262 Resources

Open Dataset

Showing 185-192 of 262 results
Speeches Dataset

Speeches Dataset

Stefan
Open Dataset
Creators: European Central Bank
Publication Date: 2019
Creators: European Central Bank

To assist researchers in the field of central bank communication, we offer a precompiled dataset containing the content of all speeches together with limited metadata. This dataset contains the full text of speeches delivered by its Executive Board members, accompanied by limited metadata. Each entry includes the complete text of the speech, offering detailed insights into the ECB’s communication. The dataset also includes metadata such as the date of the speech in YYYY-MM-DD format, the names of the ECB Executive Board members who delivered the speech, the title of the speech, and a subtitle providing additional context about the occasion or event. One special characteristic of this dataset is that it is regularly updated, typically on a monthly basis, ensuring that researchers have access to the latest speeches. It has a a size of 1,4 MB and encompasses speeches from the inception of the ECB up to the most recent update, which took place on March 1, 2025. The dataset is structured as a CSV file with the following columns: date (publication date of the speech), speakers (names of the Executive Board members who delivered the speech), title (title of the speech), subtitle (additional context or description), and contents (full text of the speech, including any footnotes).

The CEPS EurLex dataset: 142.036 EU laws from 1952-2019 with full text and 22 variables

The CEPS EurLex dataset: 142.036 EU laws from 1952-2019 with full text and 22 variables

Stefan
Open Dataset
Creators: Borret, Camille; Laurer Moritz
Publication Date: 2020
Creators: Borret, Camille; Laurer Moritz

The dataset contains 142.036 EU laws – almost the entire corpus of the EU’s digitally available legal acts passed between 1952 – 2019. It encompasses the full texts of these legal documents, providing researchers and analysts with extensive material for legal, historical, and policy-related studies. The dataset covers the three types of legally binding acts passed by the EU institutions: 102.304 regulations, 4.070 directives, 35.798 decisions in English language. The dataset was scraped from the official EU legal database (Eur-lex.eu) and transformed in machine-readable CSV format with the programming languages R and Python. It was collected by the Centre for European Policy Studies (CEPS) for the TRIGGER project (https://trigger-project.eu/). We hope that it will facilitate future quantitative and computational research on the EU. Covering EU legal acts from the year 1952 up to August 2019, this dataset provides a historical perspective on the evolution of EU legislation over nearly seven decades. It has a size of 1,5 GB.

COVID-19 Economic Stimulus Packages Database

COVID-19 Economic Stimulus Packages Database

Stefan
Open Dataset
Creators: Elgin, C; Yalaman, A
Publication Date: 2021
Creators: Elgin, C; Yalaman, A

We conduct a comprehensive review of different economic policy measures adopted by 166 countries as a response to the COVID-19 pandemic and create a large database including fiscal, monetary, and exchange rate measures. Furthermore, using principle component analysis (PCA), we construct a COVID-19 Economic Stimulus Index (CESI) that combines all adopted policy measures. This index standardises economic responses taken by governments and allows us to study cross-country differences in policies. Finally, using simple cross-country OLS regressions we report that the median age of the population, the number of hospital beds per-capita, GDP per-capita, and the number of total cases are all significantly associated with the extent of countries’ economic policy responses. The dataset covers economic policy measures adopted during the COVID-19 pandemic, with the latest version dated May 7, 2021, reflecting the policies implemented up to that point. It has a size of 6,2 kB.

Third Eye Data: TV News Archive chyrons

Third Eye Data: TV News Archive chyrons

Stefan
Open Dataset
Creators: TV News Archive
Publication Date: 2017
Creators: TV News Archive

The Third Eye: TV News Archive Chyrons dataset captures and analyzes the “lower third” text, known as chyrons, displayed during live TV news broadcasts. This dataset provides a unique look into the real-time editorial choices of major news networks, offering insights into how different media outlets frame news stories. Using Optical Character Recognition (OCR) technology, chyrons are extracted and archived continuously, making it possible to track how key topics are covered over time.

At its inception in September 2017, the dataset collected chyrons from four major news networks: BBC News, CNN, Fox News, and MSNBC. Within just two weeks of its launch, over four million chyrons had already been captured, highlighting the vast amount of real-time data available. The dataset has been continuously updated since, allowing for longitudinal studies of media framing and news presentation trends. It’s size is approximately 12.5 kB in TSV format.

The dataset is structured into several key components. Each chyron entry includes:

  • The exact chyron text, showing the wording used by the network.
  • Timestamps, allowing analysis of how frequently specific topics appear.
  • Channel identifiers, enabling comparisons between different networks.
  • Duration data, indicating how long a chyron remained on screen, which can suggest emphasis or prioritization of certain stories.

By leveraging this dataset, researchers, journalists, and media analysts can examine bias in news presentation, media influence on public perception, and breaking news coverage trends. It serves as a powerful tool for studying news framing, editorial strategies, and the evolution of televised news narratives across competing networks.

