---
task_categories:
- text-classification
language:
- en
task_ids:
- sentiment-classification
- hate-speech-detection
size_categories:
- 1K<n<10K
---
# Tweet Annotation Sensitivity Experiment 1: Annotation in Six Experimental Conditions

***<font color= red>Attention: This repository contains cases that might be offensive or upsetting. We do not support the views expressed in these hateful posts.</font>***

## Description

We drew a stratified sample of 20 tweets, that were pre-annotated in a study by [Davidson et al. (2017)](https://ojs.aaai.org/index.php/ICWSM/article/view/14955) for Hate Speech / Offensive Language / Neither. The stratification was done with respect to majority-voted class and level of disagreement.

We then recruited 1000 [Prolific](https://www.prolific.com/) workers to annotate each of the 20 tweets. Annotators were randomly selected into one of six experimental conditions, as shown in the following figures. In these conditions, they were asked to assign the labels Hate Speech / Offensive Language / Neither.

In addition, we collected a variety of demographic variables (e.g. age and gender) and some para data (e.g. duration of the whole task, duration per screen).


<img src="https://raw.githubusercontent.com/boleima/tweet-annotation-supplements/main/figs/image.png" width = "500" height = "250" alt="" align=center />


## Examples of Annotation Conditions

Here we show some examples of the annotation conditions:

Condition A
<img src="https://raw.githubusercontent.com/boleima/tweet-annotation-supplements/main/figs/condition_a.png" width = "500" height = "250" alt="" align=center />

Condition C
<img src="https://raw.githubusercontent.com/boleima/tweet-annotation-supplements/main/figs/condition_c.png" width = "500" height = "250" alt="" align=center />

Condition E
<img src="https://raw.githubusercontent.com/boleima/tweet-annotation-supplements/main/figs/condition_e.png" width = "500" height = "250" alt="" align=center />


## Tweets
We use the following 20 tweets from [Davidson et al. (2017)](https://ojs.aaai.org/index.php/ICWSM/article/view/14955). The usernames were hashed.

| Tweet ID | Tweets Hashed       |
| -------------- | ------------------ |
|1|Jihadi John has struck again. Prayers with the victims' families. What is the #bounty on His head? Time 4 him 2 meet allah|
|2|RT @#####: Seriously, Florida. A vote for Charlie Christ is a vote for taxes and ebola.|
|3|Islamic Jihadis run away to Pakistan @##### @##### #UniteBlue|
|4|At this rate, I'd cheer for the awful New York Yankees over the St. Louis Cardinals.|
|5|Allergies have my eyes all red and chink eyed, I look like I'm stoned|
|6|Not protected in the state of Utah. There is no fear of queer couples forcing churches to marry them. They do not legally have to do so.|
|7|RT @#####: Boss Niggas Fuk wit Boss bitches Vice versa..|
|8|RT @#####: ever wanna text somebody and be like bitch die I hope you don't wake up you low down dirty muthafxcka&#128520|
|9|@##### @##### @##### she's a right twat, I'd tell you, honestly Sky! Honestly &#128520|
|10|So yall give farwells to Lulu yet did all but shit on Kris? Ok bitches... ok|
|11|RT @#####: Dis bitch wanna smoke all our weed|
|12|Shittin on all my old hoes|
|13|Getting hit off a cunt thats about 6 foot sideways and a cunt that was in the army lol, i dini care, yous are fuckin laughable|
|14|When it rains it's good "go to the mall weather" all the coons be at home|
|15|Don't mind black people.....hate niggers!|
|16|My eyes feel so chink eyed|
|17|"From now on, I will call all radical MUSLIMS niggers!It is very fitting  and it is racist! I AM RACIST AGAINST ANYONE WHO HATES AMERICA!"""|
|18|RT @#####: Fucking chinks in Clash of Clans always fuck me up. Bitch ass kamikaze faggots.|
|19|@##### ya I know all the slang I'm racist I h8 porch monkies|
|20|RT @#####: Stupid fucking nigger LeBron. You flopping stupid jungle bunny monkey faggot.|


