#Extract website data

[3idatascraping]

Web Data Scraping Services - Web Scraping Service Provider

3i Data is a Web Scraping Service Provider in the USA, India, UK, Canada, Germany, France, Israel, Australia, Spain, Singapore, and UAE. We offer web data scraping services for any website at competitive prices.

[foodspark-scraper]

Kroger Grocery Data Scraping | Kroger Grocery Data Extraction

Shopping Kroger grocery online has become very common these days. At Foodspark, we scrape Kroger grocery apps data online with our Kroger grocery data scraping API as well as also convert data to appropriate informational patterns and statistics.

[actowizsolutions0]

Lawyer Data Scraping Services: The Key to Smarter Legal Insights

In the legal industry, access to accurate and updated information is crucial. Whether you're a law firm, researcher, or legal analyst, having comprehensive data at your fingertips can significantly improve decision-making. This is where lawyer data scraping services come into play. These services help extract valuable legal data from various sources, streamlining research and enhancing efficiency.

Why Do You Need Lawyer Data Scraping?

Lawyer data scraping is an advanced technique used to collect information from legal directories, court databases, attorney profiles, and law firm websites. By leveraging this service, you can:

Gather details of legal professionals, including their expertise, contact information, and case history.

Monitor legal trends and analyze case outcomes.

Keep up with changes in law firm structures and attorney movements.

Automate data collection for legal marketing and research.

Key Benefits of Lawyer Data Scraping Services

1. Enhanced Legal Research

Scraping legal data provides easy access to case summaries, judgments, and court filings, allowing legal professionals to stay informed.

2. Competitor & Market Analysis

For law firms looking to stay ahead, scraping lawyer and firm data can offer insights into competitors’ activities, helping refine strategies.

3. Time & Cost Efficiency

Manual data extraction is time-consuming and prone to errors. Automated data scraping ensures accuracy while saving valuable time.

4. Improved Lead Generation

With access to attorney and law firm directories, firms can identify potential clients or partnerships, streamlining their outreach efforts.

Industries Benefiting from Lawyer Data Scraping

Legal Research Firms – Gain instant access to extensive case records.

Law Firms – Analyze competition, recruit talent, and monitor legal trends.

Marketing Agencies – Generate leads from attorney listings and legal networks.

Insurance Companies – Verify legal credentials and case histories.

Related Data Scraping Services

Actowiz Solutions offers a range of web scraping services beyond legal data extraction. Check out our other services:

Extract Stock & Finance Data – Stay ahead in financial markets with real-time data extraction.

Yellow Pages Data Scraping – Collect business leads from directories effortlessly.

Website Price Scraper – Monitor product prices across e-commerce platforms.

Web Scraping News Articles – Extract news updates for media analysis and trend tracking.

Get Started with Lawyer Data Scraping

If you’re looking for reliable and efficient lawyer data scraping services, Actowiz Solutions is here to help. Our cutting-edge tools ensure accurate data extraction tailored to your needs. Contact us today and transform the way you access legal data!

[harigsblog]

The Benefits of Data Extraction

Aggregating data from multiple sources provides a complete picture of business operations, aiding more informed decision-making. Unfortunately, extracting and consolidating this information can often be time-consuming manual processes with substantial risks involved.

Automated data extraction eliminates the need for manual data entry and reduces human error, providing many other benefits as well. Below are four of these advantages of automating data extraction.

Reduces Risk of Errors

Data extraction is an integral component of moving and consolidating data from disparate systems, helping reduce errors in resulting datasets, making them more reliable for analysis and decision-making. Errors often occur as a result of manual processes; for example, entering, editing, and reentering data increases opportunities for mistakes. Automated tools for data extraction eliminate these manual steps to reduce chances of error while increasing accuracy.

E-commerce retailers use data extraction techniques to track competitors' pricing data and adjust their own prices in real-time, to stay competitive and attract price-sensitive customers.

ETL processes can also be used to migrate data from documents, credentials, images and other unstructured sources into a database, making the ETL process invaluable for companies in all industries who must migrate legacy data from outdated programs and applications into modern ones. Furthermore, the ETL process can help streamline internal processes by merging information across departments or divisions.

Increases Productivity

Data extraction involves locating, connecting to, and collecting information from various systems. Businesses across all industries and sectors utilize this process in order to move information from external sources into their databases more quickly while also reviewing operations strategies, curating effective processes, and mitigating risks.

Data extraction helps increase data accessibility for those without access to source tools or an understanding of their formats, by validating and normalizing (flattening nested structures for instance).

Document workflow automation software is also an indispensable asset in automating end-to-end document processing workflows, helping businesses save both time and effort through automating manual tasks, freeing them up to devote resources towards high-risk projects with strategic goals. Furthermore, document automation increases productivity by freeing employees to focus on more important work such as personalizing customer services or faster resolving customer inquiries - increasing customer loyalty while creating revenue boosting opportunities that lead to revenue gains and profit gains.

Enhances Data Accessibility

Data extraction is the initial stage in extract, transform, and load (ETL) process that prepares enterprise data for analytics. It involves retrieving raw data from different sources like databases, legacy systems, online transaction platforms, software as a service (SaaS) tools or web scraping before moving it into a central repository such as a data warehouse for further transformation and transformation.

ETL processes are essential to companies looking to gain a competitive edge through data-driven decision making. But if data is scattered across different systems and formats, making it hard for employees to use effectively.

Automated data extraction enables business users to gain easy access to the information they require without depending on IT support, while simplifying processing massive datasets. Users have several extraction options available - full or incremental extraction saves both time and resources by only retrieving new or updated information from sources, while scheduling extraction processes at certain intervals or events ensures continuous updates are occurring without manual intervention or delays in updates.

Increases ROI

Data Extraction gives your business the power to compile information from various sources and convert it into an easily shareable format, giving employees access to vital data without waiting on IT assistance and increasing productivity and ROI.

No matter the purpose, businesses need accurate and complete data in order to thrive. By automating this process, errors can be eliminated while cutting down the time needed for data sourcing - freeing up team members so they can focus on tasks which need their expertise such as marketing campaigns or lead generation strategies - creating a more data-driven approach that results in tangible increases in revenue and customer engagement. Plus, using extraction tools you can also perform incremental extraction that only captures newly updated or new information instead of full snapshots, saving on processing and transfer costs as well.

[iwebscrapingblogs]

Vacation Rental Website Data Scraping | Scrape Vacation Rental Website Data

In the ever-evolving landscape of the vacation rental market, having access to real-time, accurate, and comprehensive data is crucial for businesses looking to gain a competitive edge. Whether you are a property manager, travel agency, or a startup in the hospitality industry, scraping data from vacation rental websites can provide you with invaluable insights. This blog delves into the concept of vacation rental website data scraping, its importance, and how it can be leveraged to enhance your business operations.

What is Vacation Rental Website Data Scraping?

Vacation rental website data scraping involves the automated extraction of data from vacation rental platforms such as Airbnb, Vrbo, Booking.com, and others. This data can include a wide range of information, such as property listings, pricing, availability, reviews, host details, and more. By using web scraping tools or services, businesses can collect this data on a large scale, allowing them to analyze trends, monitor competition, and make informed decisions.

Why is Data Scraping Important for the Vacation Rental Industry?

Competitive Pricing Analysis: One of the primary reasons businesses scrape vacation rental websites is to monitor pricing strategies used by competitors. By analyzing the pricing data of similar properties in the same location, you can adjust your rates to stay competitive or identify opportunities to increase your prices during peak seasons.

Market Trend Analysis: Data scraping allows you to track market trends over time. By analyzing historical data on bookings, occupancy rates, and customer preferences, you can identify emerging trends and adjust your business strategies accordingly. This insight can be particularly valuable for making decisions about property investments or marketing campaigns.

Inventory Management: For property managers and owners, understanding the supply side of the market is crucial. Scraping data on the number of available listings, their features, and their occupancy rates can help you optimize your inventory. For example, you can identify underperforming properties and take corrective actions such as renovations or targeted marketing.

Customer Sentiment Analysis: Reviews and ratings on vacation rental platforms provide a wealth of information about customer satisfaction. By scraping and analyzing this data, you can identify common pain points or areas where your service excels. This feedback can be used to improve your offerings and enhance the guest experience.

Lead Generation: For travel agencies or vacation rental startups, scraping contact details and other relevant information from vacation rental websites can help generate leads. This data can be used for targeted marketing campaigns, helping you reach potential customers who are already interested in vacation rentals.

Ethical Considerations and Legal Implications

While data scraping offers numerous benefits, it’s important to be aware of the ethical and legal implications. Vacation rental websites often have terms of service that prohibit or restrict scraping activities. Violating these terms can lead to legal consequences, including lawsuits or being banned from the platform. To mitigate risks, it’s advisable to:

Seek Permission: Whenever possible, seek permission from the website owner before scraping data. Some platforms offer APIs that provide access to data in a more controlled and legal manner.

Respect Robots.txt: Many websites use a robots.txt file to communicate which parts of the site can be crawled by web scrapers. Ensure your scraping activities respect these guidelines.

Use Data Responsibly: Avoid using scraped data in ways that could harm the website or its users, such as spamming or creating fake listings. Responsible use of data helps maintain ethical standards and builds trust with your audience.

How to Get Started with Vacation Rental Data Scraping

If you’re new to data scraping, here’s a simple guide to get you started:

Choose a Scraping Tool: There are various scraping tools available, ranging from easy-to-use platforms like Octoparse and ParseHub to more advanced solutions like Scrapy and Beautiful Soup. Choose a tool that matches your technical expertise and requirements.

Identify the Data You Need: Before you start scraping, clearly define the data points you need. This could include property details, pricing, availability, reviews, etc. Having a clear plan will make your scraping efforts more efficient.

Start Small: Begin with a small-scale scrape to test your setup and ensure that you’re collecting the data you need. Once you’re confident, you can scale up your scraping efforts.

Analyze the Data: After collecting the data, use analytical tools like Excel, Google Sheets, or more advanced platforms like Tableau or Power BI to analyze and visualize the data. This will help you derive actionable insights.

Stay Updated: The vacation rental market is dynamic, with prices and availability changing frequently. Regularly updating your scraped data ensures that your insights remain relevant and actionable.

Conclusion

Vacation rental website data scraping is a powerful tool that can provide businesses with a wealth of information to drive growth and innovation. From competitive pricing analysis to customer sentiment insights, the applications are vast. However, it’s essential to approach data scraping ethically and legally to avoid potential pitfalls. By leveraging the right tools and strategies, you can unlock valuable insights that give your business a competitive edge in the ever-evolving vacation rental market.

[webscreen-scraping]

You can get a huge number of products on Walmart. It uses big data analytics for deciding its planning and strategies. Things like the Free-shipping day approach, are sult of data scraping as well as big data analytics, etc. against Amazon Prime have worked very well for Walmart. Getting the product features is a hard job to do and Walmart is doing wonderfully well in that. At Web Screen Scraping, we scrape data from Walmart for managing pricing practices using Walmart’s pricing scraping by our Walmart data scraper.

[datascraping001]

Google Search Results Data Scraping

Google Search Results Data Scraping

Harness the Power of Information with Google Search Results Data Scraping Services by DataScrapingServices.com. In the digital age, information is king. For businesses, researchers, and marketing professionals, the ability to access and analyze data from Google search results can be a game-changer. However, manually sifting through search results to gather relevant data is not only time-consuming but also inefficient. DataScrapingServices.com offers cutting-edge Google Search Results Data Scraping services, enabling you to efficiently extract valuable information and transform it into actionable insights.

The vast amount of information available through Google search results can provide invaluable insights into market trends, competitor activities, customer behavior, and more. Whether you need data for SEO analysis, market research, or competitive intelligence, DataScrapingServices.com offers comprehensive data scraping services tailored to meet your specific needs. Our advanced scraping technology ensures you get accurate and up-to-date data, helping you stay ahead in your industry.

List of Data Fields

Our Google Search Results Data Scraping services can extract a wide range of data fields, ensuring you have all the information you need:

-Business Name: The name of the business or entity featured in the search result.

- URL: The web address of the search result.

- Website: The primary website of the business or entity.

- Phone Number: Contact phone number of the business.

- Email Address: Contact email address of the business.

 - Physical Address: The street address, city, state, and ZIP code of the business.

- Business Hours: Business operating hours

- Ratings and Reviews: Customer ratings and reviews for the business.

- Google Maps Link: Link to the business’s location on Google Maps.

- Social Media Profiles: LinkedIn, Twitter, Facebook

These data fields provide a comprehensive overview of the information available from Google search results, enabling businesses to gain valuable insights and make informed decisions.

Benefits of Google Search Results Data Scraping

1. Enhanced SEO Strategy

Understanding how your website ranks for specific keywords and phrases is crucial for effective SEO. Our data scraping services provide detailed insights into your current rankings, allowing you to identify opportunities for optimization and stay ahead of your competitors.

2. Competitive Analysis

Track your competitors’ online presence and strategies by analyzing their rankings, backlinks, and domain authority. This information helps you understand their strengths and weaknesses, enabling you to adjust your strategies accordingly.

3. Market Research

Access to comprehensive search result data allows you to identify trends, preferences, and behavior patterns in your target market. This information is invaluable for product development, marketing campaigns, and business strategy planning.

4. Content Development

By analyzing top-performing content in search results, you can gain insights into what types of content resonate with your audience. This helps you create more effective and engaging content that drives traffic and conversions.

5. Efficiency and Accuracy

Our automated scraping services ensure you get accurate and up-to-date data quickly, saving you time and resources.

Best Google Data Scraping Services

Scraping Google Business Reviews

Extract Restaurant Data From Google Maps

Google My Business Data Scraping

Google Shopping Products Scraping

Google News Extraction Services

Scrape Data From Google Maps

Google News Headline Extraction   

Google Maps Data Scraping Services

Google Map Businesses Data Scraping

Google Business Reviews Extraction

Best Google Search Results Data Scraping Services in USA

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

Conclusion

In today’s data-driven world, having access to detailed and accurate information from Google search results can give your business a significant edge. DataScrapingServices.com offers professional Google Search Results Data Scraping services designed to meet your unique needs. Whether you’re looking to enhance your SEO strategy, conduct market research, or gain competitive intelligence, our services provide the comprehensive data you need to succeed. Contact us at info@datascrapingservices.com today to learn how our data scraping solutions can transform your business strategy and drive growth.

Website: Datascrapingservices.com

Email: info@datascrapingservices.com

[mobiledatascrape]

OTT Media Platform Data Scraping | Extract Streaming App Data

Unlock insights with our OTT Media Platform Data Scraping. Extract streaming app data in the USA, UK, UAE, China, India, or Spain. Optimize your strategy today

know more: https://www.mobileappscraping.com/ott-media-app-scraping-services.php

[saywhat-politics]

Elon Musk's henchmen have reportedly installed a commercial server to control federal databases that contain Social Security numbers and other highly sensitive personal information.

The tech billionaire installed his associates — some of them fresh out of high school — in the Office of Personnel Management (OPM), where they have gained unprecedented access to federal human resources databases containing sensitive personal information for millions of federal workers, sources in the department told the website Musk Watch.

