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.     

How U.S. and Chinese journalists think about plagiarism

A comparison of 1,096 professional journalists in China and the United States on attitudes toward attribution and plagiarism reveals Chinese journalists were more likely to see attribution as a practice to be embraced regardless of career longevity and culture, suggesting journalistic norms are more important than a collectivist orientation. Attribution was more likely to be embraced by those who see principles as more important than expediency, affirming research that plagiarism is hardly a monolithic concept. Overall, journalists in the two nations did not vary significantly in their attitudes toward plagiarism, despite vast differences in culture and politics as well as evidence that in some other fields China is more accepting of reusing material without attribution. The data show that among journalists, attitudes toward plagiarism are shared across national boundaries, reinforcing related research showing that a journalism culture exists and is shared at least in part across national boundaries.     

Reasons for Student Engagement in Extra-Class Communication

This study extends instructional communication research on extra-class communication (ECC) by presenting an integrative analysis comparing the explanatory utility of student- and instructor-oriented reasons for student engagement in frequent ECC. Results from 495 college students suggested that student-oriented reasons, specifically the relational and functional student motives, were the only significant, positive predictors of students’ perceptions of frequent ECC engagement. Other student motives (excuse making, participation, sycophancy) and perceptions of instructor approachability did not significantly predict perceived frequency of ECC engagement.     

Co-rumination and Immune Inflammatory Response in Healthy Young Adults: Associations with Interleukin-6 and C-Reactive Protein

A rich literature exists reinforcing the notion that both perceived and received social support has stress ameliorating and protective benefits both psychologically and physiologically. However, recent literature suggests that excessive dyadic negative problem talk about an issue, a phenomenon labeled co-rumination, may reverse much of the beneficial effects of social support. Healthy young adults participated in a laboratory research study exploring the associations between co-rumination and immune system inflammatory response. Partial correlations indicated a positive association between co-rumination and C-reactive protein and a negative association between co-rumination and interleukin-6 after controlling for stress, anxiety, and temperature. Discussion focuses on the means by which co-rumination may lead to negative health outcomes.     

Investigating married adults’ communal coping with genetic health risk and perceived discrimination

Increased genetic testing in personalized medicine presents unique challenges for couples, including managing disease risk and potential discrimination as a couple. This study investigated couples’ conflicts and support gaps as they coped with perceived genetic discrimination. We also explored the degree to which communal coping was beneficial in reducing support gaps and ultimately stress. Dyadic analysis of married adults (N?=?266, 133 couples), in which one person had the genetic risk for serious illness, showed that perceived discrimination predicted more frequent conflicts about alpha-1 antitrypsin deficiency-related treatment, privacy boundaries, and finances, which, in turn, predicted wider gaps in emotion and esteem support, and greater stress for both spouses. Communal coping predicted lower support gaps for both partners and marginally lower stress.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

The Librarian BFF: A Case Study of a Cohort-Based Personal Librarian Program

This case study presents the development and implementation of a personal librarian program for a cohort-based, executive-style higher education administration doctoral program. Librarians and the program director collaborated to create a student-centered program based on individual research needs. The personal librarian program was designed to build a close relationship between the librarian and individual students; to help identify their research knowledge gaps; and to identify resources to meet each individual students' research needs.     

Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

ABSTRACT

Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.     

Scaling up Content Analysis

ABSTRACT

Employing a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments.