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@@ -26,7 +26,7 @@ The dataset contains tweet data annotations of **hate speech** (HS) and **offens
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  + Annotators assigned **<font color=green>Condition D</font>** were first asked to annotate hate speech for all their assigned tweets, and then asked to annotate offensive language for the same set of tweets.
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  + **Condition E** worked the same way, but started with the offensive language annotation task followed by the hate speech annotation task.
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- We recruited 917 (?) annotators via the crowdsourcing platform [Prolific](https://www.prolific.com/) during November and December 2022. Only platform members in the US were eligible. Each annotator annotated up to 50 tweets. The dataset also contains demographic informations of the annotators.
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  Annotators received a fixed hourly wage in excess of the US federal minimum wage after completing the task.
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  <img src="https://datasets-server.huggingface.co/assets/soda-lmu/tweet_test/--/default/train/0/image/image.jpg" width = "300" height = "200" alt="" align=center />
@@ -39,18 +39,4 @@ Annotators received a fixed hourly wage in excess of the US federal minimum wage
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  ## Citation
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- If you found the dataset useful, please cite:
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-
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- ```
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- @InProceedings{becketal_22,
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- author="Beck, Jacob and Eckman, Stephanie and Chew, Rob and Kreuter, Frauke",
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- editor="Chen, Jessie Y. C. and Fragomeni, Gino and Degen, Helmut and Ntoa, Stavroula",
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- title="Improving Labeling Through Social Science Insights: Results and Research Agenda",
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- booktitle="HCI International 2022 -- Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence",
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- year="2022",
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- publisher="Springer Nature Switzerland",
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- address="Cham",
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- pages="245--261",
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- isbn="978-3-031-21707-4"
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- }
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- ```
 
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  + Annotators assigned **<font color=green>Condition D</font>** were first asked to annotate hate speech for all their assigned tweets, and then asked to annotate offensive language for the same set of tweets.
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  + **Condition E** worked the same way, but started with the offensive language annotation task followed by the hate speech annotation task.
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+ We recruited annotators via the crowdsourcing platform [Prolific](https://www.prolific.com/) during November and December 2022. Only platform members in the US were eligible. Each annotator annotated up to 50 tweets. The dataset also contains demographic informations of the annotators.
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  Annotators received a fixed hourly wage in excess of the US federal minimum wage after completing the task.
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  <img src="https://datasets-server.huggingface.co/assets/soda-lmu/tweet_test/--/default/train/0/image/image.jpg" width = "300" height = "200" alt="" align=center />
 
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  ## Citation
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+ If you found the dataset useful, please cite our dataset page.