Visualizing Gender Balance in Conferences

Data visualization is a powerful tool for digital scholarship yet not without its pitfalls. Based on the dissertation “Visualizing Gender Balance” comparing ten computer science conferences, several visualization techniques and tools undergo a critical review. The dataset underlying the visualizations contains data researchers encounter daily: bibliographic information. Analyzing larger sets of authors writing and publishing for conferences in computer science changes our perception of the gender (im)balance in this academic research area. But only a careful curation and visualization can truly reveal what goes on behind the scenes. Still the more complicated, detailed and nuanced the visualization, the harder it becomes for an untrained eye to interpret the patterns

Author-Based Analysis of Conference versus Journal Publication in Computer Science

Conference publications in computer science (CS) have attracted scholarly attention due to their unique status as a main research outlet unlike other science fields where journals are dominantly used for communicating research findings. One frequent research question has been how different conference and journal publications are, considering a paper as a unit of analysis. This study takes an author-based approach to analyze publishing patterns of 517,763 scholars who have ever published both in CS conferences and journals for the last 57 years, as recorded in DBLP. The analysis shows that the majority of CS scholars tend to make their scholarly debut, publish more papers, and collaborate with more coauthors in conferences than in journals. Importantly, conference papers seem to serve as a distinct channel of scholarly communication, not a mere preceding step to journal publications: coauthors and title words of authors across conferences and journals tend not to overlap much. This study corroborates findings of previous studies on this topic from a distinctive perspective and suggests that conference authorship in CS calls for more special attention from scholars and administrators outside CS who have focused on journal publications to mine authorship data and evaluate scholarly performance

Benchmarking some Portuguese S&T system research units: 2nd Edition

The increasing use of productivity and impact metrics for evaluation and comparison, not only of individual researchers but also of institutions, universities and even countries, has prompted the development of bibliometrics. Currently, metrics are becoming widely accepted as an easy and balanced way to assist the peer review and evaluation of scientists and/or research units, provided they have adequate precision and recall. This paper presents a benchmarking study of a selected list of representative Portuguese research units, based on a fairly complete set of parameters: bibliometric parameters, number of competitive projects and number of PhDs produced. The study aimed at collecting productivity and impact data from the selected research units in comparable conditions i.e., using objective metrics based on public information, retrievable on-line and/or from official sources and thus verifiable and repeatable. The study has thus focused on the activity of the 2003-06 period, where such data was available from the latest official evaluation. The main advantage of our study was the application of automatic tools, achieving relevant results at a reduced cost. Moreover, the results over the selected units suggest that this kind of analyses will be very useful to benchmark scientific productivity and impact, and assist peer review.Comment: 26 pages, 20 figures F. Couto, D. Faria, B. Tavares, P. Gon\c{c}alves, and P. Verissimo, Benchmarking some portuguese S\&T system research units: 2nd edition, DI/FCUL TR 13-03, Department of Informatics, University of Lisbon, February 201

Name Disambiguation from link data in a collaboration graph using temporal and topological features

In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records of multiple persons under a single reference. Such mistakes affect the performance of document retrieval, web search, database integration, and more importantly, improper attribution of credit (or blame). The task of entity disambiguation partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available, or they are costly to obtain. Besides, the attempt of collecting biographical or external data sustains the risk of privacy violation. In this work, we propose a method for solving entity disambiguation task from link information obtained from a collaboration network. Our method is non-intrusive of privacy as it uses only the time-stamped graph topology of an anonymized network. Experimental results on two real-life academic collaboration networks show that the proposed method has satisfactory performance.Comment: The short version of this paper has been accepted to ASONAM 201

Academic careers in Computer Science: Continuance and transience of lifetime co-authorships

International audienceScholarly publications reify fruitful collaborations between co-authors. A branch of research in the Science Studies focuses on analyzing the co-authorship networks of established scientists. Such studies tell us about how their collaborations developed through their careers. This paper updates previous work by reporting a transversal and a longitudinal studies spanning the lifelong careers of a cohort of researchers from the DBLP bibliographic database. We mined 3,860 researchers' publication records to study the evolution patterns of their co-authorships. Two features of co-authors were considered: 1) their expertise, and 2) the history of their partnerships with the sampled researchers. Our findings reveal the ephemeral nature of most collaborations: 70% of the new co-authors were only one-shot partners since they did not appear to collaborate on any further publications. Overall, researchers consistently extended their co-authorships 1) by steadily enrolling beginning researchers (i.e., people who had never published before), and 2) by increasingly working with confirmed researchers with whom they already collaborated

Scale‐free collaboration networks: An author name disambiguation perspective

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149559/1/asi24158.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149559/2/asi24158_am.pd

Bibliometrics: Integrating the Computing Sciences Unit of Tampere University into CSRankings

Universities have gained increasing influence on the social development through their teach- ing and research duties. Thus, it is crucial to have a concrete approach to evaluate the academic performance of universities. Besides, as a result of the globalization, a benchmark tool for universi- ties in the international level is unavoidably needed. There are global university rankings that have been widely referenced in recent years. However, many of them are reputation-based rankings which use biased methodologies and subjective data for evaluating the academic performance of universities. To solve this problem, metric-based rankings which utilize transparent approaches and objective data appeared. In this thesis, I focus on CSRankings, a metric-based ranking which ranks universities in the computer science field. In addition, I integrated the Computing Sciences Unit of Tampere University within the Faculty of Information Technology and Communi- cation Science to the database of CSRankings. As a result, Tampere University is now presented in CSRankings; thus, prospective students, researchers, and investors can have better tools to evaluate the academic performance of Tampere University in the international level within the computer science field

Publication Culture in Computing Research

The dissemination of research results is an integral part of research and hence a crucial component for any scientific discipline. In the area of computing research, there have been raised concerns recently about its publication culture, most notably by highlighting the high priority of conferences (compared to journals in other disciplines) and -- from an economic viewpoint -- the costs of preparing and accessing research results. The Dagstuhl Perspectives Workshop 12452 “Publication Culture in Computing Research” aimed at discussing the main problems with a selected group of researchers and practitioners. The goal was to identify and classify the current problems and to suggest potential remedies. The group of participants was selected in a way such that a wide spectrum of opinions would be presented. This lead to intensive discussions. The workshop is seen as an important step in the ongoing discussion. As a main result, the main problem roots were identified and potential solutions were discussed. The insights will be part of an upcoming manifesto on Publication Culture in Computing Research