#Bloomberg Website Data Scraping

[iwebscrapingblogs]

Bloomberg Website Data Scraping | Scrape Bloomberg Website Data

In the era of big data, accessing and analyzing financial information quickly and accurately is crucial for businesses and investors. Bloomberg, a leading global provider of financial news and data, is a goldmine for such information. However, manually extracting data from Bloomberg's website can be time-consuming and inefficient. This is where data scraping comes into play. In this blog post, we'll explore the intricacies of scraping data from the Bloomberg website, the benefits it offers, and the ethical considerations involved.

What is Data Scraping?

Data scraping, also known as web scraping, involves extracting information from websites and converting it into a structured format, such as a spreadsheet or database. This process can be automated using various tools and programming languages like Python, which allows users to collect large amounts of data quickly and efficiently.

Why Scrape Data from Bloomberg?

1. Comprehensive Financial Data

Bloomberg provides a wealth of financial data, including stock prices, financial statements, economic indicators, and news updates. Access to this data can give businesses and investors a competitive edge by enabling them to make informed decisions.

2. Real-Time Updates

With Bloomberg's real-time updates, staying ahead of market trends becomes easier. Scraping this data allows for the creation of custom alerts and dashboards that can notify users of significant market movements as they happen.

3. Historical Data Analysis

Analyzing historical data can provide insights into market trends and help predict future movements. Bloomberg's extensive archives offer a treasure trove of information that can be leveraged for backtesting trading strategies and conducting financial research.

4. Custom Data Aggregation

By scraping data from Bloomberg, users can aggregate information from multiple sources into a single, cohesive dataset. This can streamline analysis and provide a more holistic view of the financial landscape.

How to Scrape Bloomberg Data

Tools and Technologies

Python: A versatile programming language that offers various libraries for web scraping, such as BeautifulSoup, Scrapy, and Selenium.

BeautifulSoup: A Python library used for parsing HTML and XML documents. It creates parse trees that help extract data easily.

Scrapy: An open-source web crawling framework for Python. It's used for large-scale web scraping and can handle complex scraping tasks.

Selenium: A web testing framework that can be used to automate browser interactions. It's useful for scraping dynamic content that requires JavaScript execution.

Steps to Scrape Bloomberg Data

Identify the Data to Scrape: Determine the specific data you need, such as stock prices, news articles, or financial statements.

Inspect the Website: Use browser tools to inspect the HTML structure of the Bloomberg website and identify the elements containing the desired data.

Set Up Your Environment: Install the necessary libraries (e.g., BeautifulSoup, Scrapy, Selenium) and set up a Python environment.

Write the Scraping Script: Develop a script to navigate the website, extract the data, and store it in a structured format.

Handle Data Storage: Choose a storage solution, such as a database or a CSV file, to save the scraped data.

Ensure Compliance: Make sure your scraping activities comply with Bloomberg's terms of service and legal regulations.

Sample Python Code

Here's a basic example of how to use BeautifulSoup to scrape stock prices from Bloomberg:

python

import requests from bs4 import BeautifulSoup # URL of the Bloomberg page to scrape url = 'https://www.bloomberg.com/markets/stocks' # Send a GET request to the URL response = requests.get(url) # Parse the HTML content soup = BeautifulSoup(response.text, 'html.parser') # Extract stock prices stocks = soup.find_all('div', class_='price') for stock in stocks: print(stock.text)

Ethical Considerations

While data scraping offers numerous benefits, it's important to approach it ethically and legally:

Respect Website Terms of Service: Always review and comply with the terms of service of the website you're scraping.

Avoid Overloading Servers: Implement rate limiting and avoid making excessive requests to prevent server overload.

Use Data Responsibly: Ensure that the scraped data is used ethically and does not violate privacy or intellectual property rights.

Conclusion

Scraping data from the Bloomberg website can provide valuable insights and competitive advantages for businesses and investors. By using the right tools and following ethical guidelines, you can efficiently gather and analyze financial data to make informed decisions. Whether you're tracking real-time market trends or conducting historical data analysis, web scraping is a powerful technique that can unlock the full potential of Bloomberg's extensive data offerings.

[anniekoh]

elsewhere on the internet: AI and advertising

Bubble Trouble (about AIs trained on AI output and the impending model collapse) (Ed Zitron, Mar 2024)

A Wall Street Journal piece from this week has sounded the alarm that some believe AI models will run out of "high-quality text-based data" within the next two years in what an AI researcher called "a frontier research problem."  Modern AI models are trained by feeding them "publicly-available" text from the internet, scraped from billions of websites (everything from Wikipedia to Tumblr, to Reddit), which the model then uses to discern patterns and, in turn, answer questions based on the probability of an answer being correct. Theoretically, the more training data that these models receive, the more accurate their responses will be, or at least that's what the major AI companies would have you believe. Yet AI researcher Pablo Villalobos told the Journal that he believes that GPT-5 (OpenAI's next model) will require at least five times the training data of GPT-4. In layman's terms, these machines require tons of information to discern what the "right" answer to a prompt is, and "rightness" can only be derived from seeing lots of examples of what "right" looks like. ... One (very) funny idea posed by the Journal's piece is that AI companies are creating their own "synthetic" data to train their models, a "computer-science version of inbreeding" that Jathan Sadowski calls Habsburg AI.  This is, of course, a terrible idea. A research paper from last year found that feeding model-generated data to models creates "model collapse" — a "degenerative learning process where models start forgetting improbable events over time as the model becomes poisoned with its own projection of reality."

...

The AI boom has driven global stock markets to their best first quarter in 5 years, yet I fear that said boom is driven by a terrifyingly specious and unstable hype cycle. The companies benefitting from AI aren't the ones integrating it or even selling it, but those powering the means to use it — and while "demand" is allegedly up for cloud-based AI services, every major cloud provider is building out massive data center efforts to capture further demand for a technology yet to prove its necessity, all while saying that AI isn't actually contributing much revenue at all. Amazon is spending nearly $150 billion in the next 15 years on data centers to, and I quote Bloomberg, "handle an expected explosion in demand for artificial intelligence applications" as it tells its salespeople to temper their expectations of what AI can actually do.  I feel like a crazy person every time I read glossy pieces about AI "shaking up" industries only for the substance of the story to be "we use a coding copilot and our HR team uses it to generate emails." I feel like I'm going insane when I read about the billions of dollars being sunk into data centers, or another headline about how AI will change everything that is mostly made up of the reporter guessing what it could do.

