Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.     

Staff development planning in an academic health sciences library.

OBJECTIVE: A staff development committee (SDC) was convened to implement staff development opportunities for an academic health sciences library system comprised of three separate facilities. The charge for the SDC was to: (1) develop programs to enhance workplace skills and personal growth, (2) communicate the availability of existing programs at the university and medical center, and (3) encourage the staff to participate in these opportunities. PROGRAM: The committee created goals and objectives and developed a survey designed to give staff the opportunity to provide input for this initiative. With an 80% response rate, the survey results were used to plan 15 events based on staff needs and preferences. First-year attendance for SDC-sponsored events was 459. Committee members served as liaisons for each event. Two forms were developed to facilitate event planning. A monthly announcement sheet, email reminders, and the library's local area network are used to communicate upcoming SDC events and encourage attendance. CONCLUSION: This approach can serve as a useful model for similar program planning in any organization.     

Institutional policy process improvement: using structurating activity theory to inform practice

Organizational communication scholars are increasingly called upon to use theoretical knowledge to address problematic processes in public institutions. This article reports a process improvement project focused on a university conflict of interest (COI) policy as an example of how scholars can engage theory to improve ongoing policy processes. The project team included communication scholars and research administration staff who designed, implemented, and evaluated the mixed-methods project guided by structurating activity theory. Baseline survey results were used to design the process improvement project. Results of the follow-up survey indicate that researchers who participated in some aspect of the process improvement project (i.e. attending a policy café, using the redesigned website, or reading the new Quick Reference Guide) reported higher levels of policy communication and knowledge and more positive attitudes toward the COI policy than researchers who had not engaged with process improvement efforts. We offer theoretical and practical implications of results for organizational communication scholars and practitioners.     

Some Aspects of the Development of the All-Russian Institute for Scientific and Technical Information

Although the USSR and the United States had a comparable number of employees in the field of scientific information, there was a substantial difference in funding, which resulted in a lack of information support for Soviet scientists. While 90% of the publications in the United States were available almost immediately after their release, in the USSR they were delayed by 1.5 to 2 years. Since the publication of the Abstracts Journal by VINITI (AJ), its content was consistently expanding and reached its peak in 1990 (1.5 million documents per year). The next quarter of a century was characterized by a decline in both the composition of the AJ and the time required for its document coverage. The steps for restructuring VINITI activities are discussed. The focus is made on improving the limited coverage of the Russian-language part of the global flow of scientific information by Western information systems.     

Scientometric Instruments of Research Funding

The issues related to funding of public research organizations are explored. The history of scientometric information systems is outlined. The advantages and disadvantages of a bibliometric approach to financing of research organizations are analyzed. The link between the assessment of the scientific and technological potential of an institution and the optimal allocation of funds is investigated. Recommendations on how to improve the efficiency of public resources allocated for scientific research are presented.     

An Analytical Review of Global Ecoinformatics Problems

Modern global eco-dynamics problems are discussed. It is noted that global changes are mostly characterized by several key features, such as their multicomponent nature, as well as interactivity and nonlinearity. These features challenge various forecast estimates in such a way that the concept of forecasting has been replaced over the last few years by a much more ambiguous concept of scenarios. The vagueness of scenarios is due to the problem of global climate change. A global climate–nature–society system model is outlined.     

Russian Science Citation Index: Areas for Development Identified by Active Users

The current state of the Russian Science Citation Index is analyzed. Several areas for its further development identified by long-standing active users, such as data searching, refinement, and storage; current user alerts; data input with the Science Index license; patent information; and the application programming interface (API) are investigated.     

Online Celebrity Bashing: Wrecking Ball or Good for You? Adolescent Girls’ Attitudes Toward the Media and Public Bashing of Miley Cyrus and Selena Gomez

Journalists and readers of celebrity news regularly bash celebrities online, a behavior that is easily accepted among adolescents. This study investigates whether these attitudes of acceptance differ according to the perpetrator of the bashing (media versus public) and the likeability of the involved celebrity (liked versus disliked). Using a vignette study, we examine adolescent girls’ attitudes toward media (journalists’) and public (readers’) bashing of a generally disliked celebrity (Miley Cyrus) and a generally liked celebrity (Selena Gomez). All participants read an identical negative news story (media bashing) and two related negative reader comments (public bashing). Participants were randomly assigned to read this information about either Miley Cyrus or Selena Gomez. Results of a mixed-design ANOVA showed that the girls had less negative attitudes toward media bashing compared with public bashing. Moreover, they more easily accepted the bashing of a disliked celebrity than the bashing of a liked celebrity.