rss_2.0Library and Information Science, Book Studies FeedSciendo RSS Feed for Library and Information Science, Book Studieshttps://www.sciendo.com/subject/LBhttps://www.sciendo.comLibrary and Information Science, Book Studies Feedhttps://www.sciendo.com/subjectImages/Library_Information_&_Science,_Book_Studies.jpg700700A Comparison Study of Measures to Quantify the Evolution of Prolific Research Teamshttps://sciendo.com/article/10.2478/dim-2020-0028<abstract><title style='display:none'>Abstract</title><p>Scientific research teams play an increasingly significant role in scientific activities. To better understand the dynamic evolution process of research teams, we explored measures that quantify the evolution of prolific research teams. We collected our data from the Web of Science in the field of artificial intelligence, and applied the label propagation algorithm to identify research teams in the co-authorship network. The Top 1‰ prolific teams were selected as our research object, whose node stability and two types of edge stabilities were measured. The results show that prolific teams are much more stable during the evolution process, in terms of both member and membership stability. The measure of stability has varying degrees of impact on teams with different sizes, and small-sized teams get considerably different stability results by different measures.</p></abstract>ARTICLE2020-10-28T00:00:00.000+00:00Cross-Language Fake News Detectionhttps://sciendo.com/article/10.2478/dim-2020-0025<abstract><title style='display:none'>Abstract</title><p>With increasing globalization, news from different countries, and even in different languages, has become readily available and has become a way for many people to learn about other cultures. As people around the world become more reliant on social media, the impact of fake news on public society also increases. However, most of the fake news detection research focuses only on English. In this work, we compared the difference between textual features of different languages (Chinese and English) and their effect on detecting fake news. We also explored the cross-language transmissibility of fake news detection models. We found that Chinese textual features in fake news are more complex compared with English textual features. Our results also illustrated that the bidirectional encoder representations from transformers (BERT) model outperformed other algorithms for within-language data sets. As for detection in cross-language data sets, our findings demonstrated that fake news monitoring across languages is potentially feasible, while models trained with data from a more inclusive language would perform better in cross-language detection.</p></abstract>ARTICLE2020-11-20T00:00:00.000+00:00International Cooperation Among Artificial Intelligence Research Teams Based on Regional Cooperation Modelshttps://sciendo.com/article/10.2478/dim-2020-0036<abstract><title style='display:none'>Abstract</title><p>The paper explores the regional cooperation model and the differences among artificial intelligence research teams. It is helpful to reveal the status and strategies of scientific cooperation models across regions or within regions. We identified the world of artificial intelligence research teams with co-authorship network, and then identified the leading team based on the Number of Publications, Number of Citations, H-index, Weighted Degree Centrality, Betweenness Centrality, and Closeness Centrality. Based on the identified artificial intelligence research leading teams, this paper divides different types of cooperation models by region and comprehensively analyzed the three aspects of geographical distribution, cooperation indicators, and cooperation topics in the research teams from the perspective of comparisons. In order to find the international gap between China and other countries, we still highlight the difference between China's participation and non-participation in cooperation. The research results show that Chinese and their foreign research maintain close ties with major scientific research countries; international cooperation is widespread and is conducive to crossing into the leading team; China's domestic cooperation is higher than in other countries, and their domestic cooperation research is mainly manifested in the data processing and application level, while the core technology and basic algorithm levels need to cooperate with foreign countries.</p></abstract>ARTICLE2020-11-07T00:00:00.000+00:00An Empirical Study on the Cueing Effect of the Emotional Post Title in a Virtual Communityhttps://sciendo.com/article/10.2478/dim-2020-0024<abstract><title style='display:none'>Abstract</title><p>In a virtual community, the behavior of strengthening the emotion of a post title to draw attention of users is not uncommon, which can affect the overall performance of the information environment. This study focuses on exploring the influence of the emotional information of a post title on the users’ community perceived value in a virtual community. Based on the cue utilization theory, we propose a framework with several hypotheses. Data are collected using the experimental method from the college student sample in our study, and numerous tests are performed to analyze the data and verify the hypotheses. At the end of the study, it is found that the emotional information of the post title reduces the user community perceived financial value and it improves the user community perceived recreational value. The analysis of the mediating role reveals that emotional involvement facilitates the relationship between emotional information of post titles and user community perceived recreational value. This study adds a new dimension by discussing the user community value perception on post title expression and it reveals the conflict of interest between the manager of the virtual community and the producers of the post. Our findings may also provide guidelines and references for virtual community managers. Specifically, they should view the behavior of making post titles more emotional critically, and choose specific information management strategies based on the different value pursuit of community users.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Analysis of User Social Support Network in Online Tumor Communityhttps://sciendo.com/article/10.2478/dim-2020-0040<abstract><title style='display:none'>Abstract</title><p>With the development of Internet technology, online health forums have become indispensable for people who seek non-professional health support. This research focuses on the content posted by cancer patients and their relatives in online health forums and social networks to raise the following research questions: What is the overall view of the social support network in the online tumor community? What are the information behaviors of the online tumor community in different identities of users? How users interact in this community and build this network of social support? What are the topics users would like to share and talk about? What kinds of users could be the key users in this community? Method: Using the post and comment data of the Oncology Forum of Tianya Hospital in 2019, combined with social network analysis and word co-occurrence network analysis, the following conclusions are obtained: (1) There are some central points in the overall social support network, and there are central users consistent with other social networks. (2) Positive users are more likely to comment on others, and it is easier to get others’ comments, while negative users are more likely to share personal information and do not want to participate more in social interaction. (3) Users focus on posting emotional and emotional content in content sharing. Information-based social support information. The social support experience that this type of information brings to users can be positive and negative. (4) The most active group in the patients’ online health community, followed by the patients’ children. (5) The relationship between users and patients is diverse and there are two types of singularity. Users with diverse relationships are more likely to be commented on, and they are more willing to comment on users who also have diverse relationships.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Examination of Effects of Time Constraint and Task Type on Users’ Query Typing Behaviorshttps://sciendo.com/article/10.2478/dim-2020-0034<abstract><title style='display:none'>Abstract</title><p>Contextual factors have been found to be an important factor in information searching behaviors, however, little attention has been paid to the influence of contextual factors on users’ query typing behaviors. This study aims to explore the influence of two different contextual factors (with or without time constraint and two kinds of task type) on users’ query typing behaviors. We recruited 40 college students and conducted a user experiment, in which each participant completed two types of search tasks (Fact Finding and Information Understanding) in two different time conditions. The results show that time constraint encourages users to increase their query typing speed. Furthermore, the task type affects query length and rate of keystroke errors.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Exploring Occupation Differences in Reactions to COVID-19 Pandemic on Twitterhttps://sciendo.com/article/10.2478/dim-2020-0032<abstract><title style='display:none'>Abstract</title><p>Coronavirus disease 2019 (COVID-19) pandemic-related information are flooded on social media, and analyzing this information from an occupational perspective can help us to understand the social implications of this unprecedented disruption. In this study, using a COVID-19-related dataset collected with the Twitter IDs, we conduct topic and sentiment analysis from the perspective of occupation, by leveraging Latent Dirichlet Allocation (LDA) topic modeling and Valence Aware Dictionary and sEntiment Reasoning (VADER) model, respectively. The experimental results indicate that there are significant topic preference differences between Twitter users with different occupations. However, occupation-linked affective differences are only partly demonstrated in our study; Twitter users with different income levels have nothing to do with sentiment expression on covid-19-related topics.</p></abstract>ARTICLE2020-10-28T00:00:00.000+00:00Examining User Perception and Usage of Voice Searchhttps://sciendo.com/article/10.2478/dim-2020-0046<abstract><title style='display:none'>Abstract</title><p>With the development of mobile technologies, voice search is becoming increasingly important in our daily lives. By investigating the general usage of voice search and user perception about voice search systems, this research aims to understand users’ voice search behavior. We are particularly interested in how users perform voice search, their topics of interest, and their preference toward voice search. We elicit users’ opinions by asking them to fill out an online survey. Results indicated that participants liked voice search because it was convenient. However, voice search was used much less frequently than keyboard search. The success rate of voice search was low, and the participants usually gave up voice search or switched to keyboard search. They tended to perform voice search when they were driving or walking. Moreover, the participants mainly used voice search for simple tasks on mobile devices. The main reasons why participants disliked voice search are attributed to the system mistakes and the fact that they were unable to modify the queries.