学术活动 | 2020 ASIS&T AP | 最佳长论文奖 最佳短论文奖
The following article is from DIM数据与信息管理 Author DIM编辑部
北京时间12月13日晚9点，2020年 ASIS&T AP会议圆满结束。在闭幕式上，武汉大学信息管理学院姜婷婷教授揭晓了本次会议的最佳长论文奖、最佳短论文奖以及提名奖。本次会议共收到55份论文投稿，录用23篇，包括14篇长文章和9篇短文章，录用率42%。经组委会评议，最终评选出最佳长论文奖1名，最佳短论文奖1名，最佳长论文提名奖2名，最佳短论文提名奖2名。扫描下文二维码可直接免费获取论文全文。
最佳长论文奖
How Users’ Gaze Behavior is Related to Their Quality Evaluation of a Health Website Based on HONcode Principles?
Citation: Qin, Q., Ke, Q., Du, J. T., & Xie, Y. (2021). How Users’ Gaze Behavior Is Related to Their Quality Evaluation of a Health Website Based on HONcode Principles?, Data and Information Management, 5(1), 75-85. doi: https://doi.org/10.2478/dim-2020-0045
Abstract: 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 selfreport 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.
最佳短论文奖
Examination of Effects of Time Constraint and Task Type on Users’ Query Typing Behaviors
Citation: Peng, H., Qian, Y., & Liu, C. (2021). Examination of Effects of Time Constraint and Task Type on Users’ Query Typing Behaviors, Data and Information Management, 5(1), 48-55. doi:
https://doi.org/10.2478/dim-2020-0034Abstract: 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.
最佳长论文提名奖
Exploring Public Response to COVID-19 on Weibo with LDA Topic Modeling and Sentiment Analysis
Citation: Xie, R., Chu, S. K. W., Chiu, D. K. W., & Wang, Y. (2021). Exploring Public Response to COVID-19 on Weibo with LDA Topic Modeling and Sentiment Analysis, Data and Information Management, 5(1), 86-99. doi:
https://doi.org/10.2478/dim-2020-0023Abstract: 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.
Characteristics of Open Government Data (OGD) Around the World: A Country-based Comparative Meta-Analysis
Citation: Tang, R., & Jiang, J. (2021). Characteristics of Open Government Data (OGD) Around the World: A Country-based Comparative Meta-Analysis, Data and Information Management, 5(1), 11-26. doi:
https://doi.org/10.2478/dim-2020-0026Abstract: In this paper, we report the results of a metaanalysis 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 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.
最佳短论文提名奖
A Comparison Study of Measures to Quantify the Evolution of Prolific Research Teams
Citation: Zou, B., & Wang, Y. (2021). A Comparison Study of Measures to Quantify the Evolution of Prolific Research Teams, Data and Information Management, 5(1), 56-64. doi:
Abstract: 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.
Examining User Perception and Usage of Voice Search
Citation: Sa, N., & Yuan, X. (. (2021). Examining User Perception and Usage of Voice Search, Data and Information Management, 5(1), 40-47. doi:
Abstract: 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.
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