Biases in scholarly recommender systems: impact, prevalence, and mitigation

We create a simulated financial market and examine the effect of different levels of active and passive investment on fundamental market efficiency. In our simulated market, active, passive, and random investors interact with each other through issuing orders. Active and passive investors select their portfolio weights by optimizing Markowitz-based utility functions. We find that higher fractions of active investment within a market lead to an increased fundamental market efficiency. The marginal increase in fundamental market efficiency per additional active investor is lower in markets with higher levels of active investment. Furthermore, we find that a large fraction of passive investors within a market may facilitate technical price bubbles, resulting in market failure. By examining the effect of specific parameters on market outcomes, we find that that lower transaction costs, lower individual forecasting errors of active investors, and less restrictive portfolio constraints tend to increase fundamental market efficiency in the market

Early-stage reciprocity in sustainable scientific collaboration

Scientific collaboration is of significant importance in tackling grand challenges and breeding innovations. Despite the increasing interest in investigating and promoting scientific collaborations, we know little about the collaboration sustainability as well as mechanisms behind it. In this paper, we set out to study the relationships between early-stage reciprocity and collaboration sustainability. By proposing and defining h-index reciprocity, we give a comprehensive statistical analysis on how reciprocity influences scientific collaboration sustainability, and find that scholars are not altruism and the key to sustainable collaboration is fairness. The unfair h-index reciprocity has an obvious negative impact on collaboration sustainability. The bigger the reciprocity difference, the less sustainable in collaboration. This work facilitates understanding sustainable collaborations and thus will benefit both individual scholar in optimizing collaboration strategies and the whole academic society in improving teamwork efficiency. © 2020 Elsevier Ltd.The authors extend their appreciation to the International Scientific Partnership Program ISPP at King Saud University for funding this research work through ISPP-78. This work is partially supported by China Postdoctoral Science Foundation ( 2019M651115 )

Measuring impact of academic research in computer and information science on society

Academic research in computer & information science (CIS) has contributed immensely to all aspects of society. As academic research today is substantially supported by various government sources, recent political changes have created ambivalence amongst academics about the future of research funding. With uncertainty looming, it is important to develop a framework to extract and measure the information relating to impact of CIS research on society to justify public funding, and demonstrate the actual contribution and impact of CIS research outside academia. A new method combining discourse analysis and text mining of a collection of over 1000 pages of impact case study documents written in free-text format for the Research Excellence Framework (REF) 2014 was developed in order to identify the most commonly used categories or headings for reporting impact of CIS research by UK Universities (UKU). According to the research reported in REF2014, UKU acquired 83 patents in various areas of CIS, created 64 spin-offs, generated £857.5 million in different financial forms, created substantial employment, reached over 6 billion users worldwide and has helped save over £1 billion Pounds due to improved processes etc. to various sectors internationally, between 2008 and 2013

Blueprints for success: Guidelines for building multidisciplinary collaboration teams

From the International Conference on Agents and Artificial Intelligence. J.Filipe and A.L.N.Fred. Vilamoura, Algarve, Portugal, SciTePress. 1: 387-393.Finding collaborators to engage in academic research is a challenging task, especially when the collaboration is multidisciplinary in nature and collaborators are needed from different disciplines. This paper uses evidence of successful multidisciplinary collaborations, funded proposals, in a novel way: as an input for a method of recommendation of multidisciplinary collaboration teams. We attempt to answer two questions posed by a collaboration seeker: what disciplines provide collaboration opportunities and what combinations of characteristics of collaborators have been successful in the past? We describe a two-step recommendation framework where the first step recommends potential disciplines with collaboration potential based on current trends in funding. The second step recommends characteristics for a collaboration team that are consistent with past instances of successful collaborations. We examine how this information source can be used in a case-based recommender system and present a preliminary validation of the system using statistical methods

Studying service and metadata models of research information management systems

As the uses for research information management (RIM) systems grow, digital curation communities are increasingly interested in building shared, sustainable, community-based models for RIM services and metadata, and connecting those models to researchers’ activities and needs. This paper presents RIM service and metadata models and compares the models to researchers’ activities and engagement levels in RIM systems. The findings of this study can inform the design of RIM service templates or repertoires for different levels of researcher participation in RIM systems. Future related work will include the collection and analysis of empirical data of the actual uses of RIM services and metadata by researchers.The authors would like to express their appreciation to the researchers who participated in the study. This research is supported by an OCLC/ALISE Library and Information Research Grant for 2016 and a National Leadership Grant from the Institute of Museum and Library Services (IMLS) of the U.S. Government (grant # LG-73-16-0006-16). The article reflects the findings and conclusions of the authors, and do not necessarily reflect the views of OCLC, ALISE, and IMLS