</p></abstract>ARTICLE2020-12-01T00:00:00.000+00:00Place, Practice, and Flow: Information Practices in the Mahamevnawa Buddhist Monasteryhttps://sciendo.com/article/10.2478/dim-2020-0049<abstract><title style='display:none'>Abstract</title><p>This paper presents the findings of a study exploring the information practices of members of a religious organization. Its focus is the “Mahamevnawa Buddhist Monastery.” Particularly, this paper focuses on the study's findings in relation to participants’ information practices in constructing their understanding of “the Temple.” The study is informed by an information practices theoretical perspective, drawing on work from a variety of disciplines, including Castells’ <italic>space of flows</italic>, and Fisher's <italic>information grounds</italic>. Data was gathered from participant observation, interviews with both monks and devotees and email follow-ups, and analysis of the online presence of the temple through its website. Five social constructs for the temple appear frequently in the interviews: <italic>Virtual space</italic>; <italic>Physical/geographical place</italic>; <italic>Virtual space; Symbol</italic>; <italic>Process and practices</italic>; and <italic>Organization</italic>. Participants’ information practices are not only limited to spiritual purposes but also are linked to various social practices, activities, and interests. The study's findings suggest that constructions of place play a hitherto underexplored role in the multi-layered relationship between people and information.</p></abstract>ARTICLE2020-12-01T00:00:00.000+00:00How Users’ Gaze Behavior Is Related to Their Quality Evaluation of a Health Website Based on HONcode Principles?https://sciendo.com/article/10.2478/dim-2020-0045<abstract><title style='display:none'>Abstract</title><p>While the health website is an easily accessible source for patients to use when seeking health information, the quality of online health information has been a critical issue that concerns all stakeholders in healthcare. The aim of this research was to examine the relationship between users’ evaluation of the health website quality and their gaze behavior on the web pages. Eye tracking and a self-report questionnaire based on the HONcode principles were used to address the objective. We found that (1) the evaluations of authority, privacy, financial disclosure, and advertising policy are positively correlated with the fixation count and total fixation duration toward corresponding page components, while the evaluations of complementarity and attribution are negatively correlated with the fixation count and total fixation duration to corresponding page components; and (2) the fixation count and total fixation duration toward health information sources are negatively related to the evaluation of health website quality, while the fixation count and total fixation duration to site owner are positively related to the quality evaluation. Users’ attention to page components is closely related to the evaluation of principles, and also has a certain impact on the overall quality evaluation of a health website. Based on the findings, our research may serve to improve the health website design and be a foundation to develop an automatic evaluation approach of the health website quality.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Factors Influencing User Behavior Intention to Use Mobile Library Application: A Theoretical and Empirical Research based on Grounded Theoryhttps://sciendo.com/article/10.2478/dim-2020-0037<abstract><title style='display:none'>Abstract</title><p>User behavior intention is an important evaluation criterion for the construction of mobile library application. To help libraries and mobile application, developers better understand factors influencing user behavior intention and jointly improve the mobile service quality of library. Based on grounded theory, this study experimentally manipulates user behavior intention to use mobile library application related to the survey questionnaire that was designed to obtain data from college teachers and students. The results showed that the user behavior intention to use mobile library application is mainly influenced by system feature (i.e., accessibility, relevance, and system help), interface feature (i.e., screen design, navigation, and term), and individual difference (i.e., performance expectancy, domain knowledge, and social influence). Furthermore, system feature and interface feature are the external driver of user's usage behavior intention, and individual difference is the internal driver of user's usage behavior intention.</p></abstract>ARTICLE2020-10-31T00:00:00.000+00:00Visualization of Emergency Needs Posted on Social Media by Metaphor Maphttps://sciendo.com/article/10.2478/dim-2020-0021<abstract><title style='display:none'>Abstract</title><p>Thematic analysis based on a social network is one of the effective means in emergency management. To improve users’ understanding, the results of the thematic analysis are often displayed through visualization. However, the previous researches on text theme visualization rarely considered the unified representation of theme structure and theme evolution. Cognitive load leads to difficulty, and it happens due to the separate representation of structure and evolution relationship and it still increases because of the characteristics of urgency, uncertainty, etc. Therefore, a metaphor map is introduced in this study to overcome the limits of previous visualization tools in characterizing the structure and evolutionary relationship of emergency. On the one hand, different elements in the metaphor map represent the information of popularity and structure of the demand, respectively. On the other hand, the visual design based on the metaphor map strengthens the representation of the content and evolution states of the demand themes. At the theoretical level, a visualization method for emergency needs based on the metaphor map is proposed in this study, which enriches the theory of emergency information visualization. At the practical level, this study explores the design of a visualization system based on the metaphor map under crisis scenarios, which enhances the interaction between users and crisis information, and provides references for decision-making such as emergency material scheduling and emergency resource coordination.