Knowledge synthesis in the biomedical literature: Nordihydroguaiaretic acid and breast cancer.

This dissertation refines knowledge synthesis from publicly accessible databases, based on the model of D.R. Swanson. Knowledge synthesis endeavors bring together two or more non-interactive literatures to create combinatorial research data on a specific topic. In this endeavor the biomedical literature was searched on the anti-neoplastic agent nordihydroguaiaretic acid (NDGA) for its potential role as a functional food in the chemoprevention of breast cancer. Bibliometric cocitation was utilized to identify complementary but non-interactive literatures in the disciplines of biomedicine and dietary science. The continuing specialization and fragmentation of the cancer literature degenerates the potential usefulness of cross-disciplinary research and information. As the biomedical sciences become more specialized the potential increases for isolation of discoveries and for failures to connect science to the needs of the people. Within the information science discipline several techniques are available to bridge the isolation between discoveries recorded in different sets of literatures. Electronic database searching with combinatorial keyword entries, syllogistic modeling and bibliometric author cocitation analysis are the principle techniques applied in this endeavor. The research questions are addressed to the absence or presence of human in vivo research on breast cancer with the potentially chemopreventative functional food NDGA. Utilizing a syllogistic model the literatures of functional foods, nordihydroguaiaretic acid and breast cancer were searched with designated combinatorial keywords. The documents retrieved were subjected to author cocitation analysis to demonstrate disjointness or connectivity of the two complementary literatures. The results demonstrated a possible preventative relationship between breast cancer in women and nordihydroguaiaretic acid, a phytochemical antioxidant and potential functional food. The results of this study are consistent with D.R. Swanson's pioneering work in knowledge synthesis. Swanson's methods can be used to identify non-interactive, disjoint literatures. Continuing support for his techniques has been demonstrated

Examining Scholarly Influence: A Study in Hirsch Metrics and Social Network Analysis

This dissertation research is focused on how we, as researchers, ‘influence’ others researchers. In particular, I am concerned with the notion of what constitutes the ‘influence’ of a scholar and how ‘influence’ is conferred upon scholars. This research is concerned with the construct called ‘scholarly influence’. Scholarly influence is of interest because a clear “theory of scholarly influence” does not yet exist. Rather a number of surrogate measures or concepts that are variable are used to evaluate the value of one’s academic work. ‘Scholarly influence’ is broken down into ‘ideational influence’ or the influence that one has through publication and the uptake of the ideas presented in the publication, and ‘social influence’ or the influence that one has through working with other researchers. Finally through the use of the definition of ‘scholarly influence’ this dissertation tries to commence a definition of ‘quality’ in scholarly work

Theories of Informetrics and Scholarly Communication

Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published "The need for a theory of citing" —a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact

Semi-Supervised Learning For Identifying Opinions In Web Content

Thesis (Ph.D.) - Indiana University, Information Science, 2011Opinions published on the World Wide Web (Web) offer opportunities for detecting personal attitudes regarding topics, products, and services. The opinion detection literature indicates that both a large body of opinions and a wide variety of opinion features are essential for capturing subtle opinion information. Although a large amount of opinion-labeled data is preferable for opinion detection systems, opinion-labeled data is often limited, especially at sub-document levels, and manual annotation is tedious, expensive and error-prone. This shortage of opinion-labeled data is less challenging in some domains (e.g., movie reviews) than in others (e.g., blog posts). While a simple method for improving accuracy in challenging domains is to borrow opinion-labeled data from a non-target data domain, this approach often fails because of the domain transfer problem: Opinion detection strategies designed for one data domain generally do not perform well in another domain. However, while it is difficult to obtain opinion-labeled data, unlabeled user-generated opinion data are readily available. Semi-supervised learning (SSL) requires only limited labeled data to automatically label unlabeled data and has achieved promising results in various natural language processing (NLP) tasks, including traditional topic classification; but SSL has been applied in only a few opinion detection studies. This study investigates application of four different SSL algorithms in three types of Web content: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. SSL algorithms are also evaluated for their effectiveness in sparse data situations and domain adaptation. Research findings suggest that, when there is limited labeled data, SSL is a promising approach for opinion detection in Web content. Although the contributions of SSL varied across data domains, significant improvement was demonstrated for the most challenging data domain--the blogosphere--when a domain transfer-based SSL strategy was implemented

Theories of Informetrics and Scholarly Communication

Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published "The need for a theory of citing" —a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact