https://github.com/ben-aaron188/covid19worry
The COVID-19 Real World Worry Datasets
Science Score: 23.0%
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The COVID-19 Real World Worry Datasets
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Created over 6 years ago
· Last pushed over 4 years ago
https://github.com/ben-aaron188/covid19worry/blob/master/
# The COVID-19 Real World Worry Datasets
This repo contains the data and variable descriptions on the Real World Worry Datasets.
Papers on this dataset:
- [1]M. Mozes, I. van der Vegt, and B. Kleinberg, A repeated-measures study on emotional responses after a year in the pandemic, arXiv:2107.03466 [cs], Nov. 2021, Accessed: Nov. 24, 2021. [Online]. Available: http://arxiv.org/abs/2107.03466 (in press at _Scientific Reports_)
- [2]B. Kleinberg, I. van der Vegt, and M. Mozes, Measuring Emotions in the COVID-19 Real World Worry Dataset, presented at the ACL-NLP-COVID19 2020, Online, Jul. 2020. Accessed: Nov. 02, 2020. [Online]. Available: https://www.aclweb.org/anthology/2020.nlpcovid19-acl.11
- [3]I. van der Vegt and B. Kleinberg, Women Worry About Family, Men About the Economy: Gender Differences in Emotional Responses to COVID-19, in Social Informatics, vol. 12467, S. Aref, K. Bontcheva, M. Braghieri, F. Dignum, F. Giannotti, F. Grisolia, and D. Pedreschi, Eds. Cham: Springer, 2020, pp. 397409. doi: 10.1007/978-3-030-60975-7_29.
_Contact: bennett.kleinberg [at] tilburguniversity.edu_
These projects are also available with on the [World Pandemic Research Network](https://wprn.org/#about-us):
- _Measuring emotional responses to COVID-19_ [https://wprn.org/item/459652](https://wprn.org/item/459652); [Presentation on YouTube](https://www.youtube.com/watch?v=ftDKiCrND0k)
- _Gender Differences in Emotional Responses to COVID-19_ [https://wprn.org/item/547252](https://wprn.org/item/547252); [Presentation on YouTube](https://www.youtube.com/watch?v=30M8PFF-TMw)
- _Worry, coping and resignation - A repeated-measures study on emotional responses after a year in the pandemic_ [https://wprn.org/item/545152](https://wprn.org/item/545152); [Presentation on YouTube](https://www.youtube.com/watch?v=Q37Vmq9X6d0)
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### Repo structure
- main
- data_phase_1
- files
- meta
- texts
- short (n=2500)
- long (n=2500)
- files_clean
- liwc
- meta
- texts
- short (n=2491)
- long (n=2491)
- data_repeated_measures
- meta (n=1698)
- texts
- phase1
- long
- short
- phase2
- long
- short
_The directory `./data_phase_1/files` contains all 5000 texts, while `./data_phase_1/files_clean` contains those after the exclusion of 9 participants (as reported in the paper). Note: the LIWC data were only extracted on the "cleaned" data._
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### Variable codebook
| Variable name | Type | Meaning |
|--------------------------- |------------ |-------------------------------------------------------------------------------------------------------- |
| startdate | time stamp | Time of starting the task |
| enddate | time stamp | Time of submitting the task |
| duration | numeric | Duration in seconds |
| worry | numeric | 9-point scale rating (1=low, 9=high) |
| chosen_emotion | string | Choice of emotion that best represented their feeling |
| anger | numeric | 9-point scale rating (1=low, 9=high) |
| disgust | numeric | 9-point scale rating (1=low, 9=high) |
| fear | numeric | 9-point scale rating (1=low, 9=high) |
| anxiety | numeric | 9-point scale rating (1=low, 9=high) |
| sadness | numeric | 9-point scale rating (1=low, 9=high) |
| happiness | numeric | 9-point scale rating (1=low, 9=high) |
| relaxation | numeric | 9-point scale rating (1=low, 9=high) |
| desire | numeric | 9-point scale rating (1=low, 9=high) |
| text_long | string | Text input on long text (500 chars. minumum) |
| text_short | string | Text input on Tweet-sized text (280 chars. maximum) |
| self\_rating_general | numeric | 9-point scale rating (1=low, 9=high) - how well they could express their feelings in text in general |
| self\_rating_short | numeric | 9-point scale rating (1=low, 9=high) - how well they could express their feelings in the short text |
| self\_rating_long | numeric | 9-point scale rating (1=low, 9=high) - how well they could express their feelings in the long text |
| twitter\_general_often | numeric | 9-point scale rating (1=rarely, 9=very often) - how often they are on Twitter |
| twitter\_tweet_often | numeric | 9-point scale rating (1=rarely, 9=very often) - how often they tweet on Twitter |
| twitter\_participate_often | numeric | 9-point scale rating (1=rarely, 9=very often) - how often they participate in conversations on Twitter |
| eng_native | string | Whether English is their native language (Yes, No, No but fluent) |
**Note: in the repeated measures version of the dataset, the variables from phase 1 (April 2020) are denoted as "[VARIABLE]_wave1" and those from phase 2 (April 2021) as "[VARIABLE]_wave2". The "delta" variables are the difference between the values from these two measurements (i.e. phase 2 - phase 1).**
Owner
- Name: BKleinberg
- Login: ben-aaron188
- Kind: user
- Website: https://bkleinberg.net/
- Repositories: 18
- Profile: https://github.com/ben-aaron188
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