhang, Y.; Chen, H.; Su, H.: Text mining self-disclosing health information for public health service (2014)
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- Abstract
- Understanding specific patterns or knowledge of self-disclosing health information could support public health surveillance and healthcare. This study aimed to develop an analytical framework to identify self-disclosing health information with unusual messages on web forums by leveraging advanced text-mining techniques. To demonstrate the performance of the proposed analytical framework, we conducted an experimental study on 2 major human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) forums in Taiwan. The experimental results show that the classification accuracy increased significantly (up to 83.83%) when using features selected by the information gain technique. The results also show the importance of adopting domain-specific features in analyzing unusual messages on web forums. This study has practical implications for the prevention and support of HIV/AIDS healthcare. For example, public health agencies can re-allocate resources and deliver services to people who need help via social media sites. In addition, individuals can also join a social media site to get better suggestions and support from each other.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.928-947
-
Zhang, X.; Li, Y.; Liu, J.; Zhang, Y.: Effects of interaction design in digital libraries on user interactions (2008)
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- Abstract
- Purpose - This study aims to investigate the effects of different search and browse features in digital libraries (DLs) on task interactions, and what features would lead to poor user experience. Design/methodology/approach - Three operational DLs: ACM, IEEE CS, and IEEE Xplore are used in this study. These three DLs present different features in their search and browsing designs. Two information-seeking tasks are constructed: one search task and one browsing task. An experiment was conducted in a usability laboratory. Data from 35 participants are collected on a set of measures for user interactions. Findings - The results demonstrate significant differences in many aspects of the user interactions between the three DLs. For both search and browse designs, the features that lead to poor user interactions are identified. Research limitations/implications - User interactions are affected by specific design features in DLs. Some of the design features may lead to poor user performance and should be improved. The study was limited mainly in the variety and the number of tasks used. Originality/value - The study provided empirical evidence to the effects of interaction design features in DLs on user interactions and performance. The results contribute to our knowledge about DL designs in general and about the three operational DLs in particular.
- Source
- Journal of documentation. 64(2008) no.3, S.438-463
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Zhang, Y.: Undergraduate students' mental models of the Web as an information retrieval system (2008)
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- Abstract
- This study explored undergraduate students' mental models of the Web as an information retrieval system. Mental models play an important role in people's interaction with information systems. Better understanding of people's mental models could inspire better interface design and user instruction. Multiple data-collection methods, including questionnaire, semistructured interview, drawing, and participant observation, were used to elicit students' mental models of the Web from different perspectives, though only data from interviews and drawing descriptions are reported in this article. Content analysis of the transcripts showed that students had utilitarian rather than structural mental models of the Web. The majority of participants saw the Web as a huge information resource where everything can be found rather than an infrastructure consisting of hardware and computer applications. Students had different mental models of how information is organized on the Web, and the models varied in correctness and complexity. Students' mental models of search on the Web were illustrated from three points of view: avenues of getting information, understanding of search engines' working mechanisms, and search tactics. The research results suggest that there are mainly three sources contributing to the construction of mental models: personal observation, communication with others, and class instruction. In addition to structural and functional aspects, mental models have an emotional dimension.
- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2087-2098
