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@@ -74,3 +74,6 @@ Goodreads-Mystery/raw/goodreads_reviews_mystery_thriller_crime.json filter=lfs d
 reddit/raw/reddit.csv filter=lfs diff=lfs merge=lfs -text
 amazon_apps/raw/Apps_for_Android_5.json filter=lfs diff=lfs merge=lfs -text
 amazon_apps/raw/meta_Apps_for_Android.json filter=lfs diff=lfs merge=lfs -text
+amazon_apps/emb/output_requests_apps_edge.jsonl filter=lfs diff=lfs merge=lfs -text
+arxiv/dataset/ogbn_arxiv/processed/data_processed filter=lfs diff=lfs merge=lfs -text
+goodreads_children/emb/output_requests_children_edge.jsonl filter=lfs diff=lfs merge=lfs -text

amazon_apps/emb/output_requests_apps_edge.jsonl

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arxiv/arxiv.md

@@ -0,0 +1,18 @@
+# Arxiv
+
+### Dataset Description
+
+The Arxiv dataset is a citation network. Nodes represent the papers. Text on node is based on the nodes' titles and abstracts including following information: `The paper titled '[Title]' presents [Abstract], highlighting the key contributions and findings of the research.`. Edges represent citation relationships between papers. Text on an edge represents the context of the referenced target node from the edge's source node.
+
+## Graph Machine Learning Tasks
+
+### Link Prediction
+Link prediction in the Arxiv dataset involves predicting potential connections between papers.  The goal is to predict whether a paper will cite another paper.
+
+### Node Classification
+Node classification tasks in the arxiv dataset include predicting the paper's category. 
+
+
+## Data references
+
+* Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia.Microsoft academic graph: When experts are not enough. Quantitative Science Studies, 1(1):396–413, 2020

arxiv/dataset/ogbn_arxiv/RELEASE_v1.txt

@@ -0,0 +1,6 @@
+# Release note for ogbn-arxiv
+
+### v1
+
+May 4, 2020
+First major release.

arxiv/dataset/ogbn_arxiv/mapping/README.md

@@ -0,0 +1,15 @@
+# ogbn-arxiv
+
+### nodeidx2paperid.csv.gz
+
+Mapping from node index into the unique paper id used in Microsoft Academic Graph. 
+The actual paper can be found by https://academic.microsoft.com/paper/2894175828, where you need to replace the number (in this case, 2894175828) with the specified paper id.
+
+### labelidx2arxivcategeory.csv.gz
+
+Mapping from label index to the arXiv categories listed in https://arxiv.org/
+
+
+## Data references
+
+* Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia.Microsoft academic graph: When experts are not enough. Quantitative Science Studies, 1(1):396–413, 2020

arxiv/dataset/ogbn_arxiv/mapping/labelidx2arxivcategeory.csv.gz

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arxiv/dataset/ogbn_arxiv/mapping/nodeidx2paperid.csv.gz

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arxiv/dataset/ogbn_arxiv/processed/data_processed

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arxiv/dataset/ogbn_arxiv/raw/node_year.csv.gz

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arxiv/processed/arxiv.pkl

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goodreads_children/emb/output_requests_children_edge.jsonl

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reddit/reddit.md

@@ -13,4 +13,6 @@ Link prediction in the Reddit dataset involves predicting potential connections
 Node classification tasks in the Reddit dataset include predicting the users' category. 
 
 ## Dataset Source
-https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/
+https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/
+
+You can also directly use `reddit.csv` in raw folder we provided. 

twitter/emb/tweets_bert_base_uncased_512_cls_edge.pt

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twitter/emb/tweets_bert_base_uncased_512_cls_node.pt

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twitter/emb/twitter_openai_edge.pt

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twitter/twitter.md

@@ -11,4 +11,6 @@ Link prediction in the tweet dataset involves predicting potential connections b
 
 
 ## Dataset Source
-https://dl.acm.org/doi/10.1145/2505515.2505695
+https://dl.acm.org/doi/10.1145/2505515.2505695
+
+You can also directly use `.npy` files in raw folder we provided.