Towards a probabilistic model for supporting collaborative information access

In information retrieval research, models and systems traditionally assume that a single person is querying and reviewing the results. However, several empirical studies of professional practice identified collaboration during IR as everyday work patterns in order to solve a shared information need and to benefit from the diverse expertise and experience of the team members. Moreover, most IR systems that are employed in professional work routines are designed for individual use and prototype collaborative systems are too limited to support use in todays work practice. To bridge this gap, this papers develops and formalizes a decision theoretic approach towards supporting a team of people that explicitly set out together to resolve a shared information need. We develop a formal cost model for collaborative IR that considers the trade-off between estimated relevance of a document as well as estimated document redundancy. From this cost model, we use a decision theoretic approach to derive the notion of activity suggestions, that is, a formal optimum criterion that describes optimum collaboration strategies in IR as the solution of an integer linear program. Those collaboration strategies are suggested to team members with the aim to facilitate the collaborative performance of information retrieval tasks. We demonstrate the application of our model by means of search result division in two collaborative search tasks. In the conducted experiments, we study the effects of different domain knowledge and resulting relevance assessments of team members in four different conditions. The gathered results indicate that our approach can improve the retrieval effectiveness of teams in recall-oriented tasks.     

Team formation and team impact: The balance between team freshness and repeat collaboration

Incorporating fresh members into teams is considered a pathway to team creativity. However, whether freshness improves team performance or not remains unclear, as well as the optimal involvement of fresh members for team performance. Focusing on team impact, one important dimension of team performance, this study uses a group of authors on the byline of a publication as a proxy for a scientific team and quantifies team impact by citations of a paper authored by this team, i.e., article team impact. We extend an indicator, i.e., article team freshness, to measure the extent to which a scientific team incorporates new members, by calculating the fraction of new collaboration relations established within the team. Based on more than 43 million scientific publications covering more than a half-century of research from Microsoft Academic Graph, this study provides a holistic picture of the current development of article team freshness by outlining the temporal evolution of freshness, and its disciplinary distribution. Subsequently, using a multivariable regression approach, we examine the association between article team freshness and papers’ short-term and long-term citations. The major findings are as follows: (1) article team freshness in scientific teams has been increasing in the past half-century; (2) there exists an inverted-U-shaped association between article team freshness and papers’ citations in all the disciplines and different periods; (3) article team impact is hampered by article team freshness in small-sized teams, while medium-sized and large-sized teams can benefit more from article team freshness before the fraction of new collaboration reaches its turning point. The findings of this study provide implications for the practice of team formation and team management in science.     

在线知识协作行为研究:团队成员亲密度及协作倾向的影响

[目的/意义]帮助学者深入了解团队成员亲密度、协作倾向对小规模在线知识协作行为的影响,以及小规模用尸在线知识协作的行为模式.研究成果可以应用于在线教育、科研协作等领域,为在线知识协作工具、平台功能改进提供参考.[方法/过程]通过用户实验,对小型团队的任务规划、信息检索、信息共享、信息使用和沟通交流5种类型行为进行分析,...     

Virtually Working: Communicative and Structural Predictors of Media Use and Key Outcomes in Virtual Work Teams1 A previous version of this work was presented as a Top 3 Paper in the Organizational Communication Division at the International Communication Association Annual Conference,New Orleans,LA (May 2004).

Organizational trends toward team-based structures, globalization, and reliance on communication technology have spurred research addressing the communication processes of virtual teams. However, much of the extant research focuses on the ways virtual teams differ from conventional, face-to-face teams and fails to examine variations in virtual team characteristics that may impact team communication behaviors and experiences. The study reported here identifies two categories of virtual team characteristics (communicative and structural) and uses these to explore their relationships to team communication technology use and team outcomes. Analysis of data from 98 virtual teams reveals that structural features primarily relate to media use, whereas communication considerations are associated with team outcomes. Additional analyses indicate that various communicative predictors moderate the relationships between technology use and outcomes. These results point to theoretical and practical implications for researchers, team members, managers, and organizations related to virtual team design and communication processes.     

