No. This is just data mining on lonely people.

Ick, man. This is exactly what so many of us have feared

How ICE is watching you • Minnesota Reformer

So you’re telling me the internet makes obscene amounts of money mining our data for free, and now we have to pay every year just to delete it and cloak our existence, because no one will regulate meaningful protections for people?

These sites aren’t even the problem. They’re trying to help. But the workers doing this should be publicly or charitably funded, because this situation was imposed on all of us in the first place. Instead, we’re forced to pay out of pocket for what should be a fundamental right.

Capitalism at its finest. 🙃

Important job hunting information for USians. Comments are worth skimming through as well for other services that HR depts use.

That is what happens when you do not use human oversight and instead rely on AI to datamine it for you. Now they slap on guardrails and programs to make it safer and it ends up making it worse. The filth was already on the internet. They did not remove it like NLP’s mostly tried to do in the past.

We live in a world where we have greater access to technology than we do food and shelter.

Logan: I want us into data mining. Buy it.
Kendall: It’s a really flooded sector. Lots of hustlers, lots of bullshit. It’s a gold rush.
Logan: Oh yeah. And who wants gold?

Two Chrome Extensions Caught Secretly Stealing Credentials from Over 170 Sites

Put differently, the extension captures passwords, credit card numbers, authentication cookies, browsing history, form data, API keys, and access tokens from users accessing the targeted domains while VIP mode is active. What’s more, the theft of developer secrets could pave the way for supply chain attacks.

I am waiting for the big reveal that the new rules for non-American tourists coming into the US, that is, they must hand over five years of social media data, e-mail addresses, telephone numbers and information about their family, to be not about “weeding out un-American” people like they claim but about gathering data for corporations in order to advertise to you.

I know, I know, people are saying that they want the data because they are a fascist state. This is all Big Brother. But hear me out and take a step back with me. Who is in charge of this administration? A CEO who runs his own corporation. Who does he surround himself with? Other CEOs who run their own corporations. Who are his bigger donors and backers? Yes, you guessed it. CEOs who run their own corporations.

And what do they want the most from you besides your money? Your data in order to sell you stuff which will end with them getting your money.

So many of these non-American tourists have no idea of the advertising glut we have in this country. How hundreds of ads come across our eyeballs and ears every day. They don’t know this because they don’t have this problem in their country. Their government has stronger consumer protection laws than we do. Their government prevents corporations from turning their countries into a 24/7 advertising landscape like the way the US has become.

Thing is, corporations hate this. Think about all of those potential customers with heavy wallets out there. Blocked by their own countries. For example, Americans, you know how we are buried in pharmaceutical ads blasting everywhere? This doesn’t happen in the majority of other countries because such ads have been declared illegal. Imagine how these laws must burn Big Pharma. All that money blocked.

Now one way around these laws would be to demand everyone’s data as they come in as tourists. Then take that data and hand it over to the corporations that have backed this administration. Or to at least sell it to them. Now you don’t need to air television commercials for your drugs. You can get to them through their own email. You can wallpaper their social media accounts with ads personalized just for them using the data you have collected on them.

I want to follow the people whose data has been taken and see in a year’s time if they find themselves suddenly spammed with ads on a level they have never seen before and how specific are those ads for them.

Why Businesses Need Data Mining and Big Data Analytics: Opportunities and Use-Cases

In today’s competitive landscape, organizations rely heavily on data-driven decision making. With the explosion of digital information, Data Mining and Big Data Analytics have become essential for businesses aiming to understand customer behaviour, enhance operational performance, and stay ahead of competitors. Companies that invest in Data Analysis Services not only gain deeper insights but also unlock new growth opportunities.

What Is Data Mining and Why Does It Matter?

Data Mining is the process of extracting meaningful patterns from large datasets. It identifies hidden trends, correlations, and anomalies that traditional analysis methods often overlook.
From predicting consumer interests to detecting business risks, data mining helps organizations turn raw data into actionable intelligence.

Businesses increasingly rely on professional Business Analytics Services to handle data complexity and ensure accurate insights for strategic decisions.

Understanding Big Data Analytics

Big Data Analytics focuses on processing massive, complex datasets generated through digital interactions, social media, transactions, IoT devices, and more.
With the support of Advanced Data Analysis and modern Data Engineering, companies can analyse high-volume, high-velocity data to gain real-time insights.

Big data technologies empower organizations to:

• Forecast future trends
• Personalize customer experiences
• Optimize workflows
• Improve market competitiveness

Why Businesses Need Data Mining & Big Data Analytics

1. Better Decision-Making with Real-Time Insights

With Big Data Analytics, businesses gain the ability to spot trends instantly. This helps leaders make accurate decisions based on facts rather than assumptions.
Industries such as retail, finance, and healthcare depend heavily on Predictive Analytics to manage