"According to two members of OPM staff with direct knowledge, the Musk team running OPM has the ability to extract information from databases that store medical histories, personally identifiable information, workplace evaluations, and other private data," wrote investigative reporters Caleb Ecarma and Judd Legum. "The arrangement presents acute privacy and security risks, one of the OPM staffers said."

[mostlysignssomeportents]

Pluralistic: Leaving Twitter had no effect on NPR's traffic

I'm coming to Minneapolis! This Sunday (Oct 15): Presenting The Internet Con at Moon Palace Books. Monday (Oct 16): Keynoting the 26th ACM Conference On Computer-Supported Cooperative Work and Social Computing.

Enshittification is the process by which a platform lures in and then captures end users (stage one), who serve as bait for business customers, who are also captured (stage two), whereupon the platform rug-pulls both groups and allocates all the value they generate and exchange to itself (stage three):

https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys

Enshittification isn't merely a form of rent-seeking – it is a uniquely digital phenomenon, because it relies on the inherent flexibility of digital systems. There are lots of intermediaries that want to extract surpluses from customers and suppliers – everyone from grocers to oil companies – but these can't be reconfigured in an eyeblink the that that purely digital services can.

A sleazy boss can hide their wage-theft with a bunch of confusing deductions to your paycheck. But when your boss is an app, it can engage in algorithmic wage discrimination, where your pay declines minutely every time you accept a job, but if you start to decline jobs, the app can raise the offer:

https://pluralistic.net/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men

I call this process "twiddling": tech platforms are equipped with a million knobs on their back-ends, and platform operators can endlessly twiddle those knobs, altering the business logic from moment to moment, turning the system into an endlessly shifting quagmire where neither users nor business customers can ever be sure whether they're getting a fair deal:

https://pluralistic.net/2023/02/19/twiddler/

Social media platforms are compulsive twiddlers. They use endless variation to lure in – and then lock in – publishers, with the goal of converting these standalone businesses into commodity suppliers who are dependent on the platform, who can then be charged rent to reach the users who asked to hear from them.

Facebook designed this playbook. First, it lured in end-users by promising them a good deal: "Unlike Myspace, which spies on you from asshole to appetite, Facebook is a privacy-respecting site that will never, ever spy on you. Simply sign up, tell us everyone who matters to you, and we'll populate a feed with everything they post for public consumption":

https://lawcat.berkeley.edu/record/1128876

The users came, and locked themselves in: when people gather in social spaces, they inadvertently take one another hostage. You joined Facebook because you liked the people who were there, then others joined because they liked you. Facebook can now make life worse for all of you without losing your business. You might hate Facebook, but you like each other, and the collective action problem of deciding when and whether to go, and where you should go next, is so difficult to overcome, that you all stay in a place that's getting progressively worse.

Once its users were locked in, Facebook turned to advertisers and said, "Remember when we told these rubes we'd never spy on them? It was a lie. We spy on them with every hour that God sends, and we'll sell you access to that data in the form of dirt-cheap targeted ads."

Then Facebook went to the publishers and said, "Remember when we told these suckers that we'd only show them the things they asked to see? Total lie. Post short excerpts from your content and links back to your websites and we'll nonconsensually cram them into the eyeballs of people who never asked to see them. It's a free, high-value traffic funnel for your own site, bringing monetizable users right to your door."

Now, Facebook had to find a way to lock in those publishers. To do this, it had to twiddle. By tiny increments, Facebook deprioritized publishers' content, forcing them to make their excerpts grew progressively longer. As with gig workers, the digital flexibility of Facebook gave it lots of leeway here. Some publishers sensed the excerpts they were being asked to post were a substitute for visiting their sites – and not an enticement – and drew down their posting to Facebook.

When that happened, Facebook could twiddle in the publisher's favor, giving them broader distribution for shorter excerpts, then, once the publisher returned to the platform, Facebook drew down their traffic unless they started posting longer pieces. Twiddling lets platforms play users and business-customers like a fish on a line, giving them slack when they fight, then reeling them in when they tire.

Once Facebook converted a publisher to a commodity supplier to the platform, it reeled the publishers in. First, it deprioritized publishers' posts when they had links back to the publisher's site (under the pretext of policing "clickbait" and "malicious links"). Then, it stopped showing publishers' content to their own subscribers, extorting them to pay to "boost" their posts in order to reach people who had explicitly asked to hear from them.

For users, this meant that their feeds were increasingly populated with payola-boosted content from advertisers and pay-to-play publishers who paid Facebook's Danegeld to reach them. A user will only spend so much time on Facebook, and every post that Facebook feeds that user from someone they want to hear from is a missed opportunity to show them a post from someone who'll pay to reach them.

Here, too, twiddling lets Facebook fine-tune its approach. If a user starts to wean themself off Facebook, the algorithm (TM) can put more content the user has asked to see in the feed. When the user's participation returns to higher levels, Facebook can draw down the share of desirable content again, replacing it with monetizable content. This is done minutely, behind the scenes, automatically, and quickly. In any shell game, the quickness of the hand deceives the eye.

This is the final stage of enshittification: withdrawing surpluses from end-users and business customers, leaving behind the minimum homeopathic quantum of value for each needed to keep them locked to the platform, generating value that can be extracted and diverted to platform shareholders.

But this is a brittle equilibrium to maintain. The difference between "God, I hate this place but I just can't leave it" and "Holy shit, this sucks, I'm outta here" is razor-thin. All it takes is one privacy scandal, one livestreamed mass-shooting, one whistleblower dump, and people bolt for the exits. This kicks off a death-spiral: as users and business customers leave, the platform's shareholders demand that they squeeze the remaining population harder to make up for the loss.

One reason this gambit worked so well is that it was a long con. Platform operators and their investors have been willing to throw away billions convincing end-users and business customers to lock themselves in until it was time for the pig-butchering to begin. They financed expensive forays into additional features and complementary products meant to increase user lock-in, raising the switching costs for users who were tempted to leave.

For example, Facebook's product manager for its "photos" product wrote to Mark Zuckerberg to lay out a strategy of enticing users into uploading valuable family photos to the platform in order to "make switching costs very high for users," who would have to throw away their precious memories as the price for leaving Facebook:

https://www.eff.org/deeplinks/2021/08/facebooks-secret-war-switching-costs

The platforms' patience paid off. Their slow ratchets operated so subtly that we barely noticed the squeeze, and when we did, they relaxed the pressure until we were lulled back into complacency. Long cons require a lot of prefrontal cortex, the executive function to exercise patience and restraint.

Which brings me to Elon Musk, a man who seems to have been born without a prefrontal cortex, who has repeatedly and publicly demonstrated that he lacks any restraint, patience or planning. Elon Musk's prefrontal cortical deficit resulted in his being forced to buy Twitter, and his every action since has betrayed an even graver inability to stop tripping over his own dick.

Where Zuckerberg played enshittification as a long game, Musk is bent on speedrunning it. He doesn't slice his users up with a subtle scalpel, he hacks away at them with a hatchet.

Musk inaugurated his reign by nonconsensually flipping every user to an algorithmic feed which was crammed with ads and posts from "verified" users whose blue ticks verified solely that they had $8 ($11 for iOS users). Where Facebook deployed substantial effort to enticing users who tired of eyeball-cramming feed decay by temporarily improving their feeds, Musk's Twitter actually overrode users' choice to switch back to a chronological feed by repeatedly flipping them back to more monetizable, algorithmic feeds.

Then came the squeeze on publishers. Musk's Twitter rolled out a bewildering array of "verification" ticks, each priced higher than the last, and publishers who refused to pay found their subscribers taken hostage, with Twitter downranking or shadowbanning their content unless they paid.

(Musk also squeezed advertisers, keeping the same high prices but reducing the quality of the offer by killing programs that kept advertisers' content from being published along Holocaust denial and open calls for genocide.)

Today, Musk continues to squeeze advertisers, publishers and users, and his hamfisted enticements to make up for these depredations are spectacularly bad, and even illegal, like offering advertisers a new kind of ad that isn't associated with any Twitter account, can't be blocked, and is not labeled as an ad:

https://www.wired.com/story/xs-sneaky-new-ads-might-be-illegal/

Of course, Musk has a compulsive bullshitter's contempt for the press, so he has far fewer enticements for them to stay. Quite the reverse: first, Musk removed headlines from link previews, rendering posts by publishers that went to their own sites into stock-art enigmas that generated no traffic:

https://www.theguardian.com/technology/2023/oct/05/x-twitter-strips-headlines-new-links-why-elon-musk

Then he jumped straight to the end-stage of enshittification by announcing that he would shadowban any newsmedia posts with links to sites other than Twitter, "because there is less time spent if people click away." Publishers were advised to "post content in long form on this platform":

https://mamot.fr/@pluralistic/111183068362793821

Where a canny enshittifier would have gestured at a gaslighting explanation ("we're shadowbanning posts with links because they might be malicious"), Musk busts out the motto of the Darth Vader MBA: "I am altering the deal, pray I don't alter it any further."

All this has the effect of highlighting just how little residual value there is on the platform for publishers, and tempts them to bolt for the exits. Six months ago, NPR lost all patience with Musk's shenanigans, and quit the service. Half a year later, they've revealed how low the switching cost for a major news outlet that leaves Twitter really are: NPR's traffic, post-Twitter, has declined by less than a single percentage point:

https://niemanreports.org/articles/npr-twitter-musk/

NPR's Twitter accounts had 8.7 million followers, but even six months ago, Musk's enshittification speedrun had drawn down NPR's ability to reach those users to a negligible level. The 8.7 million number was an illusion, a shell game Musk played on publishers like NPR in a bid to get them to buy a five-figure iridium checkmark or even a six-figure titanium one.

On Twitter, the true number of followers you have is effectively zero – not because Twitter users haven't explicitly instructed the service to show them your posts, but because every post in their feeds that they want to see is a post that no one can be charged to show them.

I've experienced this myself. Three and a half years ago, I left Boing Boing and started pluralistic.net, my cross-platform, open access, surveillance-free, daily newsletter and blog:

https://pluralistic.net/2023/02/19/drei-drei-drei/#now-we-are-three

Boing Boing had the good fortune to have attracted a sizable audience before the advent of siloed platforms, and a large portion of that audience came to the site directly, rather than following us on social media. I knew that, starting a new platform from scratch, I wouldn't have that luxury. My audience would come from social media, and it would be up to me to convert readers into people who followed me on platforms I controlled – where neither they nor I could be held to ransom.

I embraced a strategy called POSSE: Post Own Site, Syndicate Everywhere. With POSSE, the permalink and native habitat for your material is a site you control (in my case, a WordPress blog with all the telemetry, logging and surveillance disabled). Then you repost that content to other platforms – mostly social media – with links back to your own site:

https://indieweb.org/POSSE

There are a lot of automated tools to help you with this, but the platforms have gone to great lengths to break or neuter them. Musk's attack on Twitter's legendarily flexible and powerful API killed every automation tool that might help with this. I was lucky enough to have a reader – Loren Kohnfelder – who coded me some python scripts that automate much of the process, but POSSE remains a very labor-intensive and error-prone methodology:

https://pluralistic.net/2021/01/13/two-decades/#hfbd

And of all the feeds I produce – email, RSS, Discourse, Medium, Tumblr, Mastodon – none is as labor-intensive as Twitter's. It is an unforgiving medium to begin with, and Musk's drawdown of engineering support has made it wildly unreliable. Many's the time I've set up 20+ posts in a thread, only to have the browser tab reload itself and wipe out all my work.

But I stuck with Twitter, because I have a half-million followers, and to the extent that I reach them there, I can hope that they will follow the permalinks to Pluralistic proper and switch over to RSS, or email, or a daily visit to the blog.

But with each day, the case for using Twitter grows weaker. I get ten times as many replies and reposts on Mastodon, though my Mastodon follower count is a tenth the size of my (increasingly hypothetical) Twitter audience.

All this raises the question of what can or should be done about Twitter. One possible regulatory response would be to impose an "End-To-End" rule on the service, requiring that Twitter deliver posts from willing senders to willing receivers without interfering in them. End-To-end is the bedrock of the internet (one of its incarnations is Net Neutrality) and it's a proven counterenshittificatory force:

https://www.eff.org/deeplinks/2023/06/save-news-we-need-end-end-web

Despite what you may have heard, "freedom of reach" is freedom of speech: when a platform interposes itself between willing speakers and their willing audiences, it arrogates to itself the power to control what we're allowed to say and who is allowed to hear us:

https://pluralistic.net/2022/12/10/e2e/#the-censors-pen

We have a wide variety of tools to make a rule like this stick. For one thing, Musk's Twitter has violated innumerable laws and consent decrees in the US, Canada and the EU, which creates a space for regulators to impose "conduct remedies" on the company.

But there's also existing regulatory authorities, like the FTC's Section Five powers, which enable the agency to act against companies that engage in "unfair and deceptive" acts. When Twitter asks you who you want to hear from, then refuses to deliver their posts to you unless they pay a bribe, that's both "unfair and deceptive":

https://pluralistic.net/2023/01/10/the-courage-to-govern/#whos-in-charge

But that's only a stopgap. The problem with Twitter isn't that this important service is run by the wrong mercurial, mediocre billionaire: it's that hundreds of millions of people are at the mercy of any foolish corporate leader. While there's a short-term case for improving the platforms, our long-term strategy should be evacuating them:

https://pluralistic.net/2023/07/18/urban-wildlife-interface/#combustible-walled-gardens

To make that a reality, we could also impose a "Right To Exit" on the platforms. This would be an interoperability rule that would require Twitter to adopt Mastodon's approach to server-hopping: click a link to export the list of everyone who follows you on one server, click another link to upload that file to another server, and all your followers and followees are relocated to your new digs:

https://pluralistic.net/2022/12/23/semipermeable-membranes/#free-as-in-puppies

A Twitter with the Right To Exit would exert a powerful discipline even on the stunted self-regulatory centers of Elon Musk's brain. If he banned a reporter for publishing truthful coverage that cast him in a bad light, that reporter would have the legal right to move to another platform, and continue to reach the people who follow them on Twitter. Publishers aghast at having the headlines removed from their Twitter posts could go somewhere less slipshod and still reach the people who want to hear from them on Twitter.

And both Right To Exit and End-To-End satisfy the two prime tests for sound internet regulation: first, they are easy to administer. If you want to know whether Musk is permitting harassment on his platform, you have to agree on a definition of harassment, determine whether a given act meets that definition, and then investigate whether Twitter took reasonable steps to prevent it.

By contrast, administering End-To-End merely requires that you post something and see if your followers receive it. Administering Right To Exit is as simple as saying, "OK, Twitter, I know you say you gave Cory his follower and followee file, but he says he never got it. Just send him another copy, and this time, CC the regulator so we can verify that it arrived."

Beyond administration, there's the cost of compliance. Requiring Twitter to police its users' conduct also requires it to hire an army of moderators – something that Elon Musk might be able to afford, but community-supported, small federated servers couldn't. A tech regulation can easily become a barrier to entry, blocking better competitors who might replace the company whose conduct spurred the regulation in the first place.

