A survey on bias and fairness in machine learning N Mehrabi, F Morstatter, N Saxena, K Lerman, A Galstyan ACM Computing Surveys (CSUR) 54 (6), 1-35, 2021 | 2474 | 2021 |
Feature selection: A data perspective J Li, K Cheng, S Wang, F Morstatter, RP Trevino, J Tang, H Liu ACM computing surveys (CSUR) 50 (6), 1-45, 2017 | 2307 | 2017 |
Is the Sample Good Enough? Comparing Data from Twitter’s Streaming API with Twitter’s Firehose F Morstatter, J Pfeffer, H Liu, KM Carley International Conference on Weblogs and Social Media, 400-408, 2013 | 1282 | 2013 |
Twitter Data Analytics S Kumar, F Morstatter, H Liu Springer, 2014 | 551 | 2014 |
Advancing Feature Selection Research: ASU Feature Selection Repository Z Zhao, F Morstatter, S Sharma, S Alelyani, A Anand, H Liu School of Computing, Informatics, and Decision Systems Engineering, Arizona …, 2010 | 399* | 2010 |
Misinformation in social media: definition, manipulation, and detection L Wu, F Morstatter, KM Carley, H Liu ACM SIGKDD explorations newsletter 21 (2), 80-90, 2019 | 276 | 2019 |
A New Approach to Bot Detection: Striking the Balance Between Precision and Recall F Morstatter, L Wu, TH Nazer, KM Carley, H Liu ASONAM, 2016 | 208 | 2016 |
When is it biased? Assessing the representativeness of twitter's streaming API F Morstatter, J Pfeffer, H Liu Proceedings of the 23rd international conference on world wide web, 555-556, 2014 | 176 | 2014 |
Tampering with Twitter’s sample API J Pfeffer, K Mayer, F Morstatter EPJ Data Science 7 (1), 50, 2018 | 128 | 2018 |
Mining misinformation in social media L Wu, F Morstatter, X Hu, H Liu Big data in complex and social networks, 135-162, 2016 | 124 | 2016 |
Understanding Twitter Data with TweetXplorer F Morstatter, S Kumar, H Liu, R Maciejewski 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 1482-1485, 2013 | 99 | 2013 |
Leveraging the Implicit Structure within Social Media for Emergent Rumor Detection J Sampson, F Morstatter, L Wu, H Liu | 92 | 2016 |
Whom Should I Follow?: Identifying Relevant Users During Crises. S Kumar, F Morstatter, R Zafarani, H Liu Hypertext, 139-147, 2013 | 82 | 2013 |
Identifying framing bias in online news F Morstatter, L Wu, U Yavanoglu, SR Corman, H Liu ACM Transactions on Social Computing 1 (2), 1-18, 2018 | 72 | 2018 |
Identifying and analyzing cryptocurrency manipulations in social media M Mirtaheri, S Abu-El-Haija, F Morstatter, G Ver Steeg, A Galstyan IEEE Transactions on Computational Social Systems 8 (3), 607-617, 2021 | 61 | 2021 |
Discovering, assessing, and mitigating data bias in social media F Morstatter, H Liu Online Social Networks and Media 1, 1-13, 2017 | 59 | 2017 |
Adaptive spammer detection with sparse group modeling L Wu, X Hu, F Morstatter, H Liu Proceedings of the international AAAI conference on web and social media 11 …, 2017 | 57 | 2017 |
Finding Eyewitness Tweets During Crises F Morstatter, N Lubold, H Pon-Barry, J Pfeffer, H Liu Proceedings of the ACL 2014 Workshop on Language Technologies and …, 2014 | 57 | 2014 |
Man is to person as woman is to location: Measuring gender bias in named entity recognition N Mehrabi, T Gowda, F Morstatter, N Peng, A Galstyan Proceedings of the 31st ACM conference on Hypertext and Social Media, 231-232, 2020 | 55 | 2020 |
SlangSD: building, expanding and using a sentiment dictionary of slang words for short-text sentiment classification L Wu, F Morstatter, H Liu Language Resources and Evaluation 52, 839-852, 2018 | 50 | 2018 |