D. Soergel and P. Zhang, “Design of a sensemaking assistant to support learning,” in The Future of Education, 2020.Abstract
Thinking tools that assist by externalizing thought processes and conceptual structures so they can be manipulated potentially improve user learning. We propose the design of a sensemaking assistant that integrates many such tools. Our design emerged from an intensive study of sensemaking by users working on real tasks, providing a link from users to developers. Sensemaking is the process of forming meaningful representations and working with them to gain understanding, possibly communicated in a report, to support planning, decision‑making, problem‑solving, and informed action. At the heart of our design is a set of tightly integrated tools for representing and manipulating a conceptual space: tools for producing and maintaining concept maps, causal maps/influence diagrams, argument maps, with support through self-organizing semantic maps, importing concepts and relationships from external Knowledge Organization Systems, and inferring connections between texts; further a tool for organizing information items (documents, text passages notes, images) linked to the concept map. The sensemaking assistant we envision guides users through the sensemaking process; for each function it suggests appropriate cognitive processes and provides tools that automate tasks. The comprehensive sensemaking model introduced in specifies functions in the iterative process of sensemaking: Task analysis and planning; Gap identification (tools for both: brainstorming, finding documents on the task); information acquisition, data seeking and structure seeking (search tool: finding databases, query expansion, passage retrieval; summarization tool); information organization, building structure, instantiating structure, information synthesis / new ideas / emerging sense (conceptual space tools mentioned above); information presentation, creating reports (from concept map to outline, guide through the writing process, analyze draft writing for coherence and clarity). The system tracks sources. Users using a sensemaking assistant may well internalize good ways for intellectual processes and good conceptual organization in addition to learning a useful application. The paper will provide some evidence from the literature and propose further testing.
J. Liu, J. An, and P. Zhang, “Analyzing opinion conflicts in an online group discussion: From the perspective of majority and minority influence,” iConference 2020. iSchools, 2020. 访问链接Abstract
Online community and groups often experience heated discussion. This paper examines a WeChat group discussion from the perspective of majority and minority influence to explore the evolvement of the discussion and the be-haviors of group members. Content analysis of 515 messages suggests that opin- ion conflicts between majority and minority evoke discussion engagement and knowledge exchange. There are different patterns of knowledge construction expressions between majority and minority groups. The majority prefer egocentric expression, while the minority prefer allocentric expression. Majority opinion holders have different conflict handling styles compared to minority opinion holders, who are more likely to avoid. Minority group is under great pressure in social interaction, they are easier to receive unfair comments and personal attacks.
X. Chen, Y. Yang, and P. Zhang, “Examining scholars' activity on a Chinese blogging and academic social network site,” iConference 2020. iSchools, 2020.
J. Liu and P. Zhang, “How to Initiate a Discussion Thread?: Exploring Factors Influencing Engagement Level of Online Deliberation”. Springer International Publishing, pp. 220-226, 2020.Abstract
Online platforms provide a public sphere for discussion, debate, and deliberation among citizens. The engagement of online deliberation enables participants to exchange viewpoints and form communities. This paper aims to explore the influencing factors on engagement level of online deliberation by examining the relationship between an initial post’s content features and length and the engagement of the discussion thread it initiates. We sampled 254 discussion threads with 254 initial posts and 2934 following posts and conducted quantitative and qualitative analysis of the posts. Findings show that initial posts which are longer and allocentric (as opposed to egocentric) would evoke longer following posts in a discussion. Different content type (social interaction, claim, argument) of initial posts would lead to significant different engagement, arguments would trigger higher level engagement (average posts per participant and average length of posts in discussions). Whether an initial post holds a clear position has no significant impact on discussion engagement. These findings contribute to a deeper understanding of online deliberation and its engagement and can be useful in promoting engagements in online deliberation.
W. Huang, J. Liu, H. Bai, and P. Zhang, “Value assessment of companies by using an enterprise value assessment system based on their public transfer specification,” Information Processing and Management, vol. 57, no. 5, 2020.
张璐, 张鹏翼, and 刘畅, “协同搜索过程中用户交流内容与模式研究,” 图书情报知识, no. 03, pp. 51-62, 2020.AbstractPKU 
[目的/意义]旨在分析协同搜索用户在信息搜索任务过程中的交流内容与模式,从而理解协同搜索用户的关注重点与搜索过程。[研究设计/方法]基于书籍交互检索平台(CLEF-Social Book Search)设计实验,共招募18名被试完成两种搜索任务,通过录音记录对话并对其进行编码和分析,总结交流内容特征和模式。结合任务类型、认知类型组合、服务器记录的搜索交互行为日志以及问卷收集的搜索体验进行了探索分析。[结论/发现]从交流内容上看,协同搜索用户主要理解与评判书目信息、商讨搜索任务计划;比起认知类型不同的用户,相同认知类型的用户在操作交互方面交流更多,在评判决策方面交流较少。交流模式依据讨论内容比重可分为理解评判型、评判主导型、均衡交流型三种,评判主导型用户的任务完成满意度最高。[创新/价值]协同搜索用户的交流反映出搜索过程中需要与同伴商讨协同的焦点,也是需要系统提供协助的重点,给协同搜索系统设计提供一定参考。本研究针对协同搜索的交流内容设计的编码系统对相关的协同交流研究也有借鉴意义。
K. Marzullo, 张鹏翼, 德德玛, 刘洁丽, and 安佳鑫, “当计算机科学遇到信息科学——马里兰大学信息学院院长Keith Marzullo教授学术访谈,” 图书情报知识, no. 03, pp. 4-10, 2020.AbstractPKU 
杨玉宇 and 张鹏翼, “视频社会化标引与标引娱乐化研究——以哔哩哔哩弹幕网为例,” 图书情报工作, vol. 64, no. 8, pp. 125-133, 2020.AbstractPKU 
P. Zhang and D. Soergel, “Cognitive Mechanisms in Sensemaking: A Qualitative User Study,” Journal of the Association for Information Science and Technology, vol. 71, no. 2, pp. 158-171, 2020.
