Predicting worker disagreement for more effective crowd labeling
Crowdsourcing is a popular mechanism used for labeling tasks to produce large corpora for
training. However, producing a reliable crowd labeled training corpus is challenging and …
training. However, producing a reliable crowd labeled training corpus is challenging and …
How do annotators label short texts? toward understanding the temporal dynamics of tweet labeling
S Räbiger, M Spiliopoulou, Y Saygın - Information Sciences, 2018 - Elsevier
Crowdsourcing is a popular means to obtain human-crafted information, for example labels
of tweets, which can then be used in text mining tasks. Many studies investigate the quality …
of tweets, which can then be used in text mining tasks. Many studies investigate the quality …
Performance comparison of crowdworkers and NLP tools on named-entity recognition and sentiment analysis of political tweets
We report results of a comparison of the accuracy of crowdworkers and seven Natural
Language Processing (NLP) toolkits in solving two important NLP tasks, named-entity …
Language Processing (NLP) toolkits in solving two important NLP tasks, named-entity …
BUOCA: budget-optimized crowd worker allocation
Due to concerns about human error in crowdsourcing, it is standard practice to collect labels
for the same data point from multiple internet workers. We here show that the resulting …
for the same data point from multiple internet workers. We here show that the resulting …
How does tweet difficulty affect labeling performance of annotators?
S Räbiger, Y Saygın, M Spiliopoulou - arXiv preprint arXiv:1808.00388, 2018 - arxiv.org
Crowdsourcing is a popular means to obtain labeled data at moderate costs, for example for
tweets, which can then be used in text mining tasks. To alleviate the problem of low-quality …
tweets, which can then be used in text mining tasks. To alleviate the problem of low-quality …
Analyzing crowd workers' learning behavior to obtain more reliable labels
S Rabiger - 2018 - research.sabanciuniv.edu
Crowdsourcing is a popular means to obtain high-quality labels for datasets at moderate
costs. These crowdsourced datasets are then used for training supervised or …
costs. These crowdsourced datasets are then used for training supervised or …
Accurate and budget-efficient text, image, and video analysis systems powered by the crowd
M Sameki - 2017 - search.proquest.com
Crowdsourcing systems empower individuals and companies to outsource labor-intensive
tasks that cannot currently be solved by automated methods and are expensive to tackle by …
tasks that cannot currently be solved by automated methods and are expensive to tackle by …