4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CL2020★ 1 cited
Performance Comparison of Crowdworkers and NLP Tools on Named-Entity Recognition and Sentiment Analysis of Political Tweets
Mona Jalal, Kate K. Mays, Lei Guo +1
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 recognition…
cs.HC2019★ 3 cited
BUOCA: Budget-Optimized Crowd Worker Allocation
Mehrnoosh Sameki, Sha Lai, Kate K. Mays +3
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 resultin…
cs.HC2016★ 4 cited
Dynamic Allocation of Crowd Contributions for Sentiment Analysis during the 2016 U.S. Presidential Election
Mehrnoosh Sameki, Mattia Gentil, Kate K. Mays +2
Opinions about the 2016 U.S. Presidential Candidates have been expressed in millions of tweets that are challenging to analyze automatically. Crowdsourcing the analysis of politica…