End-to-End does not present this kind of barrier. The default state for a social media platform is to deliver posts from accounts to their followers. Interfering with End-To-End costs more than delivering the messages users want to have. Likewise, a Right To Exit is a solved problem, built into the open Mastodon protocol, itself built atop the open ActivityPub standard.

It's not just Twitter. Every platform is consuming itself in an orgy of enshittification. This is the Great Enshittening, a moment of universal, end-stage platform decay. As the platforms burn, calls to address the fires grow louder and harder for policymakers to resist. But not all solutions to platform decay are created equal. Some solutions will perversely enshrine the dominance of platforms, help make them both too big to fail and too big to jail.

Musk has flagrantly violated so many rules, laws and consent decrees that he has accidentally turned Twitter into the perfect starting point for a program of platform reform and platform evacuation.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/10/14/freedom-of-reach/#ex

My next novel is The Lost Cause, a hopeful novel of the climate emergency. Amazon won't sell the audiobook, so I made my own and I'm pre-selling it on Kickstarter!

Image: JD Lasica (modified) https://commons.wikimedia.org/wiki/File:Elon_Musk_%283018710552%29.jpg

CC BY 2.0 https://creativecommons.org/licenses/by/2.0/deed.en

[dostoyevsky-official]

Georgia to purchase Israeli data extraction tech amid street protest crackdown

Georgia has moved to renew contracts with Israeli technology firm Cellebrite DI Ltd (CLBT.O) for software used to extract data from mobile devices, procurement documents show, as the country grapples with ongoing anti-government street protests. [...] The software, called Inseyets, allows law enforcement to "access locked devices to lawfully extract critical information from a broad range of devices", Cellebrite's website says. Cellebrite products are widely used by law enforcement, including the FBI, to unlock smartphones and scour them for evidence. [...] Georgia was plunged into political crisis in October, when opposition parties charged the ruling Georgian Dream party with rigging a parliamentary election. GD, in power since 2012, denies any wrongdoing. Georgians have been rallying nightly to demand the government's resignation since GD said in November it was suspending European Union accession talks until 2028. The demonstrations have drawn a swift crackdown by police, resulting in hundreds of arrests and beatings, rights groups say. The government has defended the police response to the protests. Gangs of masked men in black have attacked opposition politicians, activists and some journalists in recent months, raising alarm in Western capitals. Georgian authorities have said they are not involved in the attacks, and condemn them. A letter dated February 13 included among the documents on the state procurement website suggests Cellebrite was concerned about its sales to Georgia. A Cellebrite sales director, writing to a Georgian interior ministry official on what he called a "sensitive issue", warned Cellebrite's local office "could be blocked from selling our equipment". "Therefore, I would like to advise you that if you are planning a purchase this year, please try to make it as early as possible," the employee wrote, without specifying why sales might be halted.

wherever a brutal government consolidates itself, israel shows up

[3idatascraping]

Extracting Shopify product data efficiently can give your business a competitive edge. In just a few minutes, you can gather essential information such as product names, prices, descriptions, and inventory levels. Start by using web scraping tools like Python with libraries such as BeautifulSoup or Scrapy, which allow you to automate the data collection process. Alternatively, consider using user-friendly no-code platforms that simplify the extraction without programming knowledge. This valuable data can help inform pricing strategies, product listings, and inventory management, ultimately driving your eCommerce success.

[foodspark-scraper]

Web Data Extraction: Scraping Data from a Website's Store Locator

When competing with large corporations in your field, it can be challenging to find an edge. But one way to gain a competitive advantage is by knowing how to scrape data from a website's store locator. One of the best ways to compete against larger companies is to understand how to scrape data from a website's store locator . It is a primary business. You're trying to find a way to keep costs down so that you can be competitive. This might be through outsourcing physical goods production overseas or working with local suppliers who can provide enough volume for cost savings.

Even if you don't perform a lot of manufacturing, there are still methods for you to benefit from effective data scrapers for your store locator services, allowing you to save expenses while maximizing revenues. This post will review how to scrape data from a website's store locator. We'll discuss how to get the most out of your internet store locator and make it work like a machine.

What is data scraping, and how does it help businesses?

Data mining is the process of collecting data and organizing it in a way that offers beneficial results. In the case of a website's store locator, the data can be used in many ways for maximum profit.

When scraping data for your store locator, you pull a lot of information from one source. When this source is a website, this is known as web crawling. You only have to make multiple visits to each page to collect all of this information if you want to view it in detail or compare it with other pages like your competitors'. The information you collect is used to organize your business in a database. It can then be exported into other programs that can be used for marketing purposes.

It is suitable for businesses to organize their data to better hone in on the most profitable markets and potential customers. If you could manage this data from multiple sources, you may be spending more time reading through it all instead of organizing it and analyzing it cost-effectively.

[botgal]

Update on AB 3080 and AB 1949

AB 3080 (age verification for adult websites and online purchase of products and services not allowed for minors) and AB 1949 (prohibiting data collection on individuals less than 18 years of age) both officially have hearing dates for the California Senate Judiciary Committee.

