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authors: Kadhim Hayawi, Sujith Mathew, Neethu Venugopal, Mohammad M. Masud, Pin‑Han Ho
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link: https://link.springer.com/article/10.1007/s13278-022-00869-w
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file structure:
├── boto-19/
├── cresci-18/
├── cresci-17/
├── cresci-19/
├── twibot-22/
├── midterm-18/
├── cresci-15/
├── twibot-20/
├── gilani-17/
├── run.py
└── Hayawi.md # README
- implement details: “Sentiment”, “Timing” features are discarded since required information is not included in datasets.
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preprocess the dataset and train this model by running
python run.py {dataset name}
twibot-22 for example :
python run.py twibot-22
- dataset names:
- boto-19
- cresci-18
- cresci-17
- cresci-19
- twibot-22
- midterm-18
- cresci-15
- twibot-20
- gilani-17
- dataset names:
dataset | acc | precison | recall | f1 | |
---|---|---|---|---|---|
Cresci-2015 | mean | 0.8427 | 0.9296 | 0.7931 | 0.8556 |
Cresci-2015 | std | 0.0002 | 0.0003 | 0.0002 | 0.0001 |
Twibot-20 | mean | 0.7314 | 0.7161 | 0.8350 | 0.7705 |
Twibot-20 | std | 0.0001 | 0.0001 | 0.0004 | 0.0002 |
Twibot-22 | mean | 0.7650 | 0.8000 | 0.1499 | 0.2474 |
Twibot-22 | std | 0.0007 | 0.0027 | 0.0005 | 0.0008 |
Gilani-17 | mean | 0.5270 | 0.5144 | 0.2800 | 0.3467 |
Gilani-17 | std | 0.0002 | 0.0005 | 0.0013 | 0.0011 |
Cresci-2017 | mean | 0.9078 | 0.9547 | 0.9219 | 0.9378 |
Cresci-2017 | std | 0.0001 | 0.0001 | 0.0003 | 0.0001 |
Cresci-stock-2018 | mean | 0.5002 | 0.5073 | 0.7116 | 0.6075 |
Cresci-stock-2018 | std | 0.0002 | 0.0003 | 0.0007 | 0.0006 |
Cresci-rtbust-2019 | mean | 0.5118 | 0.4882 | 0.8125 | 0.6087 |
Cresci-rtbust-2019 | std | 0.0002 | 0.0001 | 0.0009 | 0.0003 |
Midterm-2018 | mean | 0.8459 | 0.8530 | 0.9864 | 0.9148 |
Midterm-2018 | std | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
Botometer-feedback-2019 | mean | 0.7698 | 0.2500 | 0.1778 | 0.2049 |
Botometer-feedback-2019 | std | 0.0002 | 0.0006 | 0.0006 | 0.0006 |
baseline | acc on Twibot-22 | f1 on Twibot-22 | type | tags |
---|---|---|---|---|
Hayawi et al. | 0.7650 | 0.2474 | F | lstm |