Resources by Stefan

Netflix Prize Data Set

Netflix Prize Data Set

Stefan
Open Dataset
Creators: Netflix
Publication Date: 2009
Creators: Netflix

This dataset was constructed to support participants in the Netflix Prize. See [Web Link] for details about the prize.

There are over 480,000 customers in the dataset, each identified by a unique integer id.

The title and release year for each movie is also provided. There are over 17,000 movies in the dataset, each identified by a unique integer id.

The dataset contains over 100 million ratings and has a size of 7,7 kB. The ratings were collected between October 1998 and December 2005 and reflect the distribution of all ratings received during this period. Each rating has a customer id, a movie id, the date of the rating, and the value of the rating.

As part of the original Netflix Prize a set of ratings was identified whose rating values were not provided in the original dataset. The object of the Prize was to accurately predict the ratings from this ‘qualifying’ set. These missing ratings are now available in the grand_prize.tar.gz dataset file.

Soccer Power Index (SPI) Ratings

Soccer Power Index (SPI) Ratings

Stefan
Open Dataset
Creators: FiveThirtyEight
Publication Date: 2022
Creators: FiveThirtyEight

This file contains links to the data behind our Club Soccer Predictions and Global Club Soccer Rankings. These data analyse soccer team performances worldwide,  providing valuable insights into team strengths and match outcomes.

The SPI database covers data up to the year 2022 with a total size of 52,6 kB and includes the following metrics:​

  • SPI Rating: An overall measure of a team’s strength, combining offensive and defensive capabilities.​

  • Offensive and Defensive Ratings: Separate evaluations of a team’s attacking and defensive proficiencies.​

  • Match Probabilities: Predicted probabilities for home win, away win, and draw outcomes, offering insights into expected match results.​

  • Projected Scores: Anticipated goal counts for both home and away teams, aiding in match analysis and forecasting.

 

2020 U.S. Election Emails

2020 U.S. Election Emails

Stefan
Open Dataset
Creators: Mathur, Arunesh; Wang, Angelina; Schemmer, Carsten; Hami, Maia; Stewart, Brandom M; Narayanan; Arvind
Publication Date: 2023
Creators: Mathur, Arunesh; Wang, Angelina; Schemmer, Carsten; Hami, Maia; Stewart, Brandom M; Narayanan; Arvind

This is a preliminary release of the code and data associated with the research paper “Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 U.S. election cycle”.

The corpus contains emails from over 3,000 political campaigns and organizations in the 2020 election cycle in the U.S. The corpus aims to be comprehensive and includes coverage of emails from the candidates in prominent federal and state races as well as political organizations such as Political Action Committees (PACs) and political parties active in the 2020 cycle. We automated the process of signing up to receive emails from the websites of the political campaigns and organizations. For each entity’s website, if the bot discovered an email sign-up form, it filled it in with the information of a fictional recipient The entire dataset contains 317,366 emails.

Comparative Constitution Project Data

Comparative Constitution Project Data

Stefan
Open Dataset
Creators: Comparative Constitutional Project
Publication Date: 2022
Creators: Comparative Constitutional Project

The dataset includes information on 799 constitutional systems and 2,999 amendments across various countries since 1789. The primary objective of the CCP is to record the characteristics of national constitutions written since 1789. The CCP aims to fill this informational gap by providing systematic data to comparative legal scholars for analysis long before they provide advice to constitution drafters. It is our hope that the analysis of, and insights from, these data will promote peace, justice, and human development through the constitution making process. The dataset has s a size of approximately 435 kB and is organized into several key components:​

  • Chronology of Constitutional Events: This component documents each constitutional event (e.g., adoption, amendment, suspension) for recognized independent states since 1789. ​

  • Constitutional Texts: The CCP has collected the texts of nearly every constitutional system as well as most amendments, providing a repository for textual analysis. ​

  • Characteristics of National Constitutions: This dataset includes approximately 650 variables coded for each constitution, detailing various aspects such as governmental structure, rights, and amendment processes.

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Stefan
Open Dataset
Creators: Henderson, Peter; Krass, Mark S.; Zheng, Lucia; Guha Neel; Manning, Christopher D.; Jurafsky, Dan; Ho, Daniel E.
Publication Date: 2022
Creators: Henderson, Peter; Krass, Mark S.; Zheng, Lucia; Guha Neel; Manning, Christopher D.; Jurafsky, Dan; Ho, Daniel E.

