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Investigating the knowledge structure of research on massively multiplayer online role-playing games: A bibliometric analysis 大型多人在线角色扮演游戏研究的知识结构调查——文献计量分析
Pub Date : 2022-11-24 DOI: 10.1016/j.dim.2022.100024
Seungjong Sun , Dongyan Nan , ShaoPeng Che , Jang Hyun Kim

As the concept of the Metaverse rapidly spread, massively multiplayer online role-playing game (MMORPG), one of the Metaverse games, received public's attention again. Additionally, MMORPGs have garnered significant academic interest in multidisciplinary fields, including human-computer interaction, computer science, and psychology. This study provides a general overview of the knowledge structures on MMORPGs in various academic fields using a bibliometric approach. To this end, we collected articles on MMORPGs published between 2001 and 2021 from the Web of Science. Then, main research forces in the field of MMORPGs are identified by examining productive authors, institutions, and countries/regions. Additionally, we applied VOSviewer to conduct co-citation analyses for identifying highly cited authors, journals, and literatures on MMORPGs. The results revealed that the USA and South Korea are the most productive countries. In addition, players' motivation, players' demographics, in-game social interaction, and pathological usage are the main research topics in the field. We expect that our results will help researchers and stakeholders to gain a general understanding of the development of the MMORPG academic field.

随着 "元宇宙 "概念的迅速传播,作为 "元宇宙 "游戏之一的大型多人在线角色扮演游戏(MMORPG)再次受到公众的关注。此外,MMORPG 在人机交互、计算机科学和心理学等多学科领域也引起了学术界的极大兴趣。本研究采用文献计量学方法对各学术领域中有关 MMORPG 的知识结构进行了概括。为此,我们从 Web of Science 收集了 2001 年至 2021 年间发表的有关 MMORPG 的文章。然后,通过研究有成果的作者、机构和国家/地区,确定了 MMORPG 领域的主要研究力量。此外,我们还应用 VOSviewer 进行了共引分析,以确定 MMORPG 的高被引作者、期刊和文献。结果显示,美国和韩国是高产国家。此外,玩家的动机、玩家的人口统计、游戏中的社交互动和病态使用也是该领域的主要研究课题。我们希望我们的研究结果能帮助研究人员和相关人士对 MMORPG 学术领域的发展有一个总体的了解。
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引用次数: 0
A review on method framework construction of Chinese Information Science 中国情报学方法框架构建述评
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100023
Bowen Li , Liang Tian , Yingyi Zhang , Heng Zhang , Chengzhi Zhang

As the unique academic culture in Chinese philosophy and social sciences, researches on method framework provide an opportunity for understanding the thinking model and value orientation of the ancient eastern civilization. The field of information science has achieved fruitful results in the method framework research closely related to the unique discipline history and academic mission. The paper reviews information science method frameworks in China and presents their academic features from three aspects: 1. levels of the framework, 2. research strategies, and 3. essential techniques. At the same time, we summarize the value of this Chinese academic wisdom and the practical experience of information science in China to promote this research.

方法框架研究作为中国哲学社会科学独特的学术文化,为理解东方古代文明的思维模式和价值取向提供了契机。信息科学领域在方法框架研究方面取得了丰硕的成果,这与它独特的学科历史和学术使命密切相关。本文综述了国内情报学方法框架,并从三个方面阐述了它们的学术特点:1.情报学方法框架;框架的层次,2。3.研究策略;基本技术。同时,总结这一中国学术智慧的价值和中国情报学的实践经验,推动这一研究。
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引用次数: 0
Collaborative Filtering system based on multi-level user clustering and aspect sentiment 基于多层次用户聚类和方面情感的协同过滤系统
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100021
Samin Poudel, Marwan Bikdash

A Collaborative Filtering (CF) method predicts an unknown overall rating of a target user towards an item based on the known overall ratings of the users that are similar to the target user. The similarity between two users is generally found based on their overall ratings toward items that both have reviewed. Two users may have similar overall ratings towards a given item, but different sentiments towards various aspects of the item. Understanding the effect of user sentiment towards specific aspects on overall ratings will sharpen estimates of user similarity as well as provide an rationale for making specific recommendations. We propose an Aspect-Sentiments based Multi-level Clustering of Users (ASMCU) approach that finds the multiple clusters of users similar to a specific user where similarity between users is based on various aspect sentiments. The proposed ASMCU CF approach can be used to predict both the overall ratings and the aspect-sentiments. The ASMCU based CF approach performed mostly better than and sometimes comparable to the eight well-established CF methods that rely only on the overall ratings or a particular aspect-sentiments. Note however that the ASMCU can also explicitly justify the recommendation in terms of aspect sentiments. We evaluated our approach using three datasets: One Hotel dataset and Two Beer datasets. The Hotel dataset involved six aspects and each Beer dataset has four aspects. Each dataset has one overall rating matrix and one sentiment tensor.