</p></abstract>ARTICLE2020-10-17T00:00:00.000+00:00Characteristics of Open Government Data (OGD) Around the World: A Country-based Comparative Meta-Analysishttps://sciendo.com/article/10.2478/dim-2020-0026<abstract><title style='display:none'>Abstract</title><p>In this paper, we report the results of a meta-analysis of 50 publications on international Open Government Data (OGD) practices instantiated via their OGD sites or portals. Specific information about 67 individual countries’/regions’ OGD sites was extracted and compared, including the levels of OGDs, the number and types of data formats, the number of datasets, and the number and types of data categories. Upon comparing the data characteristics by types and countries, the top 10 countries/regions based on the number of data formats, datasets, and data categories were presented. Significant correlations were found among individual countries’ number of data formats, datasets, and data categories. Follow-up research that examines, confirms, and traces the data processing capacity of international OGDs is currently underway.</p></abstract>ARTICLE2020-11-20T00:00:00.000+00:00Language and Intercultural Information Ethics Concepts: A Preliminary Discussion of Privacyhttps://sciendo.com/article/10.2478/dim-2020-0027<abstract><title style='display:none'>Abstract</title><p>This paper introduces the perspective to understand privacy via language as an intercultural information ethics (IIE) concept. This research perspective carries two goals: to understand privacy as an IIE concept and to do so via natural language. The paper suggests that studying privacy through language answers the challenge faced by IIE work; in addition, studying privacy as an information ethics concept through language seems most appropriate considering that language both embodies and shapes meaning. Specifically, this paper briefly discusses privacy and some of its language expressions in the Chinese and English languages, through which it hopes to reveal the richness and possibilities of using natural language as a research instrument to understand privacy in intercultural settings, which is an area of researching privacy that has attracted little discussion so far.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Factors Influencing the Health Behavior During Public Health Emergency: A Case Study on Norovirus Outbreak in a Universityhttps://sciendo.com/article/10.2478/dim-2020-0022<abstract><title style='display:none'>Abstract</title><p>It is known that health belief and health literacy are closely related to health behavior. But, we do not know explicitly how health belief and health literacy interact with each other and determine health behavior change under public health emergencies (PHE). Through the integration of constructs from health belief model (perceived susceptibility, severity, benefits, barriers, and self-efficacy) and diverse dimensions of health literacy (functional, interactive and critical), a research framework is proposed to examine the underlying mechanism of health behavior change during PHE. Structural equation modeling (SEM) was used to analyze 386 questionnaire data collected from Chinese university students for the research framework. The analysis results show that (1) both health belief and health literacy have significant impacts on health behavior change during PHE. However, health belief plays a mediating role which affects the health literacy's impact on health behavior; (2) while the increase of perceived severity of disease and self-efficacy promote the health behavior change, the effectiveness of perceived susceptibility on health behavior depends on the increase of perceived severity; and (3) the enhancement of interactive health literacy effectively promotes health behavior change, while functional and critical health literacy reduces the blind change. The results throw lights on health education services and provide references and factors in understanding and encouraging health behavior changes to relevant stakeholders including social media operators, practitioners, social service providers, and policy makers.</p></abstract>ARTICLE2020-11-06T00:00:00.000+00:00Exploring Public Response to COVID-19 on Weibo with LDA Topic Modeling and Sentiment Analysishttps://sciendo.com/article/10.2478/dim-2020-0023<abstract><title style='display:none'>Abstract</title><p>It is necessary and important to understand public responses to crises, including disease outbreaks. Traditionally, surveys have played an essential role in collecting public opinion, while nowadays, with the increasing popularity of social media, mining social media data serves as another popular tool in opinion mining research. To understand the public response to COVID-19 on Weibo, this research collects 719,570 Weibo posts through a web crawler and analyzes the data with text mining techniques, including Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis. It is found that, in response to the COVID-19 outbreak, people learn about COVID-19, show their support for frontline warriors, encourage each other spiritually, and, in terms of taking preventive measures, express concerns about economic and life restoration, and so on. Analysis of sentiments and semantic networks further reveals that country media, as well as influential individuals and “self-media,” together contribute to the information spread of positive sentiment.