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Self-citation is the hallmark of productive authors, of any gender
It was recently reported that men self-cite >50% more often than women across a wide variety of disciplines in the bibliographic database JSTOR. Here, we replicate this finding in a sample of 1.6Expand
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Quantifying Conceptual Novelty in the Biomedical Literature
We introduce several measures of novelty for a scientific article in MEDLINE based on the temporal profiles of its assigned Medical Subject Headings (MeSH). First, temporal profiles for all MeSHExpand
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Semi-supervised Named Entity Recognition in noisy-text
Many of the existing Named Entity Recognition (NER) solutions are built based on news corpus data with proper syntax. These solutions might not lead to highly accurate results when being applied toExpand
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Multi-dataset-multi-task Neural Sequence Tagging for Information Extraction from Tweets
Multi-task learning is effective in reducing the required data for learning a task, while ensuring competitive accuracy with respect to single task learning. We study effectiveness ofExpand
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Expertise as an aspect of author contributions
Authors contribute a wide variety of intellectual efforts to a research paper, ranging from initial conceptualization to final analysis and reporting, and many journals today publish the allocatedExpand
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3Idiots at HASOC 2019: Fine-tuning Transformer Neural Networks for Hate Speech Identification in Indo-European Languages
We describe our team 3Idiots’s approach for participating in the 2019 shared task on hate speech and offensive content (HASOC) identification in Indo-European languages. Our approach relies onExpand
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Sentiment Analysis with Incremental Human-in-the-Loop Learning and Lexical Resource Customization
The adjustment of probabilistic models for sentiment analysis to changes in language use and the perception of products can be realized via incremental learning techniques. We provide a free, openExpand
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Enthusiasm and support: alternative sentiment classification for social movements on social media
We present a novel sentiment classifier particularly designed for modeling and analyzing social movements; capturing levels of support (supportive versus non-supportive) and degrees of enthusiasmExpand
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Detecting the Correlation between Sentiment and User-level as well as Text-Level Meta-data from Benchmark Corpora
Do tweets from users with similar Twitter characteristics have similar sentiments? What meta-data features of tweets and users correlate with tweet sentiment? In this paper, we address these twoExpand
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Capturing Signals of Enthusiasm and Support Towards Social Issues from Twitter
Social media enables organizations to learn what users say about their products online, and to engage with their potential audiences. Social media has also been allowing individual users and theExpand
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