Dedema and P. Zhang, “"Happy Rides Are All Alike; Every Unhappy Ride Is Unhappy in Its Own Way": Passengers' Emotional Experiences while Using a Mobile Application for Ride-sharing,” in iConference 2019, Washington DC, 2019.
J. Zhou and P. Zhang, “Examining the Influence of Visual Stimuli and Personal Characteristics on Users' Willingness-to-Wait Time and Waiting Patterns,” in 21ST INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION, Orlando, Florida, USA, 2019.
J. Lai, Y. Han, and P. Zhang, “Argumentation model of WeChat group chat: Evidence from content analysis with inductive coding,” in Proceedings of the Association for Information Science and Technology, 2019, vol. 56, no. 1, pp. 699-700. 访问链接Abstract
ABSTRACT Argumentation, the act of defending one's inherent knowledge or views through speech expression, is a kind of widespread information expression and communication behavior. In this poster, we aim to explore the characteristics and patterns of argumentation in social media to examine basic rules the patterns follow by conducting content analysis of the transcript of a WeChat Group Chat. We build a theoretical model of argumentation behavior in mobile social media using the inductive coding and find that social media has a great influence on argumentation.
L. Tong, H. Lin, and P. Zhang, ““I don't understand it so it can't be good”: Users' acg domain expertise and perceived quality of video tags,” in Proceedings of the Association for Information Science and Technology, 2019, vol. 56, no. 1, pp. 780-782. 访问链接Abstract
ABSTRACT Tag quality is an important factor to the success of social tagging systems and platforms. Users' domain expertise may influence they perceive tag quality. This study aims to explore how users of different domain experience (frequent user, occasional user, and non-user) perceive the quality of the same tags. We examined an online video community, Bilibili, which specializes in Anime, Comic and Games (ACG) subculture. We asked 60 users to watch 15 videos and rate the 95 tags of these videos, and found that: 1) Users with more domain expertise give higher ratings for tags' relevance to the videos and their retrieval value; 2) Occasional users have the lowest understandability rating, followed by non-users, and frequent users; 3) users think high-frequency tags are less suitable for retrieval. These results may provide insights to high quality tag selection for personalized recommendation and retrieval.
张鹏翼, 王汉桢, 刘鸿彬, and 刘畅, “信息管理学科新兴职业研究——以用户体验相关职位为例,” 图书与情报, no. 06, pp. 25-34, 2019.AbstractPKU 
J. An, Y. Na, and P. Zhang, “How do parents of children with ASD use information grounds to seek for ASD‐related information?,” Proceedings of the Association for Information Science and Technology, vol. 56, no. 1, pp. 10-20, 2019.
周翔, 张鹏翼, and 王军, “移动购物用户信息浏览特征及对购买的影响研究——基于移动电商APP点击流日志的分析,” 数据分析与知识发现, vol. 2, no. 4, pp. 1-9, 2018.
张璐, 刘畅, and 张鹏翼, “协同搜索与独立搜索的行为与体验的比较研究,” 图书情报工作, vol. 62, no. 21, pp. 62-70, 2018.AbstractPKU 
[目的 /意义]探究在协同与独立模式下完成信息搜索任务的过程中,用户在搜索体验、交互行为方面的差异,试图通过对比研究来理解协同信息搜索行为的特点,为协同搜索系统的设计提供借鉴。[方法 /过程]基于图书交互式检索平台(CLEF-Social Book Search)进行实验,共招募16名独立被试和18名协同被试到实验室完成多种类型的书目搜索任务,对搜索前后问卷记录的搜索体验以及后台服务器记录的搜索过程交互行为进行对比分析。[结果/结论]搜索体验方面,协同搜索被试比独立搜索被试对实验系统的功能评价更好,对系统的美感、耐用性、新颖度评价更高,参与实验的专注度更高,但却感到更加费力;搜索行为方面,相比独立模式下的被试,协同模式下的被试在目标型任务中进行更多次决策,尤其是删除书目的决策,意味着协同搜索被试在搜索后期会进行更多的决策讨论和整理;在探索任务中,协同被试比独立被试的平均决策时间和首次决策时间都更长,可能是由于在探索任务中协同被试的参与度更高、讨论更多。
L. Xu, Dedema, and P. Zhang, “Comparing User Experience in Interactions with Different Types of Digital Products,” HCI International. 2018.
Y. Jiao, X. Chen, D. Wang, P. Zhang, and J. Wang, “Exploring Browsing Behavior of Product Information in an M-commerce Application: a Transaction Log Analysis,” iConference 2018: Transforming Digital Worlds. 2018.
L. Xu, Dedema, and P. Zhang, “Users’ Emotional Experiences during Interaction with Information Products: A Diary Study,” iConference 2018: Transforming Digital Worlds. 2018.