Datasets:
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README.md
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# Tweet Annotations in
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## Description
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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
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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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# Tweet Annotations in Five Experimental Conditions
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## Description
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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 US-based annotators from the crowdsourcing platform [Prolific](https://www.prolific.com/) during November and December 2022. Each annotator annotated up to 50 tweets. The dataset also contains demographic information about the annotators. 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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