Enhancing Financial Market Predictions: Causality-Driven Feature Selection FinSen dataset that revolutionizes financial market analysis by integrating economic and financial news articles from 197 countries with stock market data. The dataset’s extensive coverage spans 15 years from 2007 to 2023 with temporal information, offering a rich, global perspective 160,000 records on financial market news. Our study leverages causally validated sentiment scores and LSTM models to enhance market forecast accuracy and reliability.

CNBC Economy Articles Dataset is an invaluable collection of data extracted from CNBC’s economy section, offering deep insights into global and U.S. economic trends, market dynamics, financial policies, and industry developments.

This dataset encompasses a diverse array of economic articles on critical topics like GDP growth, inflation rates, employment statistics, central bank policies, and major global events influencing the market. Designed for researchers, analysts, and businesses, it serves as an essential resource for understanding economic patterns, conducting sentiment analysis, and developing financial forecasting models.

Dataset Highlights

Each record in the dataset is meticulously structured and includes:

• Article Titles
• Publication Dates
• Author Names
• Content Summaries
• URLs to Original Articles

This rich combination of fields ensures seamless integration into data science projects, research papers, and market analyses.

Key Features

• Number of Articles: Hundreds of articles sourced directly from CNBC.
• Data Fields: Includes title, publication date, author, article content, summary, URL, and relevant keywords.
• Topics Covered: U.S. and global economy, GDP trends, inflation, employment, financial markets, and monetary policies.
• Format: Delivered in CSV format for easy integration with research tools and analytical platforms.
• Source: Extracted directly from CNBC’s economy news section, ensuring accuracy and relevance.

Use Cases

• Economic Research: Gain insights into U.S. and global economic policies, market trends, and industry developments.
• Sentiment Analysis: Assess the sentiment of economic articles to gauge market perspectives and investor confidence.
• Financial Modeling: Build forecasting models leveraging key economic indicators discussed in the dataset.
• Content Creation: Develop research-backed reports, articles, and presentations on economic topics.

Who Benefits?

• Researchers & Academics studying macro-economics or financial policy.
  
• Data Scientists building AI models, trend analyzers, or economic forecasting tools.
  
• Economists & Analysts need real-world news data for policy analysis.
  
• Content Strategists who write data-backed articles about economic trends.

Why Choose This Dataset?

• No need to manually scrape CNBC — data is pre-extracted and clean.
  
• High-quality economy news metadata enables detailed filtering (by date, author, topic).
  
• Ready for machine learning, sentiment analysis, or building news-based economic models.
  
• Well-suited for trend tracking, policy analysis, and economic forecasting.

Explore More News Datasets

Interested in additional structured news datasets for your research or analytics needs? Check out our news dataset collection to find datasets tailored for diverse analytical applications.

Stay informed with our comprehensive Financial News Dataset, designed for investors, analysts, and businesses to track market trends, monitor financial events, and make data-driven decisions.

Dataset Features

Financial News Articles: Access structured financial news data, including headlines, summaries, full articles, publication dates, and source details. Market & Economic Indicators: Track financial reports, stock market updates, economic forecasts, and corporate earnings announcements. Sentiment & Trend Analysis: Analyze news sentiment, categorize articles by financial topics, and monitor emerging trends in global markets. Historical & Real-Time Data: Retrieve historical financial news archives or access continuously updated feeds for real-time insights.

Customizable Subsets for Specific Needs Our Financial News Dataset is fully customizable, allowing you to filter data based on publication date, region, financial topics, sentiment, or specific news sources. Whether you need broad coverage for market research or focused data for investment analysis, we tailor the dataset to your needs.

Popular Use Cases

Investment Strategy & Risk Management: Monitor financial news to assess market risks, identify investment opportunities, and optimize trading strategies. Market & Competitive Intelligence: Track industry trends, competitor financial performance, and economic developments. AI & Machine Learning Training: Use structured financial news data to train AI models for sentiment analysis, stock prediction, and automated trading. Regulatory & Compliance Monitoring: Stay updated on financial regulations, policy changes, and corporate governance news. Economic Research & Forecasting: Analyze financial news trends to predict economic shifts and market movements.

