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Building rich machine learning datasets in a scalable manner often necessitates a crowd-sourced data collection pipeline. In this work, we use human studies to investigate the consequences of employing such a pipeline, focusing on the…
Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically…
A computational workflow, also known as workflow, consists of tasks that must be executed in a specific order to attain a specific goal. Often, in fields such as biology, chemistry, physics, and data science, among others, these workflows…
The popularity and rapid development of Cloud Computing in recent years has led to a vast number of publications capturing the accumulated knowledge in this field. Due to the interdisciplinary nature and significant relevance of cloud…
As audio machine learning outcomes are deployed in societally impactful applications, it is important to have a sense of the quality and origins of the data used. Noticing that being explicit about this sense is not trivially rewarded in…
Whether citations can be objectively and reliably used to measure productivity and scientific quality of articles and researchers can, and should, be vigorously questioned. However, citations are widely used to estimate the productivity of…
Scientific topics, claims and resources are increasingly debated as part of online discourse, where prominent examples include discourse related to COVID-19 or climate change. This has led to both significant societal impact and increased…
For the purpose of efficient and cost-effective large-scale data labeling, crowdsourcing is increasingly being utilized. To guarantee the quality of data labeling, multiple annotations need to be collected for each data sample, and truth…
Publishing research data aims to improve the transparency of research results and facilitate the reuse of datasets. In both cases, referencing the datasets that were used is recommended. Research data repositories can support data…
We provide a general framework to model the growth of networks consisting of different coupled layers. Our aim is to estimate the impact of one such layer on the dynamics of the others. As an application, we study a scientometric network,…
In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles. We formulate this problem as a sequence labeling task solved using a hierarchical BiLSTM model. We contribute a new…
In recent years, citizen science has become a larger and larger part of the scientific community. Its ability to crowd source data and expertise from thousands of citizen scientists makes it invaluable. Despite the field's growing…
Scientific talks are a growing medium for disseminating research, and automatically identifying relevant literature that grounds or enriches a talk would be highly valuable for researchers and students alike. We introduce Reference…
Research accomplishment is usually measured by considering all citations with equal importance, thus ignoring the wide variety of purposes an article is being cited for. Here, we posit that measuring the intensity of a reference is crucial…
In recent years, many studies have been focusing on predicting the scientific impact of research papers. Most of these predictions are based on citations count or rely on features obtainable only from already published papers. In this…
Causal inference from observational data is the goal of many data analyses in the health and social sciences. However, academic statistics has often frowned upon data analyses with a causal objective. The introduction of the term "data…
Following the widespread digitalization of scholarship, software has become essential for research, but the current sociotechnical system of citation does not reflect this sufficiently. Citation provides context for research, but the…
The sharing and citation of research data is becoming increasingly recognized as an essential building block in scientific research across various fields and disciplines. Sharing research data allows other researchers to reproduce results,…
Recently, graphs have been widely used to represent many different kinds of real world data or observations such as social networks, protein-protein networks, road networks, and so on. In many cases, each node in a graph is associated with…
Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious…