To gain greater insight into the operation of online social networks, we applied Natural Language Processing (NLP) techniques to text-based communication to identify and describe underlying social structures in online communities. This paper presents our approach and preliminary evaluation for content-based, automated discovery of social networks. Our research question is: What syntactic and semantic features of postings in a threaded discussions help uncover explicit and implicit ties between network members, and which provide a reliable estimate of the strengths of interpersonal ties among the network members? To evaluate our automated procedures, we compare the results from the NLP processes with social networks built from basic who-to-whom data, and a sample of hand-coded data derived from a close reading of the text. For our test case, and as part of ongoing research on networked learning, we used the archive of threaded discussions collected over eight iterations of an online graduate class. We first associate personal names and nicknames mentioned in the postings with class participants. Next we analyze the context in which each name occurs in the postings to determine whether or not there is an interpersonal tie between a sender of the posting and a person mentioned in it. Because information exchange is a key factor in the operation and success of a learning community, we estimate and assign weights to the ties by measuring the amount of information exchanged between each pair of the nodes; information in this case is operationalized as counts of important concept terms in the postings as derived through the NLP analyses. Finally, we compare the resulting network(s) against those derived from other means, including basic who-to-whom data derived from posting sequences (e.g., whose postings follow whose). In this comparison we evaluate what is gained in understanding network processes by our more elaborate analyses.

In the past, raw information was frequently destroyed because it could not be stored, thereby precluding effective scholarly use of the materials. Today's computer technology allows preservation and compact storage of enormous quantities of highly detailed information. Maintenance of information in conventional paper format often required severe access restrictions to protect anonymity of particular cases, a problem which can be alleviated by utilizing the computer to delete or mask the identity of the individuals involved. The value of any archival record is enhanced by the existence of other sources, which when used in tandem more completely describe the social, administrative, or economic process. This is especially true of the machine readable record, where source materials from one file can be more easily linked with other files to provide more complete documentation of particular events and transactions, thus augmenting the potential value and increasing the analytic or explanatory potential of the original records.

“What does the global research environment look like?” This paper presents a summary look at the results of efforts to address this question using available indicators on global research production. It was surprising how little information is available, how difficult some of it is to access and how flawed the data are. The three most useful data sources were UNESCO (United Nations Educational, Scientific and Cultural Organization) Research and Development data (1996-2002), the Institute of Scientific Information publications listings for January 1998 through March 2003, and the World of Learning 2002 reference volume. The data showed that it is difficult to easily get a good overview of the global research situation from existing sources. Furthermore, inequalities between countries in research capacity are marked and challenging. Information science offers strategies for responding to both of these challenges. In both cases improvements are likely if access to information can be facilitated and the process of integrating information from different sources can be simplified, allowing transformation into effective action. The global research environment thus serves as a case study for the focus of this paper – the exploration of information science responses to challenges in the management, exchange and implementation of knowledge globally.

The aim of the Science Foresight Project was to design and assess a simple, objective and cost-effective technique to gather information about emerging short and long-term research developments, primarily in the physical and engineering sciences. International experts were objectively chosen using co-citation patterns in scientific and technical literature, and were invited to submit their predictions about emerging developments in their research fields. They were questioned about how the effects of various factors and driving forces might affect their predictions. The cost and time required to administer the questionnaire and collect the responses was minimised through the use of Internet and Web based technologies. A simple process was used to report the predictions; short excerpts from each prediction were used as the summary and each prediction was classified into one of ten categories of emerging developments. Authors from 114 papers (23.7%) responded, identifying a total of 190 short-term and 111 long-term predicted emerging developments. Expert responses were received from an international group of senior researchers between the ages of 36 and 55, mostly engaged in basic research in academic institutions. Some experts described specific emerging developments, some discussed broad emerging trends in their field and others described both. Emerging development categories such as Atomic & Stellar Matter, Biology & Biosphere, Biomedical & Clinical, Computers & Robotics and Genomics & Proteomics were closely aligned with conventional science areas while other categories such as Mathematical & Computational and Nano Science & Technology contained predictions from almost every area of science. The technique developed and applied here appears to constitute an efficient means of surveying the international research community in order to gain insights into common patterns that evolve from their collective research activities. Dynamically monitoring emerging research developments on a continuous basis could provide valuable information to policy makers, planners and researchers.

Over the last few years the bibliographic control community has initiated a series of experiments that aim to improve access to the growing number of valuable information resources that are increasingly being placed on World Wide Web (here after referred to as Web resources). Much has been written about these experiments, mainly describing their implementation and features, and there has been some evaluative reporting, but there has been little comparison among these initiatives. The research reported on in this paper addresses this limitation by comparing five leading experiments in this area. The objective was to identify characteristics of success and considerations for improvement in experiments providing access to Web resources via bibliographic control methods. The experiments examined include: OCLC's CORC project; UKOLN's BIBLINK, ROADS, and DESIRE projects; and the NORDIC project. The research used a multi-case study methodology and a framework comprised of five evaluation criteria that included the experiment's organizational structure, reception, duration, application of computing technology, and use of human resources. This paper defines the Web resource access experimentation environment, reviews the study's research methodology, and highlights key findings. The paper concludes by initiating a strategic plan and by inviting conference participants to contribute their ideas and expertise to an effort will improve experimental initiatives that ultimately aim to improve access to Web resources in the new Millennium.