They're Looting the Internet (Ed Zitron, Apr 2024)

An investigation from late last year found that a third of advertisements on Facebook Marketplace in the UK were scams, and earlier in the year UK financial services authorities said it had banned more than 10,000 illegal investment ads across Instagram, Facebook, YouTube and TikTok in 2022 — a 1,500% increase over the previous year. Last week, Meta revealed that Instagram made an astonishing $32.4 billion in advertising revenue in 2021. That figure becomes even more shocking when you consider Google's YouTube made $28.8 billion in the same period . Even the giants haven’t resisted the temptation to screw their users. CNN, one of the most influential news publications in the world, hosts both its own journalism and spammy content from "chum box" companies that make hundreds of millions of dollars driving clicks to everything from scams to outright disinformation. And you'll find them on CNN, NBC and other major news outlets, which by proxy endorse stories like "2 Steps To Tell When A Slot Is Close To Hitting The Jackpot."  These “chum box” companies are ubiquitous because they pay well, making them an attractive proposition for cash-strapped media entities that have seen their fortunes decline as print revenues evaporated. But they’re just so incredibly awful. In 2018, the (late, great) podcast Reply All had an episode that centered around a widower whose wife’s death had been hijacked by one of these chum box advertisers to push content that, using stolen family photos, heavily implied she had been unfaithful to him. The title of the episode — An Ad for the Worst Day of your Life — was fitting, and it was only until a massively popular podcast intervened did these networks ban the advert.  These networks are harmful to the user experience, and they’re arguably harmful to the news brands that host them. If I was working for a major news company, I’d be humiliated to see my work juxtaposed with specious celebrity bilge, diet scams, and get-rich-quick schemes.

...

While OpenAI, Google and Meta would like to claim that these are "publicly-available" works that they are "training on," the actual word for what they're doing is "stealing." These models are not "learning" or, let's be honest, "training" on this data, because that's not how they work — they're using mathematics to plagiarize it based on the likelihood that somebody else's answer is the correct one. If we did this as a human being — authoritatively quoting somebody else's figures without quoting them — this would be considered plagiarism, especially if we represented the information as our own. Generative AI allows you to generate lots of stuff from a prompt, allowing you to pretend to do the research much like LLMs pretend to know stuff. It's good for cheating at papers, or generating lots of mediocre stuff LLMs also tend to hallucinate, a virtually-unsolvable problem where they authoritatively make incorrect statements that creates horrifying results in generative art and renders them too unreliable for any kind of mission critical work. Like I’ve said previously, this is a feature, not a bug. These models don’t know anything — they’re guessing, based on mathematical calculations, as to the right answer. And that means they’ll present something that feels right, even though it has no basis in reality. LLMs are the poster child for Stephen Colbert’s concept of truthiness.

[datascraping001]

Bloomberg News Data Extraction

Enhance Your Insights with Bloomberg News Data Extraction Services by DataScrapingServices.com

In today's fast-paced world, staying informed with the latest news and market trends is crucial for businesses and investors. Bloomberg is a leading source of financial news, providing real-time updates and in-depth analysis. To harness this wealth of information effectively, DataScrapingServices.com offers specialized Bloomberg News Data Extraction Services. Our services are designed to provide you with accurate and comprehensive data, empowering you to make informed decisions and stay ahead in the competitive market.

Bloomberg News is a go-to platform for financial professionals, offering timely and relevant information on global markets, economic trends, and major business developments. However, manually sifting through vast amounts of news articles to find relevant data can be daunting and inefficient. DataScrapingServices.com solves this challenge by providing automated data extraction services that gather, clean, and organize news data from Bloomberg. Our service ensures you have access to the critical information you need, when you need it, without the hassle of manual research.

List of Data Fields

Our Bloomberg News Data Extraction Services cover a wide range of data fields to provide you with a comprehensive view of the financial landscape:

- Headline: The title of the news article, giving a quick overview of the topic.

- Publication Date and Time: When the news article was published, ensuring you have the most recent information.

- Author: The journalist or analyst who wrote the article, providing context on the perspective and expertise.

- Article Content: The full text of the news article, offering detailed insights and analysis.

- Keywords: Relevant keywords and tags associated with the article, aiding in quick identification of relevant topics.

- Category: The section or category the article belongs to, such as markets, technology, or politics.

- Source URL: The link to the original article on Bloomberg's website for reference.

- Stock Symbols Mentioned: Tickers of companies discussed in the article, useful for investors and financial analysts.

- Geographical Tags: Locations mentioned in the article, helping to understand regional impacts.

Benefits of Bloomberg News Data Extraction

1. Real-Time Market Insights

Stay ahead of market movements with real-time data extraction. Our services ensure you have immediate access to breaking news and critical updates, enabling you to make timely and informed decisions.

2. Comprehensive Analysis

With detailed article content and relevant metadata, you can perform thorough analysis and gain deeper insights into market trends and financial events. This comprehensive approach helps in understanding the broader impact of news on your business or investments.

3. Enhanced Decision-Making

Accurate and timely information is crucial for strategic decision-making. By leveraging our data extraction services, you can base your decisions on reliable data, reducing risks and increasing the chances of success.

4. Efficiency and Productivity

Automating the data extraction process saves time and resources. Instead of manually searching and compiling data, your team can focus on analyzing the information and developing strategies, enhancing overall productivity.

5. Customizable Data Solutions

Whether you need data on specific topics, companies, or regions, we can customize the extraction process to provide the most relevant information for your objectives.

Best News Website Article Scraping Services Provider

Extract Google News Articles

CNN News Data Scraping

News Website Article Scraping

Google News Headline Extraction

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Best Bloomberg News Data Extraction Services in USA:

Chicago, Indianapolis, Memphis, San Antonio, Houston, Colorado, Fresno, Sacramento, San Francisco, Nashville, Denver, Omaha, Mesa, Charlotte, Tulsa, Las Vegas, Austin, Louisville, Seattle, Bakersfield, Springs, Arlington, Honolulu, Miami, Portland, Los Angeles, Atlanta, Jacksonville, Virginia Beach, Dallas, Oklahoma City, San Jose, Boston, El Paso, Long Beach, Philadelphia, Wichita, Columbus, Washington, Fort Worth, Kansas City, Raleigh, Albuquerque, Orlando, Milwaukee, San Diego, New Orleans, Tucson and New York.

Conclusion

In the fast-evolving world of finance, staying informed with accurate and timely news is paramount. Bloomberg News Data Extraction Services by DataScrapingServices.com offers a powerful solution to gather and organize critical financial information efficiently. By leveraging our services, you can enhance your market insights, improve decision-making, and stay ahead of the competition. Contact us at info@datascrapingservices.com today to learn how our data extraction solutions can transform your information management and strategic planning processes.

Website: Datascrapingservices.com

Email: info@datascrapingservices.com

[iwebdata]

How Does Python Facilitate Stock Data Scraping From Various Sources?

How Does Python Facilitate Stock Data Scraping From Various Sources?

In the dynamic realm of finance, access to precise stock data is crucial for sound investment choices. Yet, manually aggregating this information from numerous websites is laborious and time-intensive. Thankfully, Python provides an efficient remedy through finance data scraping, with Selenium rising as a favored tool for extracting dynamic content. This article delves into harnessing Selenium and Python to scrape stock data from diverse websites, facilitating profound insights into financial markets. By automating the data retrieval, investors can swiftly access accurate stock data, enabling informed decision-making and strategic investments. This approach streamlines the data collection process and empowers investors with real-time market insights, facilitating agility and competitiveness in the ever-evolving financial landscape. The ability to scrape stock data using Python and Selenium offers a valuable toolkit for investors seeking to navigate and capitalize on market trends effectively.

Here is a list of popular websites where you can find stock data:

Yahoo Finance

Google Finance

Bloomberg

CNBC

MarketWatch

Reuters

Investing.com

Real-time stock quotes.

Market analysis.

In-depth reports from a team of experienced journalists and analysts.

Users can extract stock data from Reuters' platform, including prices, market trends, and company reports, for analysis and decision-making.

Understanding Python Web Scraping with Selenium

Selenium is a versatile automation tool that allows you to interact with web pages as a user would. Combined with Python's extensive data manipulation and analysis libraries, Selenium provides a comprehensive solution for scraping stock data from various websites.

Setting Up Your Environment: Before diving into web scraping, you must set up your Python environment and install the necessary packages. Ensure you have Python installed on your system, and install Selenium using pip:

pip install selenium

You'll also need to download a web driver compatible with your preferred browser (e.g., Chrome, Firefox). WebDriver acts as a bridge between your Python script and the browser, allowing Selenium to automate interactions.

Repeat this process for each data you want to extract, such as stock prices, volume, or market trends.

Handling Dynamic Content and Pagination: Many stock websites feature dynamic content and pagination, which can complicate the scraping process. Selenium excels at handling such scenarios, allowing you to seamlessly interact with dynamic elements and navigate multiple pages.

To handle pagination, identify the navigation elements (e.g., "Next Page" buttons) and use Selenium to click on them programmatically. Repeat this process until you've scraped all the desired data from each page.

Storing and Analyzing Data: Once you've scraped the stock data, you can store it in a structured format such as CSV, Excel, or a database for further analysis. Python's pandas library is handy for data manipulation and analysis, allowing you to perform calculations, visualize trends, and derive insights from the scraped data.

Conclusion: Stock data scraping services provide a powerful means to efficiently access and analyze stock data from various sources. By leveraging tools like Selenium, users can automate the process of gathering real-time stock quotes, news, and financial information from platforms such as Yahoo Finance, Google Finance, Bloomberg, CNBC, MarketWatch, Reuters, and Investing.com. It enables investors to make informed decisions, track market trends, and identify investment opportunities more efficiently and accurately. Scraping stock data using Pythion and Selenium, the financial market becomes more accessible, empowering investors to stay ahead of the curve and maximize their investment potential.

Get in touch with iWeb Data Scraping for a wide array of data services! Our team will provide expert guidance if you require web scraping service or mobile app data scraping. Contact us now to discuss your needs for scraping retail store location data. Discover how our tailored data scraping solutions can bring efficiency and reliability to meet your specific requirements effectively.

Know More : https://www.iwebdatascraping.com/python-facilitate-stock-data-scraping.php

[cyberianlife]

Meta has routinely fought data scrapers, but it also participated in that practice itself — if not necessarily for the same reasons. Bloomberg has obtained legal documents from a Meta lawsuit against a former contractor, Bright Data, indicating that the Facebook owner paid its partner to scrape other websites. Meta spokesperson Andy Stone confirmed the relationship in a discussion with Bloomberg, but said his company used Bright Data to build brand profiles, spot "harmful" sites and catch phishing campaigns, not to target competitors.

[hostor-infotech]

Documents show Meta paid for data scraping despite years of denouncing it

Meta has routinely fought data scrapers, but it also participated in that practice itself — if not necessarily for the same reasons. Bloomberg has obtained legal documents from a Meta lawsuit against a former contractor, Bright Data, indicating that the Facebook owner paid its partner to scrape other websites. Meta spokesperson Andy Stone confirmed the relationship in a discussion with Bloomberg,…

[sheminecrafts]

Gettr, the latest pro-Trump social network, is already a mess

Well, that was fast. Just days after a Twitter clone from former Trump spokesperson Jason Miller launched, the new social network is already beset by problems.

For one, hackers quickly leveraged Gettr’s API to scrape the email addresses of more than 85,000 of its users. User names, names and birthdays were also part of the scraped data set, which was surfaced by Alon Gal, co-founder of cybersecurity firm Hudson Rock.

“When threat actors are able to extract sensitive information due to neglectful API implementations, the consequence is equivalent to a data breach and should be handled accordingly by the firm [and] examined by regulators,” Gal told TechCrunch.

Last week, TechCrunch’s own Zack Whittaker predicted that Gettr would soon see its data scraped through its API.

Threat actors were able to take advantage of bad API implemented on Trump's recent social media platform, Gettr (@GettrOfficial).

