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.

The DXY exchange rate rose to 97.9584 on July 14, 2025, up 0.11% from the previous session. Over the past month, the United States Dollar has weakened 0.32%, and is down by 6.03% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July of 2025.

These files contain economic news and market data for Forex market and EUR/USD currency pair.

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Money Supply M0 in the United States decreased to 5648600 USD Million in May from 5732900 USD Million in April of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2021, newspaper advertising spending in North America amounted to 8.3 billion U.S. dollars. The medium will face a continued decline in ad investments over the next few years, and according to the latest data, spending will have fallen to six billion U.S. dollars by 2024.

Newspaper readership The newspaper industry in North America has faced many challenges over the past few decades. The advent of social media and other online platforms has arguably caused the most significant disruption to the industry, as audiences continue to replace print publications with digital sources. In the United States, print newspaper consumption has dropped to an average of nine minutes per day, and according to a recent survey, newspapers were voted one of the least popular platforms for daily news consumption among young generations in early 2021.

Has newspaper advertising lost its appeal? Newspaper advertising is one of the oldest forms of advertising. While print editions have long been an effective tool for reaching potential customers, the digital revolution is visibly shifting advertisers’ attention and investments away from this and other traditional ad formats. In the United States, circulation numbers for daily weekday newspapers have been falling for decades, making them less attractive platforms for ad placement. And even though most publications have already jumped on the digital train, online newspapers now generally rely on paid subscription models for revenue instead of advertising investments.

News translation, which is often known as news transediting, which is concerned with the translation of materials for print and/or online mass media, has long stimulated interest within the field of translation studies. The present paper explores the strategies of transediting the terms used for describing the US dollar in the websites of four news channels, namely: Alarabiya, Aljazeera, BBC and CNN between Arabic and English from the first of July 2022 to the thirty-first of December 2022. The paper conducts triangulational analysis to identify the type and frequency of the transediting strategies used in each channel, present how certain examples of each strategy are adopted and demonstrate the similarities and differences in the type and frequency of the transediting strategies employed between the channels. The paper argues that the choice of the transediting strategy is based on the type of audience, context, the channel’s policy and the type of information intended for delivery. This paper offers a baseline for exploring the strategies of transediting the terms used for describing the US dollar in both Arabic and English news websites of the aforementioned channels, which may have implications for exploring other transediting strategies used in other news websites of different channels broadcast in different languages.

United States AHE: sa: PW: Information: Newspaper, Book & Directory Publishers data was reported at 31.920 USD in Nov 2022. This records an increase from the previous number of 31.580 USD for Oct 2022. United States AHE: sa: PW: Information: Newspaper, Book & Directory Publishers data is updated monthly, averaging 22.620 USD from Jan 2003 (Median) to Nov 2022, with 239 observations. The data reached an all-time high of 31.920 USD in Nov 2022 and a record low of 15.860 USD in Jan 2003. United States AHE: sa: PW: Information: Newspaper, Book & Directory Publishers data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G076: Current Employment Statistics: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

I am hereby sharing the dataset used in the paper titled 'Beyond Tradition: A Hybrid Model Unveiling News Impact on Exchange Rates'. The dataset comprises the following components: Taylor Rule Fundamentals: - Inflation - Industrial production index (as a high-frequency proxy of GDP) - Money market rate spanning from 2000 to 2018. Textual Information: - Economic Policy Uncertainty Index from https://www.policyuncertainty.com/index.html (as of November 9, 2023). - Time series of entropies calculated for U.S. Dollar-related news topics extracted from the Nexis-Uni database. Note: To acquire the textual data from the Nexis-Uni database, we conducted the following steps: We entered "U.S. Dollar" as a keyword in the search for news, resulting in over 15 million non-duplicate news items. Subsequently, we cleaned the news data and selected relevant news items using the following criteria: (i) The U.S. Dollar appears in the title of news items, (ii) The term "U.S. Dollar" is repeated several times in the news, (iii) The first paragraph of the news contains the word "U.S. Dollar", (iv) The news items are automatically selected by the Nexis-Uni database with the U.S. Dollar as the subject. Subsequently, we identified the topics related to the US Dollar from the news using LDA and calculated the Shannon entropies over time for each topic.

India Imports: USD: HS: 49029010: Newspaper data was reported at 0.010 USD mn in 2018. This records a decrease from the previous number of 0.040 USD mn for 2017. India Imports: USD: HS: 49029010: Newspaper data is updated yearly, averaging 0.050 USD mn from Mar 2004 (Median) to 2018, with 15 observations. The data reached an all-time high of 0.770 USD mn in 2004 and a record low of 0.010 USD mn in 2018. India Imports: USD: HS: 49029010: Newspaper data remains active status in CEIC and is reported by Ministry of Commerce and Industry. The data is categorized under India Premium Database’s Foreign Trade – Table IN.JBZ005: Foreign Trade: Harmonized System 8 Digits: By Commodity: HS49: Printed Books, Newspapers, Pictures etc: Imports: USD.

United States AHE: sa: PW: RT: Book Stores & News Dealers data was reported at 17.130 USD in Nov 2022. This records an increase from the previous number of 16.910 USD for Oct 2022. United States AHE: sa: PW: RT: Book Stores & News Dealers data is updated monthly, averaging 10.060 USD from Jan 1990 (Median) to Nov 2022, with 395 observations. The data reached an all-time high of 17.320 USD in Apr 2020 and a record low of 5.940 USD in Mar 1990. United States AHE: sa: PW: RT: Book Stores & News Dealers data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G076: Current Employment Statistics: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

Hyperlocal News App Market Outlook

According to our latest research, the global Hyperlocal News App market size reached USD 2.1 billion in 2024, reflecting a robust expansion driven by rising smartphone penetration and the increasing demand for real-time community information. The market is expected to grow at a CAGR of 14.2% from 2025 to 2033, projecting a value of USD 6.3 billion by 2033. This impressive growth is primarily fueled by the shift towards digital news consumption, the proliferation of location-based services, and the growing appetite for personalized, community-centric content.

One of the primary growth factors driving the Hyperlocal News App market is the escalating reliance on mobile devices for accessing news and information. With smartphones becoming ubiquitous across both developed and emerging economies, users are increasingly seeking tailored content that is relevant to their immediate surroundings. Hyperlocal news apps leverage geolocation technologies to deliver real-time updates on community news, events, and emergencies, thereby enhancing user engagement and satisfaction. This trend is further supported by the growing availability of high-speed internet and the integration of advanced features such as push notifications, multimedia content, and interactive platforms, which collectively enhance the user experience and broaden the appeal of hyperlocal news solutions.

Another significant driver is the rising demand from local businesses and advertisers aiming to connect with nearby consumers in a targeted and cost-effective manner. Hyperlocal news apps provide a platform for local advertising, allowing businesses to reach potential customers within their vicinity through location-based promotions and sponsored content. This targeted approach not only increases the relevance and effectiveness of advertisements but also creates new revenue streams for app developers and publishers. Additionally, the integration of analytics and user data enables advertisers to refine their campaigns, measure performance, and optimize their marketing strategies, thereby maximizing the return on investment in hyperlocal advertising.

The growing importance of community engagement and local governance is also propelling the adoption of hyperlocal news apps. Government agencies and civic organizations are increasingly utilizing these platforms to disseminate crucial information, such as emergency alerts, public service announcements, and event updates, directly to residents. This direct communication channel enhances public safety, fosters civic participation, and strengthens the sense of community among users. Furthermore, the rise of citizen journalism and user-generated content is empowering individuals to contribute news stories and updates, thereby enriching the content ecosystem and ensuring comprehensive coverage of local events and issues.

From a regional perspective, North America and Europe currently lead the hyperlocal news app market, accounting for the largest shares due to high digital literacy, advanced telecommunications infrastructure, and a mature advertising ecosystem. However, the Asia Pacific region is witnessing the fastest growth, driven by rapid urbanization, increasing smartphone adoption, and the rising demand for localized content in densely populated cities. Emerging markets in Latin America and the Middle East & Africa are also experiencing notable growth, supported by improvements in internet connectivity and the growing popularity of mobile-first news consumption. As these regions continue to invest in digital infrastructure and local content creation, the global hyperlocal news app market is poised for sustained expansion in the coming years.

Platform Analysis

The platform segment of the Hyperlocal News App market is categorized into Android, iOS, and Web-based platforms, each playing a pivotal role in shaping user engagement and market penetration. Android continues to dominate the global landscape, owing to its widespread adoption in emerging markets such as India, Southeast Asia, and Africa. The open-source nature of Android, coupled with the affordability of Android devices, has made it the preferred choice for a broad spectrum of users. Hyperlocal news apps on Android benefit from a massive user base, seamless integration with Google services, and the ability to leverage device-specific features such as geolocation and notifications, which are critical for delivering timely and relevan

Uncover Market Research Intellect's latest News Apps Market Report, valued at USD 4.5 billion in 2024, expected to rise to USD 8.2 billion by 2033 at a CAGR of 8.1% from 2026 to 2033.

Prices for DXY Dollar Index including live quotes, historical charts and news. DXY Dollar Index was last updated by Trading Economics this July 13 of 2025.