We curate a large corpus of legal and administrative data. The utility of this data is twofold: (1) to aggregate legal and administrative data sources that demonstrate different norms and legal standards for data filtering; (2) to collect a dataset that can be used in the future for pretraining legal-domain language models, a key direction in access-to-justice initiatives. The data encompasses a vast number of observations, meticulously collected from 35 distinct sources. These sources include court opinions, contracts, administrative rules, legislative records, and more, reflecting various norms and legal standards for data filtering. The dataset has a size of 256GB. The temporal coverage of the dataset varies across its subsets, as each source spans different time ranges. For instance, U.S. court opinions from CourtListener are synchronized as of December 31, 2022, while the Federal Register includes draft rulemaking documents filed by agencies over an extended period.

Political risks and Covid-19 measures

Political risks and Covid-19 measures

Stefan
Open Dataset
Creators: Firm-level-risk
Publication Date: 2019
Creators: Firm-level-risk

This website aggregates firm-level measures of exposure, risk, and sentiment constructed using textual analysis of quarterly earnings conference calls held by more than 11,000 listed firms in 81 countries. The data draws on work in three papers:
In our paper “Firm-Level Political Risk: Measurement and Effects,” as published in the Quarterly Journal of Economics , we construct measures of political sentiment and risk ranging from 2002 to 2021q2.

Reference & details
In “The Global Impact of Brexit Uncertainty,” we extend this methodology to construct measures of the costs, benefits, and risks associated with specific shocks, such as the UK’s decision to leave the EU. Our measures of Brexit exposure, risk, and sentiment are currently updated through the first quarter of 2019.

Reference & details
In a third paper, “Firm-level Exposure to Epidemic Disease: Covid-19, SARS, and H1N1,” we apply the same methodology to construct measures of costs, benefits, and risks individual firms associate with the spread of Covid-19, SARS, H1N1, Ebola, Zika, and MERS, ranging 2002 to 2021q2.

The dataset (csv) is about 76.1 MB large.

Every single word - A new dataset including all parliamentary materials published in Germany

Every single word - A new dataset including all parliamentary materials published in Germany

Stefan
Open Dataset
Creators: Remschel, Tobias; Kroeber, Corinna
Publication Date: 2020
Creators: Remschel, Tobias; Kroeber, Corinna

we introduce a unique dataset containing all written communication published by the German Bundestag between 1949 and 2017. Increasing numbers of scholars make use of protocols of parliamentary speeches, parliamentary questions, or the texts of legislative drafts in various fields of comparative politics including representation, responsiveness, professionalization and political careers, or parliamentary agenda studies. Since preparing parliamentary documents is rather resource intense, these studies remain limited to single points in time, types of documents and/or policy areas. The long time horizon and various types of documents covered by our new comprehensive dataset will enable scholars interested in parliaments, parties and representatives to answer various innovative research questions related to legislative studies. (2020-11-14)

The dataset is about 1.1 GB large.

The ParlSpeech V2 data set: Full-text corpora of 6.3 million parliamentary speeches in the key legislative chambers of nine representative democracies

The ParlSpeech V2 data set: Full-text corpora of 6.3 million parliamentary speeches in the key legislative chambers of nine representative democracies

Stefan
Open Dataset
Creators: Rauh, Christian; Schwalbach, Jan
Publication Date: 2020
Creators: Rauh, Christian; Schwalbach, Jan

This dataset is an extensive collection of parliamentary speeches from nine representative democracies, offering valuable insights into legislative discourse across different political systems. ParlSpeech V2 contains complete full-text vectors of more than 6.3 million parliamentary speeches in the key legislative chambers of Austria, the Czech Republic, Germany, Denmark, the Netherlands, New Zealand, Spain, Sweden, and the United Kingdom, covering periods between 21 and 32 years. Meta-data include information on date, speaker, party, and partially agenda item under which a speech was held. The accompanying release note provides a more detailed guide to the data (2020-03-11). The speeches span from 1987 to 2018 and the full dataset has a size of 1,5 GB.

It is organized into separate R Data files for each country, with each file containing:​

  • debate: Title of the debate (if available).​

  • party: Name of the party to which the speaker belongs.​

  • text: Full text of the speech as recorded by the parliament.​

  • SPEAKER: Name of the individual delivering the speech.

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