Thomas Kleinbauer

Natural Language Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 14 citations into it; #3,394 of 5,688 by trust here, #3,107 by citations
• Artificial Intelligence — 12 citations into it; #19,888 of 35,345 by trust here, #14,718 by citations
• Safety, Robustness & Interpretability — 8 citations into it; #1,312 of 2,251 by trust here, #1,290 by citations

Whom Thomas Kleinbauer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Zeerak Talat
2. Michael Wiegand
3. Sweta Agrawal
4. Mladen Karan

Who trusts Thomas Kleinbauer overall

1. Bertie Vidgen
2. Svetlana Kiritchenko
3. Isar Nejadgholi

Papers from Thomas Kleinbauer's perspective

Ordered by how strongly the researchers Thomas Kleinbauer trusts endorse each paper. Same corpus, a different order for every researcher.

1. Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
2. Deep Learning for Hate Speech Detection in Tweets
3. Bag of Tricks for Efficient Text Classification
4. Measuring and Mitigating Unintended Bias in Text Classification
5. Understanding Abuse: A Typology of Abusive Language Detection Subtasks
6. Ex Machina: Personal Attacks Seen at Scale
7. Reducing Gender Bias in Abusive Language Detection
8. Detecting Hate Speech on the World Wide Web
9. Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior
10. Cross-Domain Detection of Abusive Language Online

Their papers

• Detection of Abusive Language: the Problem of Biased Datasets (2019) — 268 citations