协同过滤(CF)方法基于已知的与目标用户相似的用户的总体评分来预测未知的目标用户对某项的总体评分。两个用户之间的相似性通常是基于他们对两个人都评论过的物品的总体评分来发现的。两个用户可能对给定的物品有相似的总体评分,但对物品的各个方面有不同的看法。理解用户对特定方面的情感对总体评分的影响,将提高对用户相似度的估计,并为提出具体建议提供依据。我们提出了一种基于方面情感的用户多级聚类(ASMCU)方法,该方法可以找到与特定用户相似的多个用户集群,其中用户之间的相似性基于各种方面情感。所提出的ASMCU CF方法可用于预测整体评级和方面情绪。基于ASMCU的CF方法通常比仅依赖于总体评级或特定方面-情绪的八种成熟的CF方法表现得更好,有时甚至可以与之媲美。但是请注意,ASMCU也可以根据方面的情绪明确地证明建议的合理性。我们使用三个数据集来评估我们的方法:一个酒店数据集和两个啤酒数据集。酒店数据集涉及六个方面,每个啤酒数据集有四个方面。每个数据集有一个总体评价矩阵和一个情感张量。
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引用次数: 2
Twenty important theories and applications of empirical research on IS 信息系统实证研究的二十个重要理论与应用
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100003
Chuanhui Wu , Shijing Huang
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引用次数: 0
The illusion of data validity: Why numbers about people are likely wrong 数据有效性的错觉:为什么关于人的数字可能是错误的
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100020
Bernard J. Jansen , Joni Salminen , Soon-gyo Jung , Hind Almerekhi

This reflection article addresses a difficulty faced by scholars and practitioners working with numbers about people, which is that those who study people want numerical data about these people. Unfortunately, time and time again, this numerical data about people is wrong. Addressing the potential causes of this wrongness, we present examples of analyzing people numbers, i.e., numbers derived from digital data by or about people, and discuss the comforting illusion of data validity. We first lay a foundation by highlighting potential inaccuracies in collecting people data, such as selection bias. Then, we discuss inaccuracies in analyzing people data, such as the flaw of averages, followed by a discussion of errors that are made when trying to make sense of people data through techniques such as posterior labeling. Finally, we discuss a root cause of people data often being wrong – the conceptual conundrum of thinking the numbers are counts when they are actually measures. Practical solutions to address this illusion of data validity are proposed. The implications for theories derived from people data are also highlighted, namely that these people theories are generally wrong as they are often derived from people numbers that are wrong.

这篇反思文章解决了研究关于人的数字的学者和实践者所面临的一个困难,即那些研究人的人想要关于这些人的数字数据。不幸的是,这种关于人的数字数据一次又一次地是错误的。为了解决这种错误的潜在原因,我们提出了分析人数的例子,即由人或关于人的数字数据得出的数字,并讨论了数据有效性的令人欣慰的错觉。我们首先通过强调在收集人员数据时可能存在的不准确,比如选择偏差,来奠定基础。然后,我们讨论了分析人员数据的不准确性,例如平均值的缺陷,然后讨论了通过后验标记等技术试图理解人员数据时所产生的错误。最后,我们讨论了人口数据经常出错的根本原因——认为数字是计数的概念难题,而实际上它们是测量。提出了解决这种数据有效性错觉的实际解决方案。本文还强调了从人口数据中得出的理论的含义,即这些人口理论通常是错误的,因为它们通常是从错误的人口数据中得出的。
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引用次数: 3
PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits 挑衅:毒性触发检测对话从前100子reddit
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100019
Hind Almerekhi , Haewoon Kwak , Joni Salminen , Bernard J. Jansen

Promoting healthy discourse on community-based online platforms like Reddit can be challenging, especially when conversations show ominous signs of toxicity. Therefore, in this study, we find the turning points (i.e., toxicity triggers) making conversations toxic. Before finding toxicity triggers, we built and evaluated various machine learning models to detect toxicity from Reddit comments.

