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Fixed appendix

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  1. README.md +6 -6
README.md CHANGED
@@ -223,7 +223,7 @@ series = {CODASPY '22}
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  This section describes each domain/dataset in greater detail.
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- ### Fake News
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  Fake News used WELFake as a basis. The WELFake dataset combines 72,134 news articles from four pre-existing datasets
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  (Kaggle, McIntire, Reuters, and BuzzFeed Political). The dataset was cleaned of data leaks in the form of citations of
@@ -249,7 +249,7 @@ There are 20456 samples in the dataset, contained in `phishing.jsonl`. For repro
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  and validation sets in 80/10/10 ratio. They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 16364 samples, the validation and the test sets have 2064 and 2064 samles, respectively.
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- ### Job Scams
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  The Employment Scam Aegean Dataset, henceforth referred to as the Job Scams dataset, consisted of 17,880 human-annotated job listings of
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  job descriptions labeled as fraudulent or not.
@@ -278,7 +278,7 @@ For reproduceability, the data is also split into training, test, and validation
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 11436 samples, the validation and the test sets have 1429 and 1430 samles, respectively.
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- ### Phishing
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  This dataset consists of various phishing attacks as well as benign emails collected from real users.
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@@ -300,7 +300,7 @@ For reproduceability, the data is also split into training, test, and validation
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 12217 samples, the validation and the test sets have 1527 and 1528 samles, respectively.
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- ### Political Statements
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  This corpus was created from the Liar dataset which consists of political statements made by US speakers assigned
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  a fine-grain truthfulness label by PolitiFact.
@@ -351,7 +351,7 @@ For reproduceability, the data is also split into training, test, and validation
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 9997 samples, the validation and the test sets have 1250 samles each in them.
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- ### Product Reviews
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  We post-process and split Product Reviews dataset to ensure uniformity with Political Statements 2.0 and Twitter Rumours as they all go into form GDDS-2.0
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@@ -397,7 +397,7 @@ test, and validation sets in 80/10/10 ratio. They are named `train.jsonl`, `test
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  The sampling process was stratified. The training set contains 5259 samples, the validation and the test sets have 657 and 658 samles,
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  respectively.
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- ### Rumors dataset
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  This deception dataset was created using PHEME dataset from
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  This section describes each domain/dataset in greater detail.
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+ ### FAKE NEWS
227
 
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  Fake News used WELFake as a basis. The WELFake dataset combines 72,134 news articles from four pre-existing datasets
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  (Kaggle, McIntire, Reuters, and BuzzFeed Political). The dataset was cleaned of data leaks in the form of citations of
 
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  and validation sets in 80/10/10 ratio. They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 16364 samples, the validation and the test sets have 2064 and 2064 samles, respectively.
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+ ### JOB SCAMS
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  The Employment Scam Aegean Dataset, henceforth referred to as the Job Scams dataset, consisted of 17,880 human-annotated job listings of
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  job descriptions labeled as fraudulent or not.
 
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 11436 samples, the validation and the test sets have 1429 and 1430 samles, respectively.
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+ ### PHISHING
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  This dataset consists of various phishing attacks as well as benign emails collected from real users.
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 12217 samples, the validation and the test sets have 1527 and 1528 samles, respectively.
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+ ### POLITICAL STATEMENTS
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  This corpus was created from the Liar dataset which consists of political statements made by US speakers assigned
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  a fine-grain truthfulness label by PolitiFact.
 
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  They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified.
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  The training set contains 9997 samples, the validation and the test sets have 1250 samles each in them.
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+ ### PRODUCT REVIEWS
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  We post-process and split Product Reviews dataset to ensure uniformity with Political Statements 2.0 and Twitter Rumours as they all go into form GDDS-2.0
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  The sampling process was stratified. The training set contains 5259 samples, the validation and the test sets have 657 and 658 samles,
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  respectively.
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+ ### TWITTER RUMOURS
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  This deception dataset was created using PHEME dataset from
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