Understanding the assembly of interdisciplinary teams and its impact on performance

Interdisciplinary teams are assembled in scientific research and are aimed at solving complex problems. Given their increasing importance, it is not surprising that considerable attention has been focused on processes of collaboration in interdisciplinary teams. Despite such efforts, we know less about the factors affecting the assembly of such teams in the first place. In this paper, we investigate the structure and the success of interdisciplinary scientific research teams. We examine the assembly factors using a sample of 1103 grant proposals submitted to two National Science Foundation interdisciplinary initiatives during a 3-year period, including both awarded and non-awarded proposals. The results indicate that individuals’ likelihood of collaboration on a proposal is higher among those with longer tenure, lower institutional tier, lower H-index, and with higher levels of prior co-authorship and citation relationships. However, successful proposals have a little bit different relational patterns: individuals’ likelihood of collaboration is higher among those with lower institutional tier, lower H-index, (female) gender, higher levels of prior co-authorship, but with lower levels of prior citation relationships.     

How Team Interlock Ecosystems Shape the Assembly of Scientific Teams: A Hypergraph Approach

ABSTRACT

Today’s most pressing scientific problems necessitate scientific teamwork; the increasing complexity and specialization of knowledge render “lone geniuses” ill-equipped to make high-impact scientific breakthroughs. Social network research has begun to explore the factors that promote the assembly of scientific teams. However, this work has been limited by network approaches centered conceptually and analytically on “nodes as people,” or “nodes as teams.” In this article, we develop a “team-interlock ecosystem” conceptualization of collaborative environments within which new scientific teams, or other creative team-based enterprises, assemble. Team interlock ecosystems comprise teams linked to one another through overlapping memberships and/or overlapping knowledge domains. They depict teams, people, and knowledge sets as nodes, and thus, present both conceptual advantages as well as methodological challenges. Conceptually, team interlock ecosystems invite novel questions about how the structural characteristics of embedding ecosystems serve as the primordial soup from which new teams assemble. Methodologically, however, studying ecosystems requires the use of more advanced analytics that correspond to the inherently multilevel phenomenon of scientists nested within multiple teams. To address these methodological challenges, we advance the use of hypergraph methodologies combined with bibliometric data and simulation-based approaches to test hypotheses related to the ecosystem drivers of team assembly.     

How does collaboration affect researchers’ positions in co-authorship networks?

Collaboration usually has a positive effect on researchers’ productivity: researchers have become increasingly collaborative, according to recent studies. Numerous studies have focused on enhancing research collaboration by recommendation technology and measuring the influence of researchers. However, few studies have investigated the effect of collaboration on the position of a researcher in the research social network. In this paper, we explore the relationships between collaboration and influence by social analytical methods, which are pertinent to analyzing the network structure and individual traits. We evaluate three aspects of the researchers’ influence: friendship paradox validation, social circle, and structure of a researcher's ego network. Furthermore, the ”six degrees of Bacon number” theory, generalized friendship paradox, and triadic closure theory are introduced to support our analysis. Experimental results show that collaboration can help researchers increase their influence to some extent.     

Stabilisation operationalised: Using time series analysis to understand the dynamics of research collaboration

The aim of the paper is to investigate the use of online data and time series analysis, in order to study the dynamics of new types of research collaboration in a systematic way. Two international research teams were studied for more than 3 years, and quantitative data about their internet use together with observation of their collaboration patterns were gathered. Time series analysis (ARIMA modelling) was performed on their use of internet, and specific types of models related to specific ways of conducting research at a distance. The paper proposes the use of online data and ARIMA models to identify the stabilisation of a complex system, such as a research team, and investigate everyday research practices.     

搜索引擎日志挖掘领域的论文合著网络分析

基于Web of SCI和EI数据库中所收录的有关搜索引擎日志挖掘领域的研究论文,构建作者合著网络,利用社会网络分析方法研究合著网络的中心性、小世界特性、连通性等基本特征,发现该领域中最核心的科研合作团队、研究人员及其研究内容等。     

虚拟学术社区科研团队合作行为的三方动态博弈

随着互联网技术的快速发展,虚拟学术社区成为科研合作的重要平台。科研人员基于虚拟学术社区构建了虚拟科研团队,对成员合作行为进行研究,有利于促进虚拟学术社区的健康发展。文章将虚拟学术社区科研团队成员划分为任务角色倾向型、关系角色倾向型和自我角色倾向型3种类型;利用三方博弈理论,对这3类成员合作行为的演化博弈关系和过程进行分析。研究表明,虚拟学术社区科研团队成员的三方博弈结果依赖于各参数取值,反映出结果的复杂性,根据不同类型的虚拟科研团队成员,需要制定不同的策略,以发挥虚拟学术社区在科研合作中的重要作用。     

Unexpected collaborations: A science librarian and a reference archivist co-teaching

Libraries and archives are often grouped together as knowledge organizations with some shared goals and purposes, and in academic institutions this is no different. They might compete for the same resources or be managed by the same administrative teams; however, how much collaboration is there between libraries and archives in academia? Some might suppose that there is consistent collaboration and interconnected priorities and projects which foster that collaboration. Those librarians providing support for historians or history departments may have strong working relationships with reference archivists, but what about those working in other areas of librarianship? Would there be opportunity, for example, for an academic science librarian to partner with a reference archivist to elucidate the treasures hidden within archives relevant to scientists? We can definitively answer that question from our own personal experience. Since 2018, the authors, a science librarian and reference archivist, have worked together to introduce those beyond history departments the opportunities for archival research. In this column, we describe how we started working together, our various collaborative efforts over the years, and what we have learned along the way.     

Quantifying the degree of research collaboration: A comparative study of collaborative measures

This article reports a comparative study of five measures that quantify the degree of research collaboration, including the collaborative index, the degree of collaboration, the collaborative coefficient, the revised collaborative coefficient, and degree centrality. The empirical results showed that these measures all capture the notion of research collaboration, which is consistent with prior studies. Moreover, the results showed that degree centrality, the revised collaborative coefficient, and the degree of collaboration had the highest coefficient estimates on research productivity, the average JIF, and the average number of citations, respectively. Overall, this article suggests that the degree of collaboration and the revised collaborative coefficient are superior measures that can be applied to bibliometric studies for future researchers.     

Metaphoric manifestations of talking “team” with team novices

This study explores the impact of the team metaphor promoted by organizational “team talk” on individuals inexperienced in the organizational team environment. Qualitative data are used to identify metaphoric entailments that team novices associate with the team concept. Results are compared to similar data from more experienced team members from one team‐based organization. The study suggests that team novices share only a very general understanding of the team metaphor and strongly associate teams with sports activities. Novices' cognitive frameworks differ from each other and from more experienced team members and team experts in some important ways. Implications for the role of metaphoric illumination and reorientation in team development training are considered.     

Librarian and faculty collaborative instruction: A phenomenological self-study

Several models of librarian and faculty collaboration are found in the professional librarian literature. The literature on collaborative self-study research in university settings suggests collaborative self-study research can improve interdisciplinary and collaborative approaches to teaching and research and facilitate the transfer of knowledge. A research librarian and professor of education conducted a phenomenological self-study to examine their multiple roles as researchers and instructors who collaborated to develop, implement, and evaluate distance-delivered instructional services for public school teachers who live and work in remote, rural, and Alaska Native communities throughout the state of Alaska. Several themes emerged from this phenomenological self-study: (a) our interdisciplinary and collaborative efforts resulted in increased opportunities to team teach and conduct future collaborative research; (b) we struggled to communicate effectively with our students via audio-conference; and (c) our beliefs and practices were transformed by our participation in this phenomenological self-study. We believe our collaborative approach to phenomenological self-study research can promote intense self-reflection, stimulate creativity, and facilitate open and honest communication between academic librarians and teaching faculty who engage in collaborative instruction and collaborative research; furthermore, we believe our collaborative approach to phenomenological self-study research can increase the instructional effectiveness of academic librarians and teaching faculty collaborating to teach in distance-delivered higher education.     