How to Drink from a Firehose: Systemic Supports for Polytechnic Chairs

This Organizational Improvement Plan (OIP) is centred on the Problem of Practice of the inadequate institutional supports for academic Chairs at Prairie Polytechnic (a pseudonym), a large public higher education institution in Western Canada. Chairs are pivotal for higher education institutions because they impact student, departmental, and institutional outcomes; however, the leadership development needs of Chairs are overlooked, and the limited training available for Chairs is primarily ad hoc, episodic, short-term, and self-guided. The objective of this OIP is to determine how Prairie Polytechnic can provide more effective systemic supports for Chairs. Postmodernism is used to explore the relationships between knowledge and positional power, and Critical Theory highlights the inequities Chairs face. Four potential solutions are explored and compared: increased release time from teaching, increased role clarity, Chair learning communities, and a Chair life cycle strategy. The Chair life cycle strategy is selected as the most feasible, efficacious, and ethical solution, and a change plan is detailed for how the strategy will be implemented at Prairie Polytechnic. The change plan is mapped to the stages of change from the ADKAR change model (awareness; desire; knowledge; ability; reinforcement) and guided by Adaptive Leadership behaviours. A communication plan identifies how collaborators will be engaged in the change process, and a monitoring and evaluation plan identifies how the change plan will be assessed. Successful implementation of the change plan will provide the systemic infrastructure needed to support academic leadership development at Prairie Polytechnic

Mining, Modeling, and Leveraging Multidimensional Web Metrics to Support Scholarly Communities

The significant proliferation of scholarly output and the emergence of multidisciplinary research areas are rendering the research environment increasingly complex. In addition, an increasing number of researchers are using academic social networks to discover and store scholarly content. The spread of scientific discourse and research activities across the web, especially on social media platforms, suggests that far-reaching changes are taking place in scholarly communication and the geography of science. This dissertation provides integrated techniques and methods designed to address the information overload problem facing scholarly environments and to enhance the research process. There are four main contributions in this dissertation. First, this study identifies, quantifies, and analyzes international researchers’ dynamic scholarly information behaviors, activities, and needs, especially after the emergence of social media platforms. The findings based on qualitative and quantitative analysis report new scholarly patterns and reveals differences between researchers according to academic status and discipline. Second, this study mines massive scholarly datasets, models diverse multidimensional non-traditional web-based indicators (altmetrics), and evaluates and predicts scholarly and societal impact at various levels. The results address some of the limitations of traditional citation-based metrics and broaden the understanding and utilization of altmetrics. Third, this study recommends scholarly venues semantically related to researchers’ current interests. The results provide important up-to-the-minute signals that represent a closer reflection of research interests than post-publication usage-based metrics. Finally, this study develops a new scholarly framework by supporting the construction of online scholarly communities and bibliographies through reputation-based social collaboration, through the introduction of a collaborative, self-promoting system for users to advance their participation through analysis of the quality, timeliness and quantity of contributions. The framework improves the precision and quality of social reference management systems. By analyzing and modeling digital footprints, this dissertation provides a basis for tracking and documenting the impact of scholarship using new models that are more akin to reading breaking news than to watching a historical documentary made several years after the events it describes

Authorship, citations, acknowledgments and visibility in social media : symbolic capital in the multifaceted reward system of science

The reward system of science is undergoing significant changes, as traditional indicators compete with initiatives that offer novel means of disseminating and assessing scholarly impact. This paper considers a number of aspects of this reward system, including authorship, citations, acknowledgements, and the growing use of social media platforms by academics, with an eye towards identifying contemporary issues relating to scholarly communication practices, as understood through the perspectives of Bourdieu’s symbolic capital and Merton’s recognition paradigms. This paper posits that, while scientific capital remains the foundation upon which the reward system of science is built, this system is revealing itself to be more and more multifaceted, extremely complex, and facing increasing tension between its traditional means of evaluation and the potential of new indicators in the digital era. The paper presents an extended literature review, as well as recommendations for further considerations and empirical research. A better understanding of the perceptions of academics would be necessary to properly assess the effects of these new indicators on scholarly communication practices and the reward system of science

Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes

Knowing driving factors and understanding researcher behaviors from the dynamics of collaborations over time offer some insights, i.e. help funding agencies in designing research grant policies. We present longitudinal network analysis on the observed collaborations through co-authorship over 15 years. Since co-authors possibly influence researchers to have interest changes, by focusing on researchers who could become the influencer, we propose a stochastic actor-oriented model of bipartite (two-mode) author-topic networks from article metadata. Information of scientific fields or topics of article contents, which could represent the interests of researchers, are often unavailable in the metadata. Topic absence issue differentiates this work with other studies on collaboration dynamics from article metadata of title-abstract and author properties. Therefore, our works also include procedures to extract and map clustered keywords as topic substitution of research interests. Then, the next step is to generate panel-waves of co-author networks and bipartite author-topic networks for the longitudinal analysis. The proposed model is used to find the driving factors of co-authoring collaboration with the focus on researcher behaviors in interest changes. This paper investigates the dynamics in an academic social network setting using selected metadata of publicly-available crawled articles in interrelated domains of "natural language processing" and "information extraction". Based on the evidence of network evolution, researchers have a conformed tendency to co-author behaviors in publishing articles and exploring topics. Our results indicate the processes of selection and influence in forming co-author ties contribute some levels of social pressure to researchers. Our findings also discussed on how the co-author pressure accelerates the changes of interests and behaviors of the researchers