This study evaluates the data sources and research methods used in earlier studies to rank the research productivity of Library and Information Science (LIS) faculty and schools. In doing so, the study identifies both tools and methods that generate more accurate publication count rankings as well as databases that should be taken into consideration when conducting comprehensive searches in the literature for research and curricular needs. With a list of 2,625 items published between 1982 and 2002 by 68 faculty members of 18 American Library Associationâ (ALA-) accredited LIS schools, hundreds of databases were searched. Results show that there are only 10 databases that provide significant coverage of the LIS indexed literature. Results also show that restricting the data sources to one, two, or even three databases leads to inaccurate rankings and erroneous conclusions. Because no database provides comprehensive coverage of the LIS literature, researchers must rely on a wide range of disciplinary and multidisciplinary databases for ranking and other research purposes. The study answers such questions as the following: Is the Association of Library and Information Science Educationâ s (ALISEâ s) directory of members a reliable tool to identify a complete list of faculty members at LIS schools? How many and which databases are needed in a multifile search to arrive at accurate publication count rankings? What coverage will be achieved using a certain number of databases? Which research areas are well covered by which databases? What alternative methods and tools are available to supplement gaps among databases? Did coverage performance of databases change over time? What counting method should be used when determining what and how many items each LIS faculty and school has published? The authors recommend advanced analysis of research productivity to provide a more detailed assessment of research productivity of authors and programs.

In recent decades there has been a notable expansion of statistical data produced by the public and private sectors for administrative, research, policy and evaluation programmes. This is due to advances in relatively inexpensive and efficient data collection and management of computer-readable statistical data. Corresponding changes have not occurred in the management of data collection, preservation, description and dissemination. As a result, the process by which data become accessible to social researchers and others is frustrating, time consuming, and inefficient. This paper describes the reasons for this situation: the problem-solving workstyle of social data users, the nature of the data and their relationship to computer technology, and an inchoate social science information infrastructure. Since statistical data play an increasingly important role in social research and policy decisions, social science information specialists must be prepared to meet the computer-readable statistical data user's needs. Four strategies are recommended for improving utilization of these data: improving the quality of statistical evidence, educating information professionals and end-users in numerical information, using the existing information infrastructure to preserve and disseminate data, and developing retrieval tools for improving access to information about social data.

By 2000, the Internet became an information and communication medium that was integrated in our everyday lives. Following an interdisciplinary approach, the research reported in this article analyzes the wide variety of information that people seek on the Internet and investigates trends in Internet information activities between 2000 and 2004, using repeated cross-sectional data from the Pew Internet & American Life surveys to examine Internet activities that contribute to everyday life and their predictors. The objective is to deepen our understanding of Internet activities and everyday life and contribute to a growing body of research that utilizes large-scale empirical data on Internet use and everyday life. We ask: who is embedding the Internet into their everyday lives and what are the activities they pursue to facilitate everyday life? Findings demonstrate the differential returns for Internet use, particularly in key demographic categories. The study also contributes to emerging research on the digital divide, namely emphasis on the study of use rather than access to technology. Identifying trends in key Internet use dimensions enables policymakers to target populations who underutilize the potential of networked technologies.

This is a preprint of an article accepted for publication in the Journal of the American Society for Information Science © 2008. / By 2000, the Internet became an information and communication medium that was integrated in our everyday lives. Following an interdisciplinary approach, the research reported in this article analyzes the wide variety of information that people seek on the Internet and investigates trends in Internet information activities between 2000 and 2004, using repeated cross-sectional data from the Pew Internet and American Life surveys to examine Internet activities that contribute to everyday life and their predictors. The objective is to deepen our understanding of Internet activities and everyday life and contribute to a growing body of research that utilizes large-scale empirical data on Internet use and everyday life. We ask: who is embedding the Internet into their everyday lives and what are the activities they pursue to facilitate everyday life? Findings demonstrate the differential returns for Internet use, particularly in key demographic categories. The study also contributes to emerging research on the digital divide, namely emphasis on the study of use rather than access to technology. Identifying trends in key Internet use dimensions enables policymakers to target populations who underutilize the potential of networked technologies.

In my teaching and software development practice, I realized that most applications with human-computer interaction do not respond to users’ emotional needs. The dualism of reason and emotion as two fairly opposite entities that dominated Western philosophy was also reflected in software design. Computing was originally intended to provide applications for military and industrial activities and was primarily associated with cognition and rationality. Today, more and more computer applications interact with users in very complex and sophisticated ways. In human-computer interaction, attention is given to issues of usability and user modeling, but techniques to emotionally engage users or respond to their emotional needs have not been fully developed, even as specialists like Klein, Norman and Picard argued that machines that recognize and express emotions respond better and more appropriately to user interaction (Picard, 1997; Picard & Klein, 2002; Norman, 2004). This study investigated emotion from designers’ perspectives and tentatively concludes that there is little awareness and involvement in emotional design in the IT community. By contrast, participants in this study (36 IT specialists from various fields) strongly supported the idea of emotional design and confirmed the need for methodologies and theoretical models to research emotional design. Based on a review of theory, surveys and interviews, I identified a set of themes for heuristics of emotional design and recommended future research directions. Attention was given to consequences; participants in this study raised issues of manipulation, ethical responsibilities of designers, and the need for regulations, and recommended that emotional design should carry standard ethical guidelines for games and any other applications. The research design utilized a mixed QUAN-qual methodological model proposed by Creswell (2003) and Gay, Mills, and Airasian (2006), which was modified to equally emphasize both quantitative and qualitative stages. An instrument in the form of a questionnaire was designed, tested and piloted in this study and will be improved and used in future research.