18 research outputs found
From little things, big things grow: trends and fads in 110 years of Australian ornithology
Publishing histories can reveal changes in ornithological effort, focus or direction through time. This study presents a bibliometric content analysis of Emu (1901–2011) which revealed 115 trends (long-term changes in publication over time) and 18 fads (temporary increases in publication activity) from the classification of 9,039 articles using 128 codes organised into eight categories (author gender, author affiliation, article type, subject, main focus, main method, geographical scale and geographical location). Across 110 years, private authorship declined, while publications involving universities and multiple institutions increased; from 1960, female authorship increased. Over time, question-driven studies and incidental observations increased and decreased in frequency, respectively. Single species and ‘taxonomic group’ subjects increased while studies of birds at specific places decreased. The focus of articles shifted from species distribution and activities of the host organisation to breeding, foraging and other biological/ecological topics. Site- and Australian-continental-scales slightly decreased over time; non-Australian studies increased from the 1970s. A wide variety of fads occurred (e.g. articles on bird distribution, 1942–1951, and using museum specimens, 1906–1913) though the occurrence of fads decreased over time. Changes over time are correlated with technological, theoretical, social and institutional changes, and suggest ornithological priorities, like those of other scientific disciplines, are temporally labil
Comparative wood anatomy of species of Psychotria L. (Rubiaceae) in Atlantic Rainforest remnants of Rio de Janeiro State, Brazil
Mean Field Analysis of Personalized PageRank with Implications for Local Graph Clustering
International audienceWe analyse a mean-field model of Personalized PageRank on the Erdos-Renyi random graph containing a denser planted Erdos-Renyi subgraph. We investigate the regimes where the values of Personalized PageRank concentrate around the mean-field value. We also study the optimization of the damping factor, the only parameter in Personalized PageRank. Our theoretical results help to understand the applicability of Personalized PageRank and its limitations for local graph clustering