CO2 emissions and ancillary data for 343 cities from diverse sources

CO2 emissions and ancillary data for 343 cities from diverse sources

Stefan
Open Dataset
Creators: Nangini, Cathy; Peregon Anna; Ciais, Philippe; Weddige, Ulf; Vogel, Felix; Wang, Jun; Bréon, François-Marie; Bachra, Simeran; Wang, Yilong; Gurney, Kevin; Yamagata, Yoshiki; Appleby, Kyra; Telahoun, Sara; Canadell, Josep G; Grübler, Arnulf; Dhakal, Shobhakar; Creutzig, Felix
Publication Date: 2019
Creators: Nangini, Cathy; Peregon Anna; Ciais, Philippe; Weddige, Ulf; Vogel, Felix; Wang, Jun; Bréon, François-Marie; Bachra, Simeran; Wang, Yilong; Gurney, Kevin; Yamagata, Yoshiki; Appleby, Kyra; Telahoun, Sara; Canadell, Josep G; Grübler, Arnulf; Dhakal, Shobhakar; Creutzig, Felix

This dataset collects anthropogenic carbon dioxide emissions data, supplemented with various socio-economic and environmental factors, across 343 cities worldwide. A dataset of dimensions 343 × 179 consisting of CO2 emissions from CDP (187 cities, few in developing countries), the Bonn Center for Local Climate contains action and reporting data (73 cities, mainly in developing countries), and data collected by Peking University (83 cities in China). Further, a set of socio-economic variables – called ancillary data – were collected from other datasets (e.g. socio-economic and traffic indices) or calculated (climate indices, urban area expansion), then combined with the emission data. The remaining attributes are descriptive (e.g. city name, country, etc.) or related to quality assurance/control checks. The file size is 1,8 MB and the majority (88%) of the cities reported emissions between 2010 and 2015. Structurally the dataset contains

  • City Identification: Each entry includes city name, country, and other descriptive attributes.​
  • CO₂ Emissions Data: Reported emissions with quality assurance/control checks.​
  • Ancillary Variables: Socio-economic data, traffic indices, climate indices, urban area expansion metrics, and more.​

Please open using Tab as separator and ” as text delimiter.

MUStARD: Multimodal Sarcasm Detection Dataset

MUStARD: Multimodal Sarcasm Detection Dataset

Stefan
Open Dataset
Creators: Castro, Santiago; Hazarika, Devamanyu; Pérez-Rosas, Verónica; Zimmermann, Roger; Mihalcea, Rada; Poria, Soujanya
Publication Date: 2019
Creators: Castro, Santiago; Hazarika, Devamanyu; Pérez-Rosas, Verónica; Zimmermann, Roger; Mihalcea, Rada; Poria, Soujanya

We release the MUStARD dataset which is a multimodal video corpus for research in automated sarcasm discovery. The dataset is compiled from popular TV shows including Friends, The Golden Girls, The Big Bang Theory, and Sarcasmaholics Anonymous. MUStARD consists of audiovisual utterances annotated with sarcasm labels. Each entry in the dataset combines textual transcripts, audio signals, and visual cues, enabling comprehensive analysis of sarcasm as it manifests across different channels. Beyond isolated utterances, the dataset includes preceding conversational context, providing insights into how prior dialogue influences the interpretation of sarcasm. The dataset was compiled and released in 2019 and is approximately 11,9 kB in size.

Key numbers:

  • Total Utterances: 690​

  • Sarcastic Utterances: 345​

  • Non-Sarcastic Utterances: 345

The dataset is organized in JSON format with the following fields:​

  • utterance: The text of the target utterance to classify.​

  • speaker: Speaker of the target utterance.​

  • context: List of utterances (in chronological order) preceding the target utterance.​

  • context_speakers: Respective speakers of the context utterances.​

  • sarcasm: Binary label indicating sarcasm (1 for sarcastic, 0 for non-sarcastic).​

State of the State

State of the State

Stefan
Open Dataset
Creators: Fivethirtyeight
Publication Date: 2019
Creators: Fivethirtyeight

We conducted a text analysis of all 50 governors’ 2019 state of the state speeches to see what issues were talked about the most and whether there were differences between what Democratic and Republican governors were focusing on.

index.csv contains a listing of each of the 50 speeches, one for each state as well as the name and party of the state’s governor and a link to an official source for the speech.

words.csv contains every one-word phrase that was mentioned in at least 10 speeches and every two- or three-word phrase that was mentioned in at least five speeches after a list of stop-words was removed and the word “healthcare” was replaced with “health care” so that they were not counted as distinct phrases. It also contains the results of a chi^2 test that shows the statistical significance of and associated p-value of phrases. Overall, the dataset is 134,5 kB in size

Steam Video Game and Bundle Data

Steam Video Game and Bundle Data

Stefan
Open Dataset
Creators: Kang, Wang-Cheng; McAuley, Julian; Pathak, Apurva; Gupta, Kshitiz
Publication Date: 2018
Creators: Kang, Wang-Cheng; McAuley, Julian; Pathak, Apurva; Gupta, Kshitiz
This datasets collect user interactions and metadata from the Steam platform, aimed at facilitating research in recommendation systems and user behavior analysis. They encompass a vast number of user reviews, capturing detailed feedback and engagement levels. Also, it provides insights into game bundles, detailing which games are frequently purchased together, aiding in the analysis of bundling strategies and their effectiveness. The The dataset encompasses user reviews and interactions from October 2010 to January 2018 and is approximately 1.4 GB in size and includes:
  • Reviews: 7,793,069
  • Users: 2,567,538
  • Items: 15,474
  • Bundles: 615

Structurally, the dataset comprises several key components:​

  • User Reviews: Each review entry includes the user ID, game ID, review text, and associated metadata such as timestamps and ratings.​

  • Game Metadata: Information about each game, including game ID, title, genre, developer, and pricing details.​

  • Bundle Details: Descriptions of game bundles, specifying the bundle ID, included games, and pricing information.

 

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