This allowed them to extract usernames, names, bios, bdays, but most importantly, the emails which were supposed to be private, of over 85,000 users. pic.twitter.com/NsKyz9zHmQ

— Alon Gal (Under the Breach) (@UnderTheBreach) July 6, 2021

The scraped data is just one of Gettr’s headaches. The app actually went live in the App Store and Google Play last month but left beta on July 4 following a launch post in Politico. While the app is meant to appeal to the famously anti-China Trump sphere, Gettr apparently received early funding from Chinese billionaire Guo Wengui, an ally of former Trump advisor Steve Bannon. Earlier this year, The Washington Post reported that Guo is at the center of a massive online disinformation network that spreads anti-vaccine claims and QAnon conspiracies.

On July 2, the app’s team apologized for signup delays citing a spike in downloads, but a bit of launch downtime is probably the least of its problems. Over the weekend, a number of official Gettr accounts including Marjorie Taylor-Greene, Steve Bannon, and Miller’s own were compromised, raising more questions about the app’s shoddy security practices.

Jason Miller's new right-wing social media site "Gettr" was hacked this morning. pic.twitter.com/cncddw9RZ9

— Zachary Petrizzo (@ZTPetrizzo) July 4, 2021

That incident aside, fake accounts overwhelm any attempt to find verified users on Gettr. That goes for the app’s own recommendations too: a fake brand account for Steam was among the app’s own recommendations during TechCrunch’s testing.

Another red flag: The app’s design is conspicuously identical to Twitter and appears to have used the company’s API to copy some users’ follower counts and profiles. Gettr encourages new users to use their Twitter handle in the sign up process, saying that it will allow tweets to be copied over in some cases (we signed up, but this didn’t work for us). TechCrunch reached out to Twitter about Gettr’s striking similarities and the use of its API but the company declined to comment.

Trumps Gettr website didn't just copy old Twitter posts it hotlinks to Twitter images! pic.twitter.com/848G6zTXuS

— zedster (@z3dster) July 1, 2021

On mobile, Gettr is basically an exact clone of Twitter — albeit one that’s very rough around the edges. Some of Gettr’s copy is stilted and strange, including the boast that it’s a “non-bias” social network that “tried the best to provide best software quality to the users, allow anyone to express their opinion freely.”

The company is positioning itself as an alternative for anyone who believes that mainstream social networks are hostile to far right ideas. Gettr’s website beckons new users with familiar Trumpian messaging: “Don’t be Cancelled. Flex Your 1st Amendment. Celebrate Freedom.”

“Hydroxycholoroquine works!” Miller shared (Gettr’d?) over the weekend, quoting the former president. “And nobody is going to take down this post or suspend this account! #GETTR.” So far on Gettr, content moderation is either lax or nonexistent. But as we’ve seen with Parler and other havens for sometimes violent conspiracies, that approach can only last so long.

In spite of being widely associated with Trump through Miller and former Trump campaign staffer Tim Murtaugh, the former president doesn’t yet have a presence on the app. Some figures from Trump’s orbit have established profiles on Gettr, including Steve Bannon (84.7K followers) and Mike Pompeo (1.3M followers), but a search for Trump only brings up unofficial accounts. Bloomberg reported that Trump has no plans to join the app. (Given Gettr’s preponderance of Sonic the Hedgehog porn, we can’t exactly blame him.)

It’s hard to say whether the app’s technical issues or Trump’s absence will dampen interest in Gettr. According to estimates from Sensor Tower, Gettr has racked up roughly 1.3 million installs globally since June, with Brazil trailing the U.S. as the app’s second biggest market.

The online pro-Trump ecosystem remains scattered in mid-2021. With Trump banned and the roiling conspiracy network around QAnon no longer welcome on Facebook and Twitter, Gettr positioned itself as a refuge for mainstream social media’s many outcasts. But given Gettr’s mounting early woes, the sketchy Twitter clone’s moment in the sun might already be coming to an end.

Twitter bans former Trump adviser Michael Flynn and other QAnon figures

For Trump and Facebook, judgment day is around the corner

from iraidajzsmmwtv https://ift.tt/3jOrdpT via IFTTT

[96thdayofrage]

While Facebook says that the vulnerability that allowed this information to be scraped was patched in August 2019, that does nothing to protect the information that has already been leaked. It also does nothing to alleviate concerns that Facebook collects and monetizes its users' personal information, but has a poor record of protecting that information from bad actors.

In that sense, the leak of a database that includes information on a half-billion users is worse than it might seem for two reasons. First, Facebook's response shows that the company continues to lack any real sense of understanding of its responsibility to protect its users' privacy.

"This is old data that was previously reported on in 2019," a spokesperson told Bloomberg in a statement. "We found and fixed this issue in August 2019."

It's as if the company wants to take credit for fixing a problem because it patched a massive hole in its security, even though none of the stolen goods have been recovered. I reached out to Facebook directly, but the company did not immediately respond.

That's a problem because Facebook knows a lot about you--perhaps more than any other company on earth. The information that Facebook gathers is what it uses to show you targeted advertisements, but in the hands of hackers and criminals, it can be used for much more nefarious purposes.

Imagine if robbers were able to steal the contents of a bank vault because someone left the door open and unguarded (which is basically what Facebook did with your personal information). That would be bad. It would be even worse if the bank's response after the fact was "yeah, we know that a bunch of your money is gone, but we've closed the vault and changed the combination."

The problem isn't just that the vault was left open, it's that everything inside was stolen and hasn't been recovered. That's the real problem and it hasn't been fixed.

Of course--and this is the second problem--Facebook can't get the information back. That's not how things work in a digital world. It's also probably why the company has yet to acknowledge its responsibility, or even to notify individual users whose information has been compromised.

That's why this is much worse than a bank robbery. Once your personal information is leaked online, there's literally nothing that can stop it from being sold to anyone who might want to use it for less-than-noble purposes.

Especially concerning is the fact that, in many cases, the database included both email addresses and phone numbers. Considering that many people use their email address to log in to websites and accounts online, and that phone numbers are often used to verify your identity for those accounts, the fact that they are both contained in the same database could make it easier for criminals to gain access to your accounts.

[datascraping001]

News Website Article Scraping

Harness the Power of Information with News Website Article Scraping Services by DataScrapingServices.com

In today’s fast-paced digital age, staying updated with the latest news and trends is crucial for businesses, researchers, and individuals alike. However, manually sifting through countless news websites to gather relevant information can be a daunting and time-consuming task. DataScrapingServices.com offers a solution with our News Website Article Scraping Services, providing an efficient and reliable way to collect and analyze news articles from various online sources.

The sheer volume of news content available online can be overwhelming. From breaking news and in-depth analysis to opinion pieces and feature stories, news websites produce a vast amount of data every day. For businesses looking to track industry trends, researchers studying media coverage, or anyone needing to stay informed, accessing and managing this information efficiently is essential. DataScrapingServices.com specializes in extracting news articles from multiple websites, ensuring you receive comprehensive, accurate, and up-to-date information tailored to your needs.

List of Data Fields

Our News Website Article Scraping Services extract a wide range of data fields, providing a detailed and organized dataset for your analysis:

- Headline: The title of the news article.

- Publication Date: The date and time the article was published.

- Author: The name of the article’s author.

- Content: The full text of the article.

- URL: The web address where the article is located.

- Category: The category or section under which the article is published (e.g., politics, sports, technology).

- Source: The name of the news website or publication.

- Images: URLs or data of images included in the article.

- Tags/Keywords: Keywords or tags associated with the article.

- Summary/Excerpt: A brief summary or excerpt of the article.

- Comments: Reader comments or feedback on the article (if available).

- Social Media Links: Links to the article’s social media shares (if available).

Benefits of News Website Article Scraping

1. Enhanced Market and Competitor Analysis

Access to a vast array of news articles allows businesses to monitor market trends and competitor activities. By analyzing news coverage, you can identify emerging trends, gauge public sentiment, and stay ahead of the competition.

2. Improved Media Monitoring

For public relations and media monitoring professionals, our service provides a streamlined way to track media coverage across various sources. By automating the collection of news articles, you can focus on analyzing the content and developing effective media strategies.

3. Comprehensive Research and Analysis

Researchers and analysts benefit from having a large dataset of news articles at their disposal. Whether you’re studying media bias, conducting sentiment analysis, or exploring trends in news reporting, our scraping services provide the raw data needed for thorough research.

4. Content Aggregation

For content creators and aggregators, our service enables the efficient collection of news articles for publication or redistribution. This helps in curating relevant content for your audience, enhancing engagement, and providing value.

5. Time and Cost Efficiency

Manually gathering and organizing news articles is time-consuming and labor-intensive. Our automated scraping services save you time and resources, allowing you to focus on more critical tasks. This efficiency leads to reduced costs and increased productivity.

Best News Website Article Scraping Services Provider

News Website Article Scraping

Google News Headline Extraction

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Extract Google News Articles

Bloomberg News Data Extraction

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Best News Website Article Scraping Services in USA:

Colorado, Fresno, Sacramento, San Francisco, Nashville, Chicago, Indianapolis, Memphis, San Antonio, Houston, Denver, Omaha, Mesa, Charlotte, Honolulu, Miami, Portland, Los Angeles, Atlanta, Tulsa, Las Vegas, Austin, Louisville, Seattle, Bakersfield, Springs, Arlington, Jacksonville, Virginia Beach, Dallas, Oklahoma City, San Jose, Washington, Fort Worth, Kansas City, Raleigh, Albuquerque, Boston, El Paso, Long Beach, Philadelphia, Wichita, Columbus, Orlando, Milwaukee, San Diego, New Orleans, Tucson and New York.

Conclusion

In an era where information is power, having access to comprehensive and organized news data is essential. News Website Article Scraping Services by DataScrapingServices.com offer a powerful tool for businesses, researchers, and media professionals to gather and analyze news articles efficiently. By leveraging our advanced scraping technology, you can enhance market analysis, improve media monitoring, conduct thorough research, and curate relevant content. Contact us at info@datascrapingservices.com today to discover how our News Website Article Scraping Services can transform your information gathering and analysis processes.

Website: Datascrapingservices.com

Email: info@datascrapingservices.com

[breakbit]

Ramaphosa Faces Moment of Truth as South Africa Counts Votes

New Post has been published on https://worldwide-finance.net/news/commodities-futures-news/ramaphosa-faces-moment-of-truth-as-south-africa-counts-votes

Ramaphosa Faces Moment of Truth as South Africa Counts Votes

(Bloomberg) — South Africa started counting votes after an election that puts President Cyril Ramaphosa’s tenuous grip over his party to the test and hopes of reviving a flagging economy at stake.

While opinion polls all point to a sixth outright national election win for the African National Congress, the margin of victory will be crucial for Ramaphosa after he scraped through a party leadership vote in December 2017. With about 14% of ballots counted by 7:52 a.m. in Pretoria on Thursday, the ANC had secured 54.8%. The final outcome is expected by Saturday.

The 66-year-old lawyer and former labor-union leader is looking for a decisive win to quell opposition in the faction-riven ANC to give him the clout to push through reforms needed to spur growth in Africa’s most-industrialized economy. A narrow victory could embolden his critics and may force the party into coalitions to retain control of some provinces, limiting his policy options.

“Ramaphosa is weak and vulnerable inside the ANC, but strong in the government and protected by society,” said Xolani Dube, an analyst at the Xubera Institute for Research and Development in the eastern city of Durban. “He needs to navigate how to serve the interests of two masters — the ANC constituency that reluctantly placed him into power and society at large, which holds the key to keeping him safe from the wolves of his own party.”

Declining Share

The ANC share of the vote has declined from a peak of more than 69% in 2004, when the economy was expanding at about 5% a year and the government was cutting taxes. Its support plummeted to 54.5% in 2016 municipal elections when its supporters shunned the ballot amid weak economic growth and allegations of graft and misrule during Jacob Zuma’s presidency.

The ANC forced Zuma to resign in February last year, but after initial euphoria when Ramaphosa took over, confidence has slumped and is now at multi-year lows. The rand is more than 20% weaker against the dollar over that period. The currency gained for a second day on Wednesday as the vote proceeded peacefully. The equity and bond markets were closed for the election-day holiday.

Investors are expecting Ramaphosa to use a strong mandate to implement structural reforms to lure investment and spark an economy that has expanded by less than 1.5% for the past four years. He would still face an unemployment rate of more than 27%, persistently high inequality and ballooning debt. The government has failed to close a yawning fiscal gap despite tax hikes over the past five years.

The election will allocate seats in the 400-member National Assembly and nine provincial legislatures to parties based on the proportion of the vote they win. A first meeting of the new parliament has been provisionally set for May 22, where the president is due to be officially elected.

Also at stake in this election is the ANC’s majority in the province of Gauteng, which includes the capital, Pretoria, and the economic hub of Johannesburg. The ruling party lost both cities in the 2016 municipal election, with the Democratic Alliance taking control with support from smaller parties.

The ANC’s main challengers among 48 parties contesting the national vote are Mmusi Maimane’s center-right DA and the populist Economic Freedom Fighters, led by former ANC youth-wing leader Julius Malema.

(Updates with latest results in second paragraph.)

Disclaimer: Fusion Media would like to remind you that the data contained in this website is not necessarily real-time nor accurate. All CFDs (stocks, indexes, futures) and Forex prices are not provided by exchanges but rather by market makers, and so prices may not be accurate and may differ from the actual market price, meaning prices are indicative and not appropriate for trading purposes. Therefore Fusion Media doesn`t bear any responsibility for any trading losses you might incur as a result of using this data.

Fusion Media or anyone involved with Fusion Media will not accept any liability for loss or damage as a result of reliance on the information including data, quotes, charts and buy/sell signals contained within this website. Please be fully informed regarding the risks and costs associated with trading the financial markets, it is one of the riskiest investment forms possible.

Read More https://worldwide-finance.net/news/commodities-futures-news/ramaphosa-faces-moment-of-truth-as-south-africa-counts-votes

[taylordmorris]

Ramaphosa Faces Moment of Truth as South Africa Counts Votes

New Post has been published on https://worldwide-finance.net/news/commodities-futures-news/ramaphosa-faces-moment-of-truth-as-south-africa-counts-votes

Ramaphosa Faces Moment of Truth as South Africa Counts Votes

(Bloomberg) — South Africa started counting votes after an election that puts President Cyril Ramaphosa’s tenuous grip over his party to the test and hopes of reviving a flagging economy at stake.

While opinion polls all point to a sixth outright national election win for the African National Congress, the margin of victory will be crucial for Ramaphosa after he scraped through a party leadership vote in December 2017. With about 14% of ballots counted by 7:52 a.m. in Pretoria on Thursday, the ANC had secured 54.8%. The final outcome is expected by Saturday.

The 66-year-old lawyer and former labor-union leader is looking for a decisive win to quell opposition in the faction-riven ANC to give him the clout to push through reforms needed to spur growth in Africa’s most-industrialized economy. A narrow victory could embolden his critics and may force the party into coalitions to retain control of some provinces, limiting his policy options.

“Ramaphosa is weak and vulnerable inside the ANC, but strong in the government and protected by society,” said Xolani Dube, an analyst at the Xubera Institute for Research and Development in the eastern city of Durban. “He needs to navigate how to serve the interests of two masters — the ANC constituency that reluctantly placed him into power and society at large, which holds the key to keeping him safe from the wolves of his own party.”

Declining Share

The ANC share of the vote has declined from a peak of more than 69% in 2004, when the economy was expanding at about 5% a year and the government was cutting taxes. Its support plummeted to 54.5% in 2016 municipal elections when its supporters shunned the ballot amid weak economic growth and allegations of graft and misrule during Jacob Zuma’s presidency.

The ANC forced Zuma to resign in February last year, but after initial euphoria when Ramaphosa took over, confidence has slumped and is now at multi-year lows. The rand is more than 20% weaker against the dollar over that period. The currency gained for a second day on Wednesday as the vote proceeded peacefully. The equity and bond markets were closed for the election-day holiday.

Investors are expecting Ramaphosa to use a strong mandate to implement structural reforms to lure investment and spark an economy that has expanded by less than 1.5% for the past four years. He would still face an unemployment rate of more than 27%, persistently high inequality and ballooning debt. The government has failed to close a yawning fiscal gap despite tax hikes over the past five years.

The election will allocate seats in the 400-member National Assembly and nine provincial legislatures to parties based on the proportion of the vote they win. A first meeting of the new parliament has been provisionally set for May 22, where the president is due to be officially elected.

Also at stake in this election is the ANC’s majority in the province of Gauteng, which includes the capital, Pretoria, and the economic hub of Johannesburg. The ruling party lost both cities in the 2016 municipal election, with the Democratic Alliance taking control with support from smaller parties.

The ANC’s main challengers among 48 parties contesting the national vote are Mmusi Maimane’s center-right DA and the populist Economic Freedom Fighters, led by former ANC youth-wing leader Julius Malema.

(Updates with latest results in second paragraph.)

Disclaimer: Fusion Media would like to remind you that the data contained in this website is not necessarily real-time nor accurate. All CFDs (stocks, indexes, futures) and Forex prices are not provided by exchanges but rather by market makers, and so prices may not be accurate and may differ from the actual market price, meaning prices are indicative and not appropriate for trading purposes. Therefore Fusion Media doesn`t bear any responsibility for any trading losses you might incur as a result of using this data.

Fusion Media or anyone involved with Fusion Media will not accept any liability for loss or damage as a result of reliance on the information including data, quotes, charts and buy/sell signals contained within this website. Please be fully informed regarding the risks and costs associated with trading the financial markets, it is one of the riskiest investment forms possible.

Read More https://worldwide-finance.net/news/commodities-futures-news/ramaphosa-faces-moment-of-truth-as-south-africa-counts-votes

[warninggraphiccontent]

14 February 2020

That was the week that was - in three tweet threads

The fact I only have time to say something in tweets probably says all that needs to be said about how busy this week has been!

On reshuffles Both more dramatic (Javid! Julian Smith!) and less dramatic (no fiddling or fundamental changes to the machinery of government) than expected. As ever, we tried to cut through the spin through charts and analysis - tweet thread here, live blog itself here.

On personal data Two small threads rather than one, really - this one on some of the personal data/politics and government stories over last weekend, and this one on the apparent decision not to consult civil society or the public on how government should process personal data. The joint civil society letter to DCMS last summer holds up well.

On data The Committee on Standards in Public Life's report on AI was a good excuse to return to our open spreadsheets of important government reports on data, information and open government, and a broader 'data' reading list. Please add anything we've missed.

We'll continue to follow what's left of the reshuffle. And I'm also taking part in what should be a fun panel dicussion on government and social media on 27 February, thanks to Vuelio - come!

Have a great weekend

Gavin

Today's links:

Graphic content

Everyday I'm reshufflin'

Government reshuffle February 2020: live blog (IfG)

Thread (me for IfG)

Cabinet diversity (Ketaki for IfG)

Perm secs (me for IfG)

Cummings: the man who ‘hates the media’ is most in the news* (The Times, via Tim)

Labour pains

Labour leadership: The party's ups and downs charted over a century (BBC News)

Another version (Nigel Marriott)

And another (IfG)

What the latest CLP nominations tell us about Labour’s leadership elections (LabourList)

Leader, deputy leader, Labour prime minister (thread - Tom Wilson)

Labour’s history of highs and lows — and what it reveals* (The Times)

Diagnosis of Defeat: Labour’s Turn to Smell the Coffee (Lord Ashcroft)

UK

Our politics in one chart... (via Matt Bevington)

UK Poverty 2019/20 (Joseph Rowntree Foundation)

Scottish Index of Multiple Deprivation (Jamie Whyte)

The companies that win the most UK government contracts have a bigger #genderpaygap than their competitors (Lobo)

US politics

Who’s Winning the 2020 Presidential Delegate Count?* (Bloomberg)

Which Candidates Got the Most Speaking Time in the Democratic Debate* (New York Times)

The Democratic delegate count so far (Brian McGill/WSJ)

New Hampshire Democratic primary exit poll results and analysis* (Washington Post)

Experiment Shows Conservatives More Willing to Share Wealth Than They Say* (The Upshot)

Everything else

AI governance map v.2.0 (Nesta)

How much should we really drink?* (FT)

The financiers who struck it rich on ‘Joker’* (FT)

How the coronavirus spread across China and the world – visual explainer (The Guardian)

A ray of hope in the coronavirus curve* (The Economist)

Analysts’ stock recommendations are coloured by their cultural biases* (The Economist)

Data newsletters by diverse authors (Marie Segger)

Meta data

Personal data

Revealed: how drugs giants can access your health records (The Observer)

Labour accuses Keir Starmer campaign team of data breach (BBC News)

Thread from me

Deja vu... (Phil Booth)

No public consultation on new government frameworks for data processing (via Sam)

Labour could be fined up to £15m for failing to protect members' data (Sky News - 'General Data Protection Regulations' though???)

Data and privacy will be Brexit battlegrounds (RTE)

The risks of not sharing data are greater than the costs* (THE)

Don’t sell my data! We finally have a law for that* (Washington Post)

India's Data Protection Bill Threatens Global Cybersecurity* (Wired)

Mis/Disinformation

The Billion-Dollar Disinformation Campaign to Reelect the President* (The Atlantic)

When You Set Out To Block Misinformation, You Can Wind Up Blocking A Hero Like Li Wenliang (Techdirt)

Putinising ourselves (Standpoint)

He Combs the Web for Russian Bots. That Makes Him a Target.* (New York Times)

AI

Artificial Intelligence and Public Standards: report (CSPL)

Artificial intelligence must meet ethical standards* (The Times)

Lord Evans: AI can be game-changing for public services – but reassurance needed on how it will be used (Civil Service World)

The future of minds and machines: how artificial intelligence can enhance collective intelligence (Nesta)

Fretting about FRT

Live Facial Recognition: how good is it really? We need clarity about the statistics. (David Spiegelhalter and Kevin Mcconway)

The ACLU Slammed A Facial Recognition Company That Scrapes Photos From Instagram And Facebook (BuzzFeed)

Met police deploy live facial recognition technology (The Guardian)

Clearview's facial recognition app is identifying child victims of abuse* (New York Times)

Openness

FOIA and loathing: why government departments are less free with their information* (me for Prospect)

ICO information notices (Martin Rosenbaum/CFOI)

The right pair of eyes (Tim Davies)

New Open Knowledge Foundation website (Open Knowledge Foundation)

Tech

Online Harms White Paper - Initial consultation response (DCMS/Home Office)

Summary (Will Perrin)

FTC to Examine Past Acquisitions by Large Technology Companies (Federal Trade Commission)

Candidates for a top 10 of systemic blockers to Internet-era ways of working in your org, please! (Tom Loosemore)

11 predictions for how tech will change citizen engagement* (Apolitical)

Data

ADR UK-sponsored event explores how to ‘get things done’ with data in government (ADR UK)

Data Bites #8: Getting things done with data in government (Institute for Government)

Data institutions and implicit assumptions (Peter Wells)

This data didn't use to be news, because it didn't exist (Tom Forth)

Numbers won’t tell us the full story on regions until we start counting correctly* (The Times)

UK's 2021 census could be the last, statistics chief reveals (BBC News)

The promise of synthetic data* (FT)

Home Office statistics on Police Workforce and Police Powers and Procedures (Office for Statistics Regulation)

Everything else

Ownership Futures: Towards Democratic Public Ownership in the 21st Century (Common Wealth)

‘The intelligence coup of the century’ (Washington Post)

Mapping ‘career causeways’ for workers in the age of automation (Nesta)

Future cities... (Lou Downe)

Agile governance: How regulators can keep pace with technology* (Apolitical)

Pole position: finance chief Mike Driver on why government’s number crunchers must be central to decision making (Civil Service World)

Opportunities

JOB: Research Assistant/Research Fellow in Data Science for Governance and Public Policy (Data for Policy)

JOB: Technology Lead: Data for Science and Health (Wellcome Trust)

JOB: Geospatial Commission: Head of Geospatial Data Contracts (Cabinet Office)

JOB: Programme Manager (Parliamentary Digital Service)

CONSULTANT: Processing of biometric data in national and regional counter-terrorism measures (Privacy International)

EVENT: how political campaigning has been reshaped by social media (Vuelio)

And finally...

Six things we learned about love* (Tortoise)

Oh, but I'm proud of you (ONS, via Graham)

How football grounds explain the election result* (Prospect)

And... (Matthew Bailey and Philip Cowley)

The Stepping-Feet Illusion (Steve Stewart-Williams)

15 times things got weird on Google Maps, in honor of its 15th anniversary (Mashable)

This Professor’s ‘Amazing’ Trick Makes Quadratic Equations Easier* (New York Times)

What is the worst type of dirty data? (Angharad Stone)

[datascraping001]

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[cryptoquicknews-blog]

New Post has been published here https://is.gd/ME9mBv

Researchers Find Thousands of Crypto Pump-and-Dump Groups on Messaging Apps

This post was originally published here

There are thousands of pump-and-dump groups on popular messaging apps, a study conducted by the Social Science Research Network (SSRN) revealed Dec. 18.