基于科研合作网络演化的个体网络生命过程分析

将复杂网络的研究方法引入到科研合作网络的研究中,为分析和评价科研人员提供了一个新途径.文章以合作网络为背景,微观深入地研究了科研合作网络中个体成员的网络生命特性,从全局网络和局部社团演化的角度定量分析个体网络生命过程对网络发展的影响.文章以大量的科技文献数据为实验数据集,以网络演化为线索跟踪个体成员的生命过程,同时考虑网络演化中的普通成员和核心成员对社团演化的不同影响,定量分析演化特性和个体网络生命过程.数据分析证实了科研团队要持续不断地发展,既要不断吸纳新成员为科研团队注入新活力,同时又要有相对稳定的中坚力量维持着团队的科研方向.更进一步地,文章的研究方法可以扩展到对其他社会组织分析,追踪分析相关组织的发展趋势及关键人物对组织演化的影响.     

Gender-specific patterns in the artificial intelligence scientific ecosystem

Gender disparity in science is one of the most focused debating points among authorities and the scientific community. Over the last few decades, numerous initiatives have endeavored to accelerate gender equity in academia and research society. However, despite the ongoing efforts, gaps persist across the world, and more measures need to be taken. Using social network analysis, natural language processing, and machine learning, in this study, we comprehensively analyzed gender-specific patterns in the highly interdisciplinary and evolving field of artificial intelligence for the period of 2000–2019. Our findings suggest an overall increasing rate of mixed-gender collaborations. From the observed gender-specific collaborative patterns, the existence of disciplinary homophily at both dyadic and team levels is confirmed. However, a higher preference was observed for female researchers to form homophilous collaborative links. Our core-periphery analysis indicated a significant positive association between having diverse collaboration and scientific performance and experience. We found evidence in support of expecting the rise of new female superstar researchers in the artificial intelligence field.     

A Bibliometric Analysis of Collaboration in the Field of Information Retrieval

Collaboration practices vary greatly per scientific area and discipline and influence the scientific performance and its scholarly communication. In this study, the collaborative pattern of the Information Retrieval (IR) research field is analyzed using co-authored articles retrieved from Social Science Citation Index for a period of 11 years from 1987 to 1997. The level of collaboration, journal collaborative distribution, disciplinary collaborative distribution and country collaboration are probed according to IR collaborative research. Findings are discussed from the above perspectives in detail. In particular, this study reveals a perceptible upward trend of collaborative IR research with the results of these research efforts being reported in all major core IR journals. The inter-disciplinary and intra-disciplinary scholarly communications in collaborative researches are very much in evidence and cover broad areas like psychology, and computer and medical sciences, respectively.     

Library development in Swaziland

Collaboration practices vary greatly per scientific area and discipline and influence the scientific performance and its scholarly communication. In this study, the collaborative pattern of the Information Retrieval (IR) research field is analyzed using co-authored articles retrieved from Social Science Citation Index for a period of 11 years from 1987 to 1997. The level of collaboration, journal collaborative distribution, disciplinary collaborative distribution and country collaboration are probed according to IR collaborative research. Findings are discussed from the above perspectives in detail. In particular, this study reveals a perceptible upward trend of collaborative IR research with the results of these research efforts being reported in all major core IR journals. The inter-disciplinary and intra-disciplinary scholarly communications in collaborative researches are very much in evidence and cover broad areas like psychology, and computer and medical sciences, respectively.     

基于有向合著网络的核心团队挖掘研究——以图情领域为例

[目的/意义] 为便于机构人才引进,构建领域核心团队识别规范化流程,从核心区域作者确定、团队指导/师承关系判别、团队发刊倾向和团队研究方向4个方面对领域核心团队进行挖掘研究。[方法/过程] 首先,进行数据前期规范;然后,结合作者合著无向二值矩阵与核心-边缘结构分析,划分核心区域作者,综合多维指标对核心区域作者进行适当调整;最后,基于第一作者与其他作者的有向合著网络,识别领域核心研究团队。[结果/结论] 在厘清团队指导/师承关系判别基本流程上,提炼通用性规律,包括：①在"外射星型"拓扑结构的合著团队中,处于中心位置节点有较高概率为导师/指导者,而"内聚星型"拓扑结构合著团队位于网络中心的作者科研能力较强;②在第一作者与其他作者的有向合著网络中,两个节点若同时具备第一作者与通讯作者关系、有相同的所属机构、学术年龄有一定差距,则这两个节点间一定存在指导关系,有较高的概率存在师承关系。