Subsequently, we used our best-performing model, a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model that achieved an area under the receiver operating characteristic curve (AUC) score of 0.983 to detect toxicity. Next, we constructed conversation threads and used the toxicity prediction results to build a training set for detecting toxicity triggers. This procedure entailed using our large-scale dataset to refine toxicity triggers' definition and build a trigger detection dataset using 991,806 conversation threads from the top 100 communities on Reddit. Then, we extracted a set of sentiment shift, topical shift, and context-based features from the trigger detection dataset, using them to build a dual embedding biLSTM neural network that achieved an AUC score of 0.789. Our trigger detection dataset analysis showed that specific triggering keywords are common across all communities, like ‘racist’ and ‘women’. In contrast, other triggering keywords are specific to certain communities, like ‘overwatch’ in r/Games. Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.

在Reddit等以社区为基础的在线平台上推广健康的话语可能具有挑战性,尤其是当对话显示出有害的不祥迹象时。因此,在这项研究中,我们发现转折点(即毒性触发器)使对话有毒。在发现毒性触发因素之前,我们建立并评估了各种机器学习模型,以检测Reddit评论中的毒性。随后,我们使用了我们表现最好的模型,一个经过微调的双向编码器表示来自变压器(BERT)模型,该模型在接收者工作特征曲线(AUC)评分下的面积达到0.983,以检测毒性。接下来,我们构建对话线程,并使用毒性预测结果构建用于检测毒性触发器的训练集。这个过程需要使用我们的大规模数据集来完善毒性触发器的定义,并使用来自Reddit前100个社区的991,806个对话线程构建触发器检测数据集。然后,我们从触发检测数据集中提取了一组情感转移、主题转移和基于上下文的特征,利用它们构建了一个双嵌入biLSTM神经网络,该神经网络的AUC得分为0.789。我们的触发检测数据集分析显示,特定的触发关键词在所有社区中都很常见,比如“种族主义者”和“女性”。相比之下,其他触发关键词则是特定于特定社区,如r/Games中的“守望先锋”。这意味着毒性触发检测算法可以利用通用方法,但也必须针对特定社区定制检测。
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引用次数: 5
Analysis of interoperability, security and usability of digital repositories in Kenyan Institutions of Higher Learning 肯尼亚高等院校数字资源库的互操作性、安全性和可用性分析
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100011
Johnson Mulongo Masinde , Otuoma Sanya

Kenya has experienced a significant growth in the number of institutional repositories in the recent past. The number grew from a paltry two (2) in 2009 to 42 in August 2020. The growth is a positive indicator as repositories play a crucial role in solving some of the problems experienced in the broader area of scholarly communication. This study sought to establish the current extent to which institutions of higher learning in Kenya have established and implemented digital repositories, from a technical perspective. To achieve this goal, the study undertook a technical analysis of institutional repositories implemented by accredited universities in Kenya by the Commission for University Education as at June 2020. The analysis focused on numerous metrics on interoperability, security and usability of the analyzed institutional repositories. The study employed an exploratory approach to collecting the data. The data collected was stored on a MySQL database using the PhpMyAdmin tool. Data analysis was done by SQL querying and the result set copied to MS Excel for generation of graphical visualizations. From a total of 49 institutions examined, 34 (69%) had institutional repositories while 15 (39%) did not have institutional repositories. All the 34 institutions with repositories were using Dspace software. Of all the metrics analyzed, the study established that most of the institutional repositories did not implement essential features that improve interoperability, security and usability of their repository platforms. The study recommends either further training for repository managers or outsourcing of the technical process of establishing and maintaining functional institutional repositories. We further recommend more comprehensive studies to cover all the aspects of the FAIR principles of data management in Kenya.

