Search (3 results, page 1 of 1)

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Abstract

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 an article as a unit of analysis. This study takes an author-based approach to analyze the 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 articles, and collaborate with more coauthors in conferences than in journals. Importantly, conference articles 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.

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Abstract

Scholars have often relied on name initials to resolve name ambiguities in large-scale coauthorship network research. This approach bears the risk of incorrectly merging or splitting author identities. The use of initial-based disambiguation has been justified by the assumption that such errors would not affect research findings too much. This paper tests that assumption by analyzing coauthorship networks from five academic fields-biology, computer science, nanoscience, neuroscience, and physics-and an interdisciplinary journal, PNAS. Name instances in data sets of this study were disambiguated based on heuristics gained from previous algorithmic disambiguation solutions. We use disambiguated data as a proxy of ground-truth to test the performance of three types of initial-based disambiguation. Our results show that initial-based disambiguation can misrepresent statistical properties of coauthorship networks: It deflates the number of unique authors, number of components, average shortest paths, clustering coefficient, and assortativity, while it inflates average productivity, density, average coauthor number per author, and largest component size. Also, on average, more than half of top 10 productive or collaborative authors drop off the lists. Asian names were found to account for the majority of misidentification by initial-based disambiguation due to their common surname and given name initials.

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Abstract

Compared to the early versions of smart phones, recent mobile devices have bigger screens that can present more web search results. Several previous studies have reported differences in user interaction between conventional desktop computer and mobile device-based web searches, so it is imperative to consider the differences in user behavior for web search engine interface design on mobile devices. However, it is still unknown how the diversification of screen sizes on hand-held devices affects how users search. In this article, we investigate search performance and behavior on three different small screen sizes: early smart phones, recent smart phones, and phablets. We found no significant difference with respect to the efficiency of carrying out tasks, however participants exhibited different search behaviors: less eye movement within top links on the larger screen, fast reading with some hesitation before choosing a link on the medium, and frequent use of scrolling on the small screen. This result suggests that the presentation of web search results for each screen needs to take into account differences in search behavior. We suggest several ideas for presentation design for each screen size.