Data, measurement and empirical methods in the science of science
The advent of large-scale datasets that trace the workings of science has encouraged
researchers from many different disciplinary backgrounds to turn scientific methods into …
researchers from many different disciplinary backgrounds to turn scientific methods into …
A survey of information cascade analysis: Models, predictions, and recent advances
The deluge of digital information in our daily life—from user-generated content, such as
microblogs and scientific papers, to online business, such as viral marketing and advertising …
microblogs and scientific papers, to online business, such as viral marketing and advertising …
Temporal cross-effects in knowledge tracing
Knowledge tracing (KT) aims to model students' knowledge level based on their historical
performance, which plays an important role in computer-assisted education and adaptive …
performance, which plays an important role in computer-assisted education and adaptive …
[HTML][HTML] Predicting the citations of scholarly paper
X Bai, F Zhang, I Lee - Journal of Informetrics, 2019 - Elsevier
Citation prediction of scholarly papers is of great significance in guiding funding allocations,
recruitment decisions, and rewards. However, little is known about how citation patterns …
recruitment decisions, and rewards. However, little is known about how citation patterns …
Early indicators of scientific impact: Predicting citations with altmetrics
Identifying important scholarly literature at an early stage is vital to the academic research
community and other stakeholders such as technology companies and government bodies …
community and other stakeholders such as technology companies and government bodies …
Modeling item-specific temporal dynamics of repeat consumption for recommender systems
Repeat consumption is a common scenario in daily life, such as repurchasing items and
revisiting websites, and is a critical factor to be taken into consideration for recommender …
revisiting websites, and is a critical factor to be taken into consideration for recommender …
Utilizing citation network structure to predict paper citation counts: A deep learning approach
Q Zhao, X Feng - Journal of Informetrics, 2022 - Elsevier
With the advancement of science and technology, the number of academic papers
published each year has increased almost exponentially. While a large number of research …
published each year has increased almost exponentially. While a large number of research …
Barriers and boosts: Using inequity frames theory to expand understanding of mechanisms of race and gender inequity
Inequity can be framed in terms of disadvantage or advantage, with different consequences
for how people understand the inequity. Here we ask, how do scholars conceptualize race …
for how people understand the inequity. Here we ask, how do scholars conceptualize race …
The coverage of Microsoft Academic: Analyzing the publication output of a university
This is the first detailed study on the coverage of Microsoft Academic (MA). Based on the
complete and verified publication list of a university, the coverage of MA was assessed and …
complete and verified publication list of a university, the coverage of MA was assessed and …
A deep-learning based citation count prediction model with paper metadata semantic features
A Ma, Y Liu, X Xu, T Dong - Scientometrics, 2021 - Springer
Predicting the impact of academic papers can help scholars quickly identify the high-quality
papers in the field. How to develop efficient predictive model for evaluating potential papers …
papers in the field. How to develop efficient predictive model for evaluating potential papers …