肯尼亚在最近的过去经历了机构存储库数量的显著增长。这一数字从2009年微不足道的2个增加到2020年8月的42个。这种增长是一个积极的指标,因为知识库在解决更广泛的学术交流领域遇到的一些问题方面发挥了至关重要的作用。本研究试图从技术角度确定肯尼亚高等教育机构建立和实施数字知识库的当前程度。为了实现这一目标,该研究对截至2020年6月肯尼亚大学教育委员会认可的大学实施的机构知识库进行了技术分析。分析集中于所分析的机构存储库的互操作性、安全性和可用性方面的许多度量。该研究采用探索性方法收集数据。收集的数据使用PhpMyAdmin工具存储在MySQL数据库中。通过SQL查询完成数据分析,并将结果集复制到MS Excel中以生成图形可视化。在接受调查的49所院校中,34所(69%)拥有机构资料库,而15所(39%)没有机构资料库。所有34间拥有资料库的机构均使用Dspace软件。在分析的所有指标中,该研究确定了大多数机构存储库没有实现提高其存储库平台的互操作性、安全性和可用性的基本特性。该研究建议对存储库管理人员进行进一步的培训,或者将建立和维护功能性机构存储库的技术过程外包出去。我们进一步建议进行更全面的研究,以涵盖肯尼亚公平数据管理原则的所有方面。
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引用次数: 4
Gain-framed product descriptions are more appealing to elderly consumers in live streaming E-commerce: Implications from a controlled experiment 在电子商务直播中,增益框架的产品描述对老年消费者更有吸引力:来自一项对照实验的启示
Pub Date : 2022-10-01 DOI: 10.1016/j.dim.2022.100022
Zhumo Sun , Shiting Fu , Tingting Jiang

Live streaming e-commerce has become increasingly popular among elderly consumers. This new form of online shopping allows the elderly, who might be less effective in making purchase decisions than younger people, to better understand the products sold through the comprehensive descriptions provided by the anchors. This study is interested in investigating the effects of the gain-loss framing of product descriptions on the elderly's purchase intention. A total of 36 participants between the ages of 60 and 70 were invited to watch a number of live streaming videos involving either gain- or loss-framed product descriptions in a controlled experiment. The results show that the gain-framed descriptions of the products engendered significantly higher purchase intention among the participants than the loss-framed ones. In particular, the gain-framed descriptions were effective for the participants with high approach motivation, but not for those with low approach motivation, which suggests the significant moderating effect of approach motivation. This study focused on the elderly customers whose life quality can be greatly enhanced by live streaming e-commerce. The findings not only add to the knowledge about the effects of message framing, but also provide useful implications for live-streaming e-commerce practitioners to increase the persuasiveness of their product descriptions.

电商直播在老年消费者中越来越受欢迎。这种新形式的网上购物可以让老年人更好地通过主播提供的全面描述了解所售产品,而老年人在做出购买决定时可能不如年轻人有效。本研究旨在探讨产品描述的得失框架对老年人购买意愿的影响。在一项对照实验中,共有36名年龄在60到70岁之间的参与者被邀请观看一些直播视频,其中包括增益或损失框架的产品描述。结果表明,增益框架的产品描述显著高于损失框架的产品描述。其中,增益框架描述对高趋近动机的被试有效,对低趋近动机的被试无效,说明趋近动机具有显著的调节作用。本研究针对的是可以通过电商直播极大提升生活质量的老年客户。这些发现不仅增加了对信息框架影响的认识,而且为直播电子商务从业者增加产品描述的说服力提供了有用的启示。
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引用次数: 1
Empowering linked data in cultural heritage institutions: A knowledge management perspective 赋予文化遗产机构关联数据权力:知识管理视角
Pub Date : 2022-07-01 DOI: 10.1016/j.dim.2022.100013
Lei Zhang

This reported research explores the barriers and challenges in linked data implementation in cultural heritage institutions, i.e., libraries, archives, and museums. Various data were collected from different sources regarding the linked data use cases related to libraries, archives, and museums over the past decade and analyzed from multiple facets. The analysis revealed very few activities of effective knowledge management in the linked data implementation and suggested that the crucial role of knowledge management and innovation should deserve enough attention in linked data projects and services. The findings will add value to the literature on knowledge management in the context of linked data and the semantic web.

本报告探讨了在文化遗产机构(即图书馆、档案馆和博物馆)中实施关联数据的障碍和挑战。在过去十年中,我们从不同来源收集了与图书馆、档案馆和博物馆相关的关联数据用例的各种数据,并从多个方面进行了分析。分析表明,在关联数据实施中,有效的知识管理活动很少,并建议在关联数据项目和服务中,知识管理和创新的关键作用应得到足够的重视。这些发现将为关联数据和语义网背景下的知识管理文献增加价值。
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引用次数: 3
Knowledge management and innovation 知识管理与创新
Pub Date : 2022-07-01 DOI: 10.1016/j.dim.2022.100018
Lu An, Alton Y.K. Chua, Md Anwarul Islam
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引用次数: 0
期刊
Data and information management
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