social networks

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Social circles: Google+

Social circles: Google+

Stefan
Open Dataset
Creators: McAuley, Julian; Leskovec, Jure
Publication Date: 2012

This dataset consists of ‘circles’ from Google+. Google+ data was collected from users who had manually shared their circles using the ‘share circle’ feature. The dataset includes node features (profiles), circles, and ego networks. The dataset includes 107,614 nodes and 13,673,453 edges.

Social circles: Facebook

Social circles: Facebook

Stefan
Open Dataset
Creators: McAuley, Julian; Leskovec, Jure
Publication Date: 2012

This dataset consists of ‘circles’ (or ‘friends lists’) from Facebook. Facebook data was collected from survey participants using this Facebook app. The dataset includes node features (profiles), circles, and ego networks. The dataset includes 4,039 nodes and 88,234 edges. Facebook data has been anonymized by replacing the Facebook-internal ids for each user with a new value.

Food.com Recipe & Review Data

Food.com Recipe & Review Data

Stefan
Open Dataset
Creators: Majumder, Bodhisattwa P.; Li, Shuyang; Ni, Jianmo; McAuley, Julian
Publication Date: 2019
This dataset consists of 180K+ recipes and 700K+ recipe reviews covering 18 years of user interactions and uploads on Food.com (formerly GeniusKitchen), an online recipe aggregator.This dataset contains three sets of data from Food.com:

Interaction splits

  • interactions_test.csv
  • interactions_validation.csv
  • interactions_train.csv

Preprocessed data for result reproduction

In this format, the recipe text metadata is tokenized via the GPT subword tokenizer with start-of-step, etc. tokens.

  • PP_recipes.csv
  • PP_users.csv

To convert these files into the pickle format required to run our code off-the-shelf, you may use pandas.read_csv and pandas.to_pickle to convert the CSV’s into the proper pickle format.

 

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