Pump-and-dump is the fraudulent practice of perpetrators encouraging unwitting investors to buy an asset to inflate its price artificially, and then selling it when the price gets high enough.

This practice is not new, Cointelegraph having reported last year about Telegram groups organizing pump-and-dumps. The newly published data, however, “suggest that [the pump-and-dump] phenomenon is widespread and often quite profitable.”

According to an article on the study, published by Bloomberg Dec. 19, the researchers have identified 4,818 pump-and-dump attempts between January and July this year, studying data scraped from messaging platforms Telegram and Discord.

The academics admit that while the pump-and-dump schemes reviewed by them were conducted in a similar manner to those that already took place in the past, “the recent explosion of nearly 2,000 cryptocurrencies in a largely unregulated environment has greatly expanded the scope for abuse.”

The paper notes that “pumping obscure coins (with low volume) is much more profitable than pumping the dominant coins in the ecosystem,” but at the same time “Bitcoin is not immune from the pump-and-dump phenomenon.” The report has managed to identify 76 Bitcoin (BTC) pump-and-dump groups on Telegram and six on Discord.

As Cointelegraph reported this month, two bills addressing crypto market manipulation, dubbed “The Virtual Currency Consumer Protection Act of 2018” and “The U.S. Virtual Currency Market and Regulatory Competitiveness Act of 2018,” compiled in mid-November, are set to go before the United States House of Representatives.

The world’s second-largest stock exchange, NASDAQ, said in November that its market surveillance technology can “stamp out manipulation” in crypto markets. The first NASDAQ’s crypto client who adopted its surveillance system is Gemini, the crypto exchange owned by the Winklevoss twins.

#crypto #cryptocurrency #btc #xrp #litecoin #altcoin #money #currency #finance #news #alts #hodl #coindesk #cointelegraph #dollar #bitcoin View the website

New Post has been published here https://is.gd/ME9mBv

[acoolchristianchick]

Fatherland Card

Venezuela’s government is getting Chinese help to track all of its citizens with a national identity card referred to as the ‘fatherland card’.

In a country struggling to keep itself together in the midst of economic turmoil, Venezuela’s government is attempting to find new ways of securing greater control over its citizens.

According to Reuters, a decade ago, delegates of the government travelled to China to help develop a national ID card system that would give official documentation to its citizens.

Now, all these years later, it is working with ZTE to develop a much more advanced ID card system that pushes the limits of privacy, with it being able to track a citizen’s spending habits and how they voted. The so-called ‘fatherland card’ developed by ZTE includes a mobile payment system, with employees of the Chinese company now based in a special unit of Venezuela’s state communications company, Cantv.

Official government statements have shied away from mentioning ZTE’s involvement, except for one passing reference in a press release.

Speaking of the power of the card, a founder of the ruling Socialist Party, Héctor Navarro, said: “It’s blackmail. Venezuelans with the cards now have more rights than those without.”

Google Cloud’s Diane Greene to step down

One of Google’s highest-ranking women executives, Google Cloud CEO Diane Greene, has announced she is to step down. According to Bloomberg, she will be replaced by former Oracle executive Thoman Kurian when her tenure finishes at the end of January.

Explaining that she now wants to focus on mentoring and education, Greene’s time at Google saw her expand Google Cloud significantly, but she also drew criticism for attempting to woo the US military as a client.

Alex Jones’ website hit with card skimming malware

After being deplatformed from much of social media, the website Infowars – founded and run by Alex Jones – was recently hit with card skimming malware.

According to ZDNet, the discovery was made by Dutch security researcher Willem de Groot using a scanner that found the malware in a modified block of Google Analytics code. After scraping all content from the site’s checkout form every 1.5 seconds, the malware then sent the collected data to a remote server hosted in Lithuania.

While Jones wrote in a statement that “only 1,600 customers were affected” in the 24-hour period it was in place, much of the rest of his statement followed his conspiratorial style, as he claimed it to have been “an act of industrial and political sabotage”.

He continued: “America is under attack by globalist forces, and anyone standing up for our republic will be attacked mercilessly by the corporate press, Antifa and rogue intelligence operatives. Infowars will never surrender!”

Midlands Regional Hospital hit by ransomware

The HSE is investigating the origin of a ransomware attack against Midlands Regional Hospital in Tullamore, Co Offaly, that affected its library information systems.

According to the Irish Independent, the HSE said the attack was an isolated incident, with no sign of it having affected the wider healthcare network. “There has been no impact on patient care, and business continuity plans are in operation until the full system is restored,” the statement read, adding that it is working with the Data Protection Commissioner on a “cautionary basis”.

In May of last year, the HSE cautiously reopened its servers to the outside world after the hugely damaging WannaCry ransomware attacks spread globally. The HSE was lucky in that its systems were almost completely unaffected. However, fearing a similar situation to our nearest neighbour, it cut its systems off from the wider internet as a safety measure.

Facebook bug let websites read users’ private info

Facebook is once again in the midst of a PR nightmare, but it might have been missed last week that a bug found in its social network allowed websites to read the private information of users and their friends.

According to The Next Web, the discovery was made by security research firm Imperva in May and it has now been patched. Imperva said that in order to tap into the data, a website could embed an iframe to siphon off data from the user. When the Facebook user visited a website with the malicious code, the tool activated and began sending queries to Facebook to find out more personal information about the user.

Having been discovered when Imperva was looking for Chrome vulnerabilities, Facebook said it has “made recommendations to browser makers and relevant web standards groups to encourage them to take steps to prevent this type of issue from occurring in other web applications”.

Venezuela flag flying outside buildings. Image: jkraft5/Depositphotos

RELATED: CLOUD, ENTERPRISE DIGEST, BUGS, FACEBOOK, MALWARE, GOOGLE, BREACHES, INFOSEC

Colm Gorey is a journalist with Siliconrepublic.com

editorial@siliconrepublic.com