</p></abstract>ARTICLE2020-11-27T00:00:00.000+00:00Information Search Trail Recommendation Based on Markov Chain Model and Case-based Reasoninghttps://sciendo.com/article/10.2478/dim-2020-0047<abstract><title style='display:none'>Abstract</title><p>An information search trail recommendation method based on the Markov chain model and case-based reasoning is proposed. A laboratory user experiment was designed to evaluate the proposed method. The experimental results demonstrated that novice searchers have a positive attitude toward the search trail recommendation and a willingness to use the recommendation. Importantly, this study found that the search trail recommendation could effectively improve novice searchers’ search performance. This finding is mainly reflected in the diversity of information sources and the integrity of the information content of the search results. The proposed search trail recommendation method extends the application scope of information recommendations and provides insights to improve the organization and management of online information resources.</p></abstract>ARTICLE2020-12-01T00:00:00.000+00:00Public Sector Employee Perspective towards Adoption of E-Government in Pakistan: A Proposed Research Agendahttps://sciendo.com/article/10.2478/dim-2020-0029<abstract><title style='display:none'>Abstract</title><p>Governments across the globe are continually working to improve infrastructure for their people. Today, the precise and accurate understanding of the factors that significantly affect public sector employees is one of the utmost crucial challenges for the adoption of e-government services in Pakistan. Without adequate knowledge of these factors, the level of welcome to new services or technology would not be predictable. The study targets employees in the public sector who provide e-government services in Pakistan. On a theoretical basis, Technology Acceptance Model (TAM) examined the effect of ease of use on attitudes, perceived usefulness, and trust and its effect on the public sector employees intent to adopt an e-government system. This research aimed to identify the factors that influence the adoption of e-government services by public sector employees in Pakistan. Data for this survey can be obtained from public sector employees in Pakistan. The results of this study are projected to show that the proposed framework is useful in evaluating the adoption of the e-government system in public sector employees and that the expanding new factor, trust, and attitude in this model are of essential importance.</p></abstract>ARTICLE2020-11-20T00:00:00.000+00:00Research on Influencing Factors of Personal Information Disclosure Intention of Social Media in Chinahttps://sciendo.com/article/10.2478/dim-2020-0038<abstract><title style='display:none'>Abstract</title><p>The disclosure of personal information by users is very important for social media, in order to balance privacy protection and personalized service. This article probes into the factors influencing users’ disclosure intention. Based on the privacy calculus theory and theory of planned behavior, the study constructs an influencing factor model of social media personal information disclosure intention. Then an extensive survey of social media users is conducted through questionnaire, and the hypothetical model is verified using structural equation model, and finally the relationship between various influencing factors and personal information disclosure intentions is obtained. The results show that the perceived benefits and subjective norm are related to personal information disclosure intentions, and privacy view is associated with perceived risk. Finally, the study provides new ideas for social media services and user privacy protection, such as creating a secure social media environment, increasing valuable social services, reducing users’ risk perception and making information processing open and transparent.</p></abstract>ARTICLE2020-11-07T00:00:00.000+00:00Exploring Significant Characteristics and Models for Classification of Structure Function of Academic Documentshttps://sciendo.com/article/10.2478/dim-2020-0031<abstract><title style='display:none'>Abstract</title><p>With the increasing abundance of literature resources, how to acquire knowledge elements efficiently and accurately is the key to achieving accurate literature retrieval and utilization of available literature resources. The identification of the structure function of academic documents is a fundamental work to meet the above requirements. In this study, the proceedings of the Association for Computational Linguistics (ACL) conferences are used as the primitive corpus, and the training corpus of chapter category is obtained by manual annotation. Based on the chapter titles and the in-chapter texts, traditional machine learning and deep learning models are both used for classifier training. Our results show that the title of a chapter is more beneficial to the identification of the structure function of academic documents than the in-chapter texts. The highest F<sub>1</sub> value in our experiments is 0.9249, which is obtained on the traditional logistic regression (LR) and support vector machine (SVM) models (slightly higher than on the convolutional neural network [CNN]). And through the experiment of adding other chapter characteristics based on the traditional model, we find that combining the relative position of chapters can effectively improve the classification performance. Finally, this study compares the results of experimental groups with different methods, analyzes the misclassification of the structure function of academic documents, and points out the main direction to improve the classification performance in the future.</p></abstract>ARTICLE2020-11-07T00:00:00.000+00:00en-us-1