Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Update README.md
Browse files
README.md
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@@ -57,25 +57,25 @@ The label2id dictionary can be found at [here](https://huggingface.co/datasets/t
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### Data Splits
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| split
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| test | 1693 | alias of `temporal_2021_test` |
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| train | 2858 | alias of `temporal_2020_train` |
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| validation | 352 | alias of `temporal_2020_validation` |
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| temporal_2020_test | 376 | test set in 2020 period of temporal split |
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| temporal_2021_test | 1693 | test set in 2021 period of temporal split |
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| temporal_2020_train | 2858 | training set in 2020 period of temporal split |
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| temporal_2021_train | 1516 | training set in 2021 period of temporal split |
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| temporal_2020_validation | 352 | validation set in 2020 period of temporal split |
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| temporal_2021_validation | 189 | validation set in 2021 period of temporal split |
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| random_train | 2830 | training set of random split (mix of 2020 and 2021) |
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| random_validation | 354 | validation set of random split (mix of 2020 and 2021) |
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| coling2022_random_test | 3399 | test set of random split used in COLING 2022 Tweet Topic paper |
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| coling2022_random_train | 3598 | training set of random split used in COLING 2022 Tweet Topic paper |
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| coling2022_temporal_test | 3399 | test set of temporal split used in COLING 2022 Tweet Topic paper |
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| coling2022_temporal_train | 3598 | training set of temporal split used in COLING 2022 Tweet Topic paper|
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For the temporal-shift setting, we recommend to train models on `train` (`temporal_2020_train`) with `validation` (`temporal_2020_validation`) and evaluate on `test` (`temporal_2021_test`).
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For the random split, we recommend to train models on `random_train` with `random_validation` and evaluate on `test` (`temporal_2021_test`).
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To get a result that is comparable with the results of the COLING 2022 Tweet Topic paper, please use `coling2022_temporal_train` and `coling2022_temporal_test` for temporal-shift, and `coling2022_random_train` and `coling2022_temporal_test` fir random split (note that the coling2022 split does not have validation set).
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### Data Splits
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| split | number of texts | description |
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|:----------------------------|-----:|:-----|
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| `test` | 1693 | alias of `temporal_2021_test` |
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| 63 |
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| `train` | 2858 | alias of `temporal_2020_train` |
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| 64 |
+
| `validation` | 352 | alias of `temporal_2020_validation` |
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| `temporal_2020_test` | 376 | test set in 2020 period of temporal split |
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| 66 |
+
| `temporal_2021_test` | 1693 | test set in 2021 period of temporal split |
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| 67 |
+
| `temporal_2020_train` | 2858 | training set in 2020 period of temporal split |
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| 68 |
+
| `temporal_2021_train` | 1516 | training set in 2021 period of temporal split |
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| 69 |
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| `temporal_2020_validation` | 352 | validation set in 2020 period of temporal split |
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| `temporal_2021_validation` | 189 | validation set in 2021 period of temporal split |
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| `random_train` | 2830 | training set of random split (mix of 2020 and 2021) |
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| `random_validation` | 354 | validation set of random split (mix of 2020 and 2021) |
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| `coling2022_random_test` | 3399 | test set of random split used in COLING 2022 Tweet Topic paper |
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| `coling2022_random_train` | 3598 | training set of random split used in COLING 2022 Tweet Topic paper |
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| `coling2022_temporal_test` | 3399 | test set of temporal split used in COLING 2022 Tweet Topic paper |
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| `coling2022_temporal_train` | 3598 | training set of temporal split used in COLING 2022 Tweet Topic paper|
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For the temporal-shift setting, we recommend to train models on `train` (or `temporal_2020_train`) with `validation` (or `temporal_2020_validation`) and evaluate on `test` (or `temporal_2021_test`).
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For the random split, we recommend to train models on `random_train` with `random_validation` and evaluate on `test` (`temporal_2021_test`).
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To get a result that is comparable with the results of the COLING 2022 Tweet Topic paper, please use `coling2022_temporal_train` and `coling2022_temporal_test` for temporal-shift, and `coling2022_random_train` and `coling2022_temporal_test` fir random split (note that the coling2022 split does not have validation set).
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