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.

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.

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.

<正>1社会技术视角:CS与IS的联合张鹏翼:Marzullo教授,您好!感谢您抽时间接受我的访谈。据我了解,您的学术背景是计算机科学,现在作为马里兰大学iSchool的院长,您如何看待计算机科学(CS)与信息科学(IS)二者之间的关系?计算机科学对信息科学的影响更大吗?信息科学对计算机科学是否产生了什么影响呢?Prof.Marzullo:诚然,计算机科学院系的数量确实远多于iSchools院系的数量。不过,如果我们关注非常有影响力的团队,例如佐治亚理工学院、康奈尔

[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。

[目的/意义]随着视频资源的广泛使用，视频社会化标引中出现了新的表达用户观点情感的标引目的，而并非以传统的信息组织和检索为目的。对哔哩哔哩弹幕网（简称“B站”）的视频标签进行分析研究，以探索视频标签内容和视频标引新趋势——娱乐化标引。[方法/过程]采用日志分析与用户访谈等定性、定量相结合的方法，对视频标签内容、娱乐标引的标引动机与作用进行研究。[结果/结论]①用户最常使用的视频标签类型是“内容主题”与“人物主体”；②娱乐标签是B站标签内容的重要组成部分；③用户使用娱乐标签的动机多为社交交流型；④娱乐标签有很多特殊的、区别于传统标签的作用，如“提高视频观看体验”等。本研究对视频标引内容与娱乐化标引进行了初步的探索，研究结果有利于进一步了解视频标引以及社会标引的新趋势。