News and Magazines App Market size was valued at USD 1.20 billion in 2021 and is poised to grow from USD 2.15 billion in 2022 to USD 4.55 billion by 2030, growing at a CAGR of 11.2%

AI News Anchor Market Outlook

According to our latest research, the global AI News Anchor market size reached USD 1.39 billion in 2024, driven by rapid advancements in artificial intelligence and machine learning technologies. The market is expected to expand at a robust CAGR of 28.6% from 2025 to 2033, culminating in an estimated market value of USD 13.47 billion by 2033. This remarkable growth is primarily fueled by the increasing adoption of digital automation in media, the need for cost-effective news production, and the rising demand for personalized news delivery across multiple platforms.

One of the most significant growth factors propelling the AI News Anchor market is the escalating demand for 24/7 news coverage and real-time content delivery. Traditional newsrooms are under immense pressure to provide continuous updates, which is not only resource-intensive but also costly. AI-powered news anchors, capable of delivering news in multiple languages and dialects, offer a scalable and efficient solution. These AI anchors can be deployed across various platforms, ensuring consistent, unbiased, and timely news dissemination. The integration of natural language processing and deep learning algorithms further enhances their ability to present news with human-like intonation and expressions, thereby increasing viewer engagement and trust.

Another key driver of market expansion is the growing trend of digital transformation in the media and broadcasting industry. As news consumption shifts from conventional TV to digital and mobile platforms, media organizations are increasingly investing in AI technologies to remain competitive. AI news anchors not only reduce operational costs by minimizing the need for human anchors but also enable the creation of hyper-localized and personalized news content. This technological shift is particularly advantageous for online media platforms and digital broadcasters, enabling them to cater to diverse audiences and expand their reach without significant additional costs. Furthermore, the ability of AI anchors to work around the clock without fatigue or error is revolutionizing news production workflows.

The surge in investments from both public and private sectors is also accelerating the adoption of AI news anchors. Governments and regulatory bodies in regions like Asia Pacific and North America are actively promoting the use of AI in media to enhance information dissemination and combat fake news. Meanwhile, private enterprises are leveraging AI anchors to bolster their corporate communication strategies, ensuring consistent messaging and improved stakeholder engagement. The growing emphasis on digital literacy and the integration of AI in educational institutions for news and media training further contribute to the market's upward trajectory. As AI technologies continue to evolve, the range of applications for AI news anchors is expected to broaden, driving sustained growth in the coming years.

Regionally, Asia Pacific leads the adoption of AI news anchors, accounting for the largest market share in 2024, followed closely by North America and Europe. The region's dominance is attributed to its robust technological infrastructure, high digital penetration, and significant investments in AI research and development. Countries such as China, South Korea, and Japan are at the forefront of deploying AI-powered news anchors, both in traditional broadcasting and digital media. In contrast, North America is witnessing rapid adoption in online media platforms and corporate communications, while Europe is focusing on regulatory compliance and ethical AI deployment. The Middle East & Africa and Latin America are emerging markets, gradually increasing their investments in AI-driven news solutions to enhance their media ecosystems.

Component Analysis

The AI News Anchor market by component is categorized into software, hardware, and services, each playing a pivotal role in the deployment and operation of AI-powered news anchors. Software forms the backbone of AI news anchor solutions, encomp

Discover the latest insights from Market Research Intellect's Mobile News Apps Market Report, valued at USD 3.45 billion in 2024, with significant growth projected to USD 7.12 billion by 2033 at a CAGR of 8.5% (2026-2033).

AI-Driven News Aggregation Market Outlook

According to our latest research, the AI-Driven News Aggregation market size reached USD 2.14 billion globally in 2024, with a robust compound annual growth rate (CAGR) of 17.2% observed over the past year. The market is anticipated to expand significantly, reaching approximately USD 10.08 billion by 2033, as per the projected CAGR. This growth is primarily fueled by the increasing demand for real-time, personalized news experiences and the proliferation of digital content consumption across multiple platforms. As per our latest research, the market's trajectory is strongly influenced by technological advancements in artificial intelligence, particularly natural language processing and machine learning, which have fundamentally transformed the way news is curated, aggregated, and delivered to end-users worldwide.

The rapid digitalization of the media landscape and the exponential growth in online news content have been pivotal growth drivers for the AI-Driven News Aggregation market. As consumers increasingly turn to digital platforms for news consumption, the volume and variety of available content have soared. This, in turn, has created a pressing need for sophisticated aggregation tools that can intelligently filter, personalize, and deliver relevant news to users in real time. The integration of AI technologies enables news aggregators to analyze vast amounts of unstructured data, extract meaningful insights, and curate content tailored to individual preferences. This level of personalization not only enhances user engagement but also drives higher retention rates for news platforms, positioning AI-driven solutions as essential tools in the evolving digital news ecosystem.

