TwiCOVID19 Dataset

Data Collection

We utilized a web crawler to climb Twitter to build a TwiCOVID19 dataset of the COVID-19 pandemic.

We replaced URLs and user handles (@user-name) with the symbols “<url>” and “<user>”

We label tweets with positive, neutral, or negative polarities using TextBlob

The timeframe of the TwiCOVID19 dataset is from 2021-01-01 00:00:00 to 2021-12-31 23:59:59.

Data files

1. covid19_tweet.csv desipts information of tweets.
2. covid19_user.csv desipts information of users.

Data Statistics

1. Event tags: #covid19, #covid-19, #coronaviruspandemic, #coronavirus, and others.
2. Tweet information: tweet ID, content, posting time, user ID, tag, number of retweets, number of favorited, number of replies, source tweet ID (unique field of retweets), and sentiment label.
3. User information: user ID, gender, nickname, number of followers, number of friends, number of favorites, and number of users’ tweets.

Here is the statistics of TwiCOVID19 dataset (“#” DENOTES “NUMBER OF”):

Statistic	TwiCOVID19
# Tweets	17,675 5
# Positive tweets	10,052
# Neutral tweets	3,999
# Negative tweets	3,624
avg. # words per tweet	23
# Users	7,489
# Forwarding tweets of users	15,350
Density of user forwarding network	0.0274%

Citation

Please cite our repository if you use TRESP in your work.

@article{zhang2024modeling,
  title={Modeling group-level public sentiment in social networks through topic and role enhancement},
  author={Zhang, Ruwen and Liu, Bo and Cao, Jiuxin and Zhao, Hantao and Sun, Xuheng and Liu, Yan and Sun, Xiangguo},
  journal={Knowledge-Based Systems},
  pages={112594},
  year={2024},
  publisher={Elsevier}
}