The hearing date for these bills is scheduled to be Tuesday 07/02/2024. Which means that the deadline to turn in position letters is going to be noon one week before the hearing on 06/25/2024. It's not a lot of time from this moment, but I'm certain we can each turn one in before then

Remember that position letters should be single topic, in strict opposition of what each bill entails. Keep on topic and professional when writing them. Let us all do our best to keep these bills from leaving committee so that we don't have to fight them on the Senate floor. But let's also not stop sending correspondence to our state representatives anyway.

Remember, the jurisdiction of the Senate Judiciary Committee is as follows.

"Bills amending the Civil Code, Code of Civil Procedure, Evidence Code, Family Code, and Probate Code. Bills relating to courts, judges, and court personnel. Bills relating to liens, claims, and unclaimed property. Bills relating to privacy and consumer protection."

Best of luck everyone. And thank you for your efforts to fight this so far.

Below is linked the latest versions of the bills.

Below are the links to the Committee's homepage which gives further information about the Judiciary Committee, and the page explaining further in depth their letter policy.

Edit: Was requested to add in information such as why these bills are bad and what sites could potentially be affected by these bills. So here's the explanation I gave in asks.

Why are these bills bad?

Both bills are essentially age verification requirement laws. AB 3080 explicitly, and AB 1949 implicitly.

AB 3080 strictly is calling for dangerous age verification requirements for both adult websites and any website which sells products or services which it is illegal for minors to access in California. While this may sound like a good idea on paper, it's important to keep in mind that any information that's put online is at risk of being extracted and used by bad actors like hackers. Even if there are additional requirements by the law that data be deleted after its used for its intended purpose and that it not be used to trace what websites people access. The former of which provides very little protection from people who could access the databases of identification that are used for verification, and the latter which is frankly impossible to completely enforce and could at any time reasonably be used by the government or any surveying entity to see what private citizens have been looking at since their ID would be linked to the access and not anonymized.

AB 1949 is nominally to protect children from having their data collected and sold without permission on websites. However by restricting this with an age limit it opens up similar issues wherein it could cause default requirements for age verification for any website so that they can avoid liability by users and the state.

What websites could they affect?

AB 3080, according to the bill's text, would affect websites which sells the types of items listed below

"

(b) Products or services that are illegal to sell to a minor under state law that are subject to subdivision (a) include all of the following:

(1) An aerosol container of paint that is capable of defacing property, as referenced in Section 594.1 of the Penal Code.

(2) Etching cream that is capable of defacing property, as referenced in Section 594.1 of the Penal Code.

(3) Dangerous fireworks, as referenced in Sections 12505 and 12689 of the Health and Safety Code.

(4) Tanning in an ultraviolet tanning device, as referenced in Sections 22702 and 22706 of the Business and Professions Code.

(5) Dietary supplement products containing ephedrine group alkaloids, as referenced in Section 110423.2 of the Health and Safety Code.

(6) Body branding, as referenced in Sections 119301 and 119302 of the Health and Safety Code.

(c) Products or services that are illegal to sell to a minor under state law that are subject to subdivision (a) include all of the following:

(1) Firearms or handguns, as referenced in Sections 16520, 16640, and 27505 of the Penal Code.

(2) A BB device, as referenced in Sections 16250 and 19910 of the Penal Code.

(3) Ammunition or reloaded ammunition, as referenced in Sections 16150 and 30300 of the Penal Code.

(4) Any tobacco, cigarette, cigarette papers, blunt wraps, any other preparation of tobacco, any other instrument or paraphernalia that is designed for the smoking or ingestion of tobacco, products prepared from tobacco, or any controlled substance, as referenced in Division 8.5 (commencing with Section 22950) of the Business and Professions Code, and Sections 308, 308.1, 308.2, and 308.3 of the Penal Code.

(5) Electronic cigarettes, as referenced in Section 119406 of the Health and Safety Code.

(6) A less lethal weapon, as referenced in Sections 16780 and 19405 of the Penal Code."

This is stated explicitly to include "internet website on which the owner of the internet website, for commercial gain, knowingly publishes sexually explicit content that, on an annual basis, exceeds one-third of the contents published on the internet website". Wherein "sexually explicit content" is defined as "visual imagery of an individual or individuals engaging in an act of masturbation, sexual intercourse, oral copulation, or other overtly sexual conduct that, taken as a whole, lacks serious literary, artistic, political, or scientific value."

This would likely not include websites like AO3 or any website which displays NSFW content not in excess of 1/3 of the content on the site. Possibly not inclusive of writing because of the "visual imagery", but don't know at this time. In any case we don't want to set a precedent off of which it could springboard into non-commercial websites or any and all places with NSFW content.

AB 1949 is a lot more broad because it's about general data collection by any and all websites in which they might sell personal data collected by the website to third parties, especially if aimed specifically at minors or has a high chance of minors commonly accesses the site. But with how broad the language is I can't say there would be ANY limits to this one. So both are equally bad and would require equal attention in my opinion.

[iwebscrapingblogs]

Follow the list of 10 websites for web scraping. You will get an overview of what to scrape for the best results. We’ve shared the list based on categories.

For More Information:-

[webscreen-scraping]

Collecting seller and quantity related data may provide the finest leads for you Web Screen Scraping offers Best Walmart Product Data Scraping Services.