Data and information management最新文献

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.

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.

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.

Digital storytelling, an innovative way of writing, has been introduced to young learners who are taught to construct stories with digital tools to convey their knowledge and ideas. In 2018 and 2019, 31 digital stories created by Hong Kong primary school students were published on a digital story writing platform and linked from an online gamified reading platform. Each book on average gained 4,000+ views from across the globe and received 3,000+ favorable comments in total. While the digital stories are popular in these platforms, their quality and education value are uncertain. A review of the literature shows there is a lack of robust tools for assessing digital stories by young authors. The research team for this paper thus constructed their own framework in evaluating digital stories. An assessment of the stories has been done by two capable assessors, who found that the stories overall were of good quality and suggested room for improvement. This paper made three contributions: (1) “invention” of a digital story assessment framework; (2) it shows that stories created by students (with support from educators) can be an enjoyable and useful educational resource for their peers; and (3) digital storytelling can help foster the development of young authors.

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.

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.

The current study investigates cooking hobbyists' information behavior with emphasis on the sources used and information activities performed in different situations and in different stages. Drawing upon Stebbins' serious leisure theory, Hektor's framework of information activities, and Hartel's cooking stages, a web survey was designed including a serious leisure scale, sets of questions asking various information sources consulted, and frequencies of information activities performed when “trying new recipes” and “making dishes once made before” in the “exploring stage” and “planning stage.” Four hundred eighty-seven cooking hobbyists participated in the survey. Results show that while most cooking hobbyists tend to obtain cooking information through online sources, but some cooking hobbyists with higher scores on the serious leisure scale also value print resources. They also engage in various information activities more frequently. Comparing to “dishes made before,” cooking hobbyists are more likely to seek information when “trying new recipes.” Nevertheless, the home recipe was the only source consulted more frequently when making dishes people once made before. Cooking hobbyists tend to browse and exchange information more frequently in the exploring stage when gathering cooking ideas rather than in the planning stage. Suggestions for food ingredients online shopping websites, recipe-recommendation systems, culinary bookstores, and special libraries were also provided and discussed based on the findings.

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.

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.

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.