## Codebook
| Column Name | Description       | Type       |
| -------------- | ------------------ |---------------- |
|id|annotator ID|integer|
|age|Age|integer|
|gender|Gender<br> 1: Female<br>2: Male<br> 3: Something Else<br> 4: Prefer not to say<br> |factor|
|afam|African-American<br> 0: No<br> 1: Yes|binary|
|asian|Asian-American<br> 0: No<br> 1: Yes|binary|
|hispanic|Hispanic<br> 0: No<br> 1: Yes|binary|
|white|White<br> 0: No<br> 1: Yes|binary|
|race_other|Other race/ethnicity<br> 0: No<br> 1: Yes|binary|
|race_not_say|Prefer not to say race/ethnicity<br> 0: No<br> 1: Yes|binary|
|education|Highest educational attainment<br> 1: Less than high school<br>2: High school<br> 3: Some college<br> 4: College graduate<br> 5: Master's degree or professional degree (Law, Medicine, MPH, etc.) <br> 6: Doctoral degree (PhD, DPH, EdD, etc.)|factor|
|sexuality|Sexuality<br> 1: Gay or Lesbian<br>2: Bisexual<br> 3: Straight<br> 4: Something Else<br> |factor|
|english|English first language? <br> 0: No<br> 1: Yes|binary|
|tw_use|Twitter Use <br> 1: Most days<br>2: Most weeks,  but not every day<br> 3: A few times a month<br> 4: A few times a year<br> 5: Less often <br>  6: Never|factor|
|social_media_use|Social Media Use<br> 1: Most days<br>2: Most weeks,  but not every day<br> 3: A few times a month<br> 4: A few times a year<br> 5: Less often <br>  0: Never|factor|
|prolific_hours|Prolific hours worked last month|integer|
|task_fun|Coding work was: fun<br> 0: No<br> 1: Yes|binary|
|task_interesting|Coding work was: interesting<br> 0: No<br> 1: Yes|binary|
|task_boring|Coding work was: boring<br> 0: No<br> 1: Yes|binary|
|task_repetitive|Coding work was: repetitive<br> 0: No<br> 1: Yes|binary|
|task_important|Coding work was: important<br> 0: No<br> 1: Yes|binary|
|task_depressing|Coding work was: depressing<br> 0: No<br> 1: Yes|binary|
|task_offensive|Coding work was: offensive<br> 0: No<br> 1: Yes|binary|
|another_tweettask|Likelihood to do another Tweet related task<br> not at all: Not at all likely<br> somewhat: Somewhat likely<br> very: Very likely|factor|
|another_hatetask|Likelihood to do another Hate Speech related task<br> not at all: Not at all likely<br> somewhat: Somewhat likely<br> very: Very likely|factor|
|page_history|Order in which annotator saw pages|character|
|date_of_first_access|Datetime of first access|datetime|
|date_of_last_access|Datetime of last access|datetime|
|duration_sec|Task duration in seconds|integer|
|version|Version of annotation task <br> A: Version A<br>B: Version B<br> C: Version C<br> D: Version D<br> E: Version E<br> F: Version F|factor|
|tw1-20|Label assigned to Tweet 1-20<br> hate speech: Hate Speech<br> offensive language: Offensive Language<br> neither: Neither HS nor OL <br> NA: Missing or "don't know"|factor|
|tw_duration_1-20|Annotation duration in milliseconds Tweet 1-20|numerical|
|num_approvals|Prolific data: number of previous task approvals of annotator|integer|
|num_rejections|Prolific data: number of previous task rejections of annotator|integer|
|prolific_score|Annotator quality score by Prolific|numerical|
|countryofbirth|Prolific data: Annotator country of birth|character|
|currentcountryofresidence|Prolific data: Annotator country of residence|character|
|employmentstatus|Prolific data: Annotator Employment Status<br> Full-timePart-time<br> Unemployed (and job-seeking)<br> Due to start a new job within the next month<br> Not in paid work (e.g. homemaker, retired or disabled)<br> Other<br> DATA EXPIRED|factor|
|firstlanguage|Prolific data: Annotator first language|character|
|nationality|Prolific data: Nationality|character|
|studentstatus|Prolific data: Student status<br> Yes<br> No <br> DATA EXPIRED|factor|

## Citation

If you found the dataset useful, please cite:

```
@InProceedings{beck2022,
      author="Beck, Jacob and Eckman, Stephanie and Chew, Rob and Kreuter, Frauke",
      editor="Chen, Jessie Y. C. and Fragomeni, Gino and Degen, Helmut and Ntoa, Stavroula",
      title="Improving Labeling Through Social Science Insights: Results and Research Agenda",
      booktitle="HCI International 2022 -- Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence",
      year="2022",
      publisher="Springer Nature Switzerland",
      address="Cham",
      pages="245--261",
      isbn="978-3-031-21707-4"
}
```