Another significant growth factor is the rising adoption of AI-powered news aggregation by enterprises and government organizations. Businesses are leveraging these platforms for competitive intelligence, brand monitoring, and sentiment analysis, while governments utilize them to track public opinion and monitor emerging trends. The ability of AI-driven systems to provide real-time alerts and actionable insights makes them invaluable across diverse sectors. Furthermore, the scalability and adaptability of cloud-based deployment models have made it easier for organizations of all sizes to implement sophisticated aggregation solutions without significant infrastructure investments. As a result, the enterprise and government segments are expected to witness accelerated adoption, further propelling market growth.

The continuous evolution of AI algorithms, particularly in natural language understanding and sentiment analysis, has also played a crucial role in shaping the market. Advanced algorithms can now understand context, detect nuances in language, and even identify fake news or misinformation, thereby improving the reliability and credibility of aggregated news. The integration of multilingual capabilities has expanded the reach of AI-driven news aggregators to non-English-speaking markets, unlocking new growth opportunities in regions with high internet penetration and diverse linguistic landscapes. This technological maturation, combined with increasing regulatory scrutiny on digital content, underscores the importance of robust AI-driven solutions in ensuring the accuracy and relevance of news dissemination.

Regionally, North America remains the largest contributor to the AI-Driven News Aggregation market, accounting for approximately 38% of global revenues in 2024. The region's dominance is attributed to the presence of leading technology companies, high digital literacy, and early adoption of AI-driven solutions by both consumers and enterprises. However, Asia Pacific is emerging as the fastest-growing region, with a projected CAGR of 20.1% through 2033, driven by rapid urbanization, increasing smartphone penetration, and a burgeoning digital media landscape. Europe continues to demonstrate steady growth, supported by strong regulatory frameworks and a high demand for reliable, multilingual news aggregation platforms.

Component Analysis

The AI-Driven News Aggregation market is segmented by component into Software and Services. Software solutions form the backbone of this market, encompassing AI-powered aggregation engines, natu

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Dollar Index (Live)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

AI-Driven News Aggregation Market Outlook

According to our latest research, the global AI-driven news aggregation market size reached USD 5.4 billion in 2024, with a robust compound annual growth rate (CAGR) of 17.2% forecasted from 2025 to 2033. By 2033, the market is anticipated to reach USD 23.7 billion as per our CAGR calculations. This impressive growth trajectory is primarily fueled by the surging demand for real-time, personalized content, the proliferation of digital devices, and the increasing reliance on artificial intelligence for automated content curation and distribution.

A key growth driver for the AI-driven news aggregation market is the exponential increase in digital content consumption across the globe. With the proliferation of smartphones, tablets, and other connected devices, users are constantly seeking up-to-date information tailored to their interests. AI-powered news aggregators leverage advanced machine learning algorithms and natural language processing to filter, analyze, and deliver highly personalized news feeds. This not only enhances user engagement but also addresses the challenge of information overload by streamlining vast amounts of news content into manageable, relevant streams. As digital literacy continues to rise and internet penetration deepens, the demand for intelligent content aggregation solutions is expected to escalate further, driving market expansion.

Another significant factor propelling market growth is the increasing adoption of AI technologies by media organizations and enterprises aiming to optimize their content strategies. Newsrooms and digital publishers are leveraging AI-driven tools to automate editorial workflows, perform sentiment analysis, and generate real-time alerts on trending topics. These capabilities enable organizations to respond rapidly to breaking news, understand audience sentiment, and enhance content relevance. Furthermore, enterprises outside the media industry, such as financial services and government agencies, are adopting AI-driven news aggregation platforms to monitor market developments, regulatory changes, and public sentiment, thereby improving decision-making processes and risk management.

The integration of advanced analytics and natural language understanding into news aggregation platforms is also a critical growth catalyst. Modern AI-driven solutions not only aggregate content from diverse sources but also perform deep semantic analysis to identify trends, biases, and emerging narratives. This empowers users to gain a more comprehensive and nuanced understanding of current events. The ability to offer multilingual support and cross-platform integration further extends the reach of these platforms, making them indispensable tools for global audiences. As AI models continue to improve in accuracy and contextual understanding, the value proposition of AI-driven news aggregation platforms will become even more compelling, fostering sustained market growth.

From a regional perspective, North America currently dominates the AI-driven news aggregation market, owing to its advanced technological infrastructure, high internet penetration, and the presence of leading AI innovators. Europe follows closely, driven by strong digital adoption and regulatory initiatives promoting transparency in news dissemination. The Asia Pacific region is poised for the fastest growth over the forecast period, buoyed by rapid digital transformation, expanding middle-class populations, and increasing consumption of digital media. Latin America and the Middle East & Africa are also witnessing rising adoption, albeit from a smaller base, as digital connectivity improves and local content aggregation platforms gain traction.

Component Analysis

The component segment of the AI-driven news aggregation market is bifurcated into software and services. The software segment currently holds the lion’s share of the market, accounting for over 68% of global revenue in 2024. This dom