Whether you're tracking stock market trends, analyzing financial sentiment, or training AI models, our Financial News Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

Explore the "Bloomberg Quint News Dataset," a comprehensive collection of news articles from Bloomberg Quint, a leading source of financial, business, and economic news in India and around the world.

This dataset includes thousands of articles covering a wide range of topics, such as financial markets, economic policies, corporate news, technology, politics, and more. Each article in the dataset comes with detailed information, including headlines, publication dates, authors, article content, and categories, offering valuable insights for researchers, data analysts, and media professionals.

Key Features:

• Extensive Coverage: Thousands of news articles from Bloomberg Quint, covering diverse topics including business, finance, economics, technology, and global news.
• Detailed Metadata: Each article includes key details such as headline, publication date, author, content, and category, making it ideal for in-depth research and analysis.
• Ideal for Analysis: Perfect for researchers, data scientists, and content strategists looking to analyze trends in news reporting, study media coverage, or develop content strategies.
• Rich Source of Information: Provides up-to-date information on financial markets, economic policies, and global events, helping professionals stay informed and make data-driven decisions.

Whether you're researching financial trends, analyzing media coverage, or developing new content, the "Bloomberg Quint News Dataset" is an invaluable resource that offers detailed insights and extensive coverage of the latest news.

Explore the largest pre-crawled news articles dataset from CNBC, a leading global news source for business, finance and current affairs. This comprehensive news dataset includes thousands of articles covering a wide range of topics: financial markets, economic trends, technology, politics, health, and more. Each entry in this dataset provides detailed information, including headlines, publish dates, authors, article content and categories — offering valuable insights for researchers, data analysts and media professionals.

Key Features

• Extensive Coverage: Thousands of news articles from CNBC, spanning business, finance, technology and global news.
  
  
• Detailed Metadata: Each news record includes headline, publication date, author, content and category — enabling in-depth research.
  
  
• Ready for Analysis: Ideal for data scientists, content strategists and media researchers building trend-analysis, media-monitoring or news-analytics models.
  
  
• Immediate Use: Data is delivered in CSV format, instantly downloadable, ready for machine-learning, AI modelling or reporting pipelines.
  

Who benefits?

• Academic researchers analysing media coverage or news sentiment.
  
  
• Data scientists building news analytics dashboards or training NLP models.
  
  
• Content teams / SEO specialists sourcing datasets to support articles about media trends or data-driven stories.
  
  
• Global marketers investigating business & financial news trends across the US/UK/EU markets.
  

Why choose this dataset?

• Ready to use: no manual scraping required.
  
  
• High-quality metadata allowing filtered exports by topic, date or author.
  
  
• Broad topic coverage: business, finance, technology, politics, health, and global news.
  

Ideal for building derivatives: summarisation, classification, clustering.

US Economic news articles with tone and relevance

The dataset consists of approximately 8000 news articles, which were tagged as relevant or not relevant to the US Economy.

Explore the intricate dance between gold prices and key economic events across major global players – Canada, Japan, USA, Russia, European Union, and China. This comprehensive dataset spans from January 2019 to December 2023, offering a nuanced analysis of how economic news from these influential regions impacts the ever-volatile gold market. Delve into the ebb and flow of financial landscapes, uncovering trends, correlations, and invaluable insights for strategic decision-making in the dynamic world of investments.

Historical Gold Price Dataset:

• Day: The day of the week when the data was recorded.
• Date: The specific date corresponding to the recorded gold price.
• Hour: The time of day when the gold price was recorded.
• Country: The country associated with the economic event or news affecting gold prices.
• Event: The economic event or news that potentially influenced gold prices.
• Actual: The actual reported value or figure related to the economic event.
• Previous: The previously reported value or figure for the same economic event.
• Consensus: The consensus forecast or expected value for the economic event.
• Forecast: The forecasted value or figure for the economic event.

** Economic Calendar Dataset**:

• Day: The day of the week when the economic event is scheduled.
• Date: The specific date when the economic event is expected to occur.
• Hour: The time of day when the economic event is scheduled.
• Country: The country associated with the economic event.
• Event: The specific economic event or news scheduled to take place.
• Actual The actual reported value or figure related to the economic event.
• Previous: The previously reported value or figure for the same economic event.
• Consensus: The consensus forecast or expected value for the economic event.
• Forecast: The forecasted value or figure for the economic event.

Techsalerator’s News Event Data in Asia offers a detailed and expansive dataset designed to provide businesses, analysts, journalists, and researchers with comprehensive insights into significant news events across the Asian continent. This dataset captures and categorizes major events reported from a diverse range of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable perspectives on regional developments, economic shifts, political changes, and cultural occurrences.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide range of sources such as company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse array of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most current events, ensuring users have access to the latest news and can stay informed about recent developments as they happen. Geographic Segmentation:

Events are tagged with their respective countries and regions within Asia. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into the evolution of news events. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Asian Countries and Territories Covered: Central Asia: Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan East Asia: China Hong Kong (Special Administrative Region of China) Japan Mongolia North Korea South Korea Taiwan South Asia: Afghanistan Bangladesh Bhutan India Maldives Nepal Pakistan Sri Lanka Southeast Asia: Brunei Cambodia East Timor (Timor-Leste) Indonesia Laos Malaysia Myanmar (Burma) Philippines Singapore Thailand Vietnam Western Asia (Middle East): Armenia Azerbaijan Bahrain Cyprus Georgia Iraq Israel Jordan Kuwait Lebanon Oman Palestine Qatar Saudi Arabia Syria Turkey (partly in Europe, but often included in Asia contextually) United Arab Emirates Yemen Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Asia, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Asian news and events. Techsalerator’s News Event Data in Asia is a crucial resource for accessing and analyzing significant news events across the continent. By offering detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

We have successfully extracted a comprehensive news dataset from CNBC, covering not only financial updates but also an extensive range of news categories relevant to diverse audiences in Europe, the US, and the UK. This dataset includes over 500,000 records, meticulously structured in JSON format for seamless integration and analysis.

Diverse News Segments for In-Depth Analysis

This extensive extraction spans multiple segments, such as:

• Business and Market Analysis: Stay updated on major companies, mergers, and acquisitions.
• Technology and Innovation: Explore developments in AI, cybersecurity, and digital transformation.
• Economic Forecasts: Access insights into GDP, employment rates, inflation, and other economic indicators.
• Geopolitical Developments: Understand the impact of political events and global trade dynamics on markets.
• Personal Finance: Learn about saving strategies, investment tips, and real estate trends.

Each record in the dataset is enriched with metadata tags, enabling precise filtering by region, sector, topic, and publication date.

Why Choose This Dataset?

The comprehensive news dataset provides real-time insights into global developments, corporate strategies, leadership changes, and sector-specific trends. Designed for media analysts, research firms, and businesses, it empowers users to perform:

• Trend Analysis
• Sentiment Analysis
• Predictive Modeling

Additionally, the JSON format ensures easy integration with analytics platforms for advanced processing.

Access More News Datasets

Looking for a rich repository of structured news data? Visit our news dataset collection to explore additional offerings tailored to your analysis needs.

Sample Dataset Available

To get a preview, check out the CSV sample of the CNBC economy articles dataset.

Financial news significantly influences investment decisions, stock market trends, and corporate strategies. However, extracting meaningful insights from unstructured news articles, particularly event-cause relationships, remains a challenge. This dataset addresses this gap by providing manually annotated event-cause pairs from financial news, enabling improved predictive modeling, risk assessment, and automated trading strategies.

Dataset Composition:

The dataset comprises 456 financial news articles from the following four major Indian financial news sources.

Business Standard

Economic Times

Live Mint

Moneycontrol

It covers articles from 2021 to 2025. Each entry includes annotated event-cause relationships along with metadata such as stock symbols, stock change, company names, and financial indicators. The dataset categorizes events into five key types:

Financial Reports & Earnings Announcements

Mergers & Acquisitions

Regulatory Changes & Legal Actions

Executive Leadership Changes

Market & Economic Trends

Dataset Attributes

The dataset comprises the following attributes:

Source: The origin of the news article (e.g., financial news websites).

Title: The headline of the article.

Content: The full text of the article.

Date: The publication date of the article.

Stock: Name of the Stock.

Labels: The annotation Tags (e.g., ORG, EVENT, CAUSE)

Stock Gain/Loss Percent: The percentage change in stock price associated with the event described in the article. The gain/loss percent was manually extracted from the Tickertape website.

The dataset is structured in JSON format and CSV, ensuring efficient storage and accessibility.

Applications:

This dataset supports event-cause extraction in financial NLP applications such as:

Stock market prediction using causal analysis

Algorithmic trading models incorporating financial event impact

Sentiment analysis & risk assessment for investment strategies

Corporate strategy evaluation based on financial event insights

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

RBA Governor Lowe’s Testimony High inflation is damaging and corrosive

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

Techsalerator’s News Event Data in Latin America offers a detailed and extensive dataset designed to provide businesses, analysts, journalists, and researchers with an in-depth view of significant news events across the Latin American region. This dataset captures and categorizes key events reported from a wide array of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable insights into regional developments, economic changes, political shifts, and cultural events.

Key Features of the Dataset: Comprehensive Coverage:

The dataset aggregates news events from numerous sources such as company press releases, industry news outlets, blogs, PR sites, and traditional news media. This broad coverage ensures a wide range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly locate and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most recent events, ensuring users have access to the latest news and can stay informed about current developments. Geographic Segmentation:

Events are tagged with their respective countries and regions within Latin America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps in understanding the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Latin America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Latin American news and events. Techsalerator’s News Event Data in Latin America is a crucial resource for accessing and analyzing significant news events across the region. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

Techsalerator’s News Event Data in North America offers a comprehensive and detailed dataset designed to provide businesses, analysts, journalists, and researchers with a thorough view of significant news events across North America. This dataset captures and categorizes major events reported from a diverse range of news sources, including press releases, industry news sites, blogs, and PR platforms, providing valuable insights into regional developments, economic shifts, political changes, and cultural events.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide array of sources, including company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types such as business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most current events, ensuring that users have access to up-to-date news and can stay informed about recent developments as they happen. Geographic Segmentation:

Events are tagged with their respective countries and territories within North America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and conduct comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. North American Countries and Territories Covered: Countries: Canada Mexico United States Territories: American Samoa (U.S. territory) French Polynesia (French overseas collectivity; included for regional relevance) Guam (U.S. territory) New Caledonia (French special collectivity; included for regional relevance) Northern Mariana Islands (U.S. territory) Puerto Rico (U.S. territory) Saint Pierre and Miquelon (French overseas territory; geographically close to North America and included for regional comprehensiveness) Wallis and Futuna (French overseas collectivity; included for regional relevance) Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across North America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to North American news and events. Techsalerator’s News Event Data in North America is a crucial resource for accessing and analyzing significant news events across the continent. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

This dataset is the result of research in applying Large Language Models (LLMs) to financial news processing. It contains over 5,000 news articles from various financial publishers, with the following information available for each article: - Title - Summary - Relevant stock tickers - The sentiment of each stock ticker in the article along with the reasoning for the categorization - Metadata including publish date, author, and image URL

The data is a result of an LLM-powered pipeline proposed by the data provider Polygon.io in a recent white paper. A live and continuously updated version of this dataset can be obtained via API here.

Cite as: @article{dolphin2024extracting, title={Extracting Structured Insights from Financial News: An Augmented LLM Driven Approach}, author={Dolphin, Rian and Dursun, Joe and Chow, Jonathan and Blankenship, Jarrett and Adams, Katie and Pike, Quinton}, journal={arXiv preprint arXiv:2407.15788}, year={2024} }

This dataset is compiled through scraping articles from Guardian news starting from 2021 up to the present. It's meticulously crafted to facilitate multimodal classification tasks, especially in the realm of Natural Language Processing (NLP).

The dataset comprises 13 labels representing various topics covered in the news, ranging from sports to economics, politics, art, and entertainment. Each label corresponds to a distinct category, offering a comprehensive overview of the diverse subjects discussed in journalistic discourse. Researchers and practitioners can utilize these labels for multi-label classification tasks, aiming to categorize news articles based on their thematic content.

The topics encapsulated by these labels reflect the multifaceted nature of contemporary news media, capturing the breadth and depth of global events and developments. Whether it's the latest in sports, updates on economic trends, insights into political affairs, or coverage of the arts and entertainment industry, this dataset encompasses a wide spectrum of subjects.

The file forma is parquet. If you are new to this, for open it just do pd.read_parquet(filepath) and it's done!

Economic calendar extracted from Investing.com (CSV) from 01-01-2015 to 31-12-2024 all countries

Columns

• Id of event
• Date (d-m-y)
• Hour of event
• Zone
• Currency
• Importance
• Event
• Actual
• Forecast (prediction of the market)
• Previous

yjernite/news-economy-coverage dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset is about news. It has 1 row and is filtered where the keywords includes Economic assistance-Ghana. It features one column called news link.

Techsalerator's News Events Data for Singapore: A Comprehensive Overview

Techsalerator's News Events Data for Singapore offers a powerful resource for businesses, researchers, and media organizations. This dataset compiles information on significant news events across Singapore, pulling from a wide range of media sources, including news outlets, online publications, and social platforms. It provides valuable insights for those looking to track trends, analyze public sentiment, or monitor industry-specific developments.

Key Data Fields - Event Date: Captures the exact date of the news event. This is crucial for analysts who need to monitor trends over time or for businesses responding to market shifts. - Event Title: A brief headline describing the event. This allows users to quickly categorize and assess news content based on relevance to their interests. - Source: Identifies the news outlet or platform where the event was reported. This helps users track credible sources and assess the reach and influence of the event. - Location: Provides geographic information, indicating where the event took place within Singapore. This is especially valuable for regional analysis or localized marketing efforts. - Event Description: A detailed summary of the event, outlining key developments, participants, and potential impact. Researchers and businesses use this to understand the context and implications of the event.

Top 5 News Categories in Singapore - Politics: Major news coverage on government decisions, political movements, elections, and policy changes that affect the national landscape. - Economy: Focuses on Singapore’s economic indicators, inflation rates, international trade, and corporate activities influencing business and finance sectors. - Social Issues: News events covering public health, education, and other societal concerns that drive public discourse. - Sports: Highlights events in popular sports such as soccer, swimming, and table tennis, often drawing widespread attention and engagement. - Technology and Innovation: Reports on tech developments, startups, and innovations in Singapore’s thriving tech ecosystem, featuring emerging companies and advancements.

Top 5 News Sources in Singapore - The Straits Times: A leading news outlet providing comprehensive coverage of national politics, economy, and social issues. - Channel News Asia: A major news platform known for its timely updates on breaking news, politics, and current affairs. - The Business Times: A widely-read newspaper offering insights into economic developments, business news, and corporate activities. - TODAY: A significant news source covering a broad spectrum of topics, including politics, economy, and social issues. - Channel 8 News: The national news channel delivering updates on significant events, public health, and sports across Singapore.

Accessing Techsalerator’s News Events Data for Singapore To access Techsalerator’s News Events Data for Singapore, please contact info@techsalerator.com with your specific needs. We will provide a customized quote based on the data fields and records you require, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields - Event Date - Event Title - Source - Location - Event Description - Event Category (Politics, Economy, Sports, etc.) - Participants (if applicable) - Event Impact (Social, Economic, etc.)

Techsalerator’s dataset is an invaluable tool for keeping track of significant events in Singapore. It aids in making informed decisions, whether for business strategy, market analysis, or academic research, providing a clear picture of the country’s news landscape.

About this Dataset

Techcrunch news dataset in csv format.

Category

Economic

Keywords

news dataset,news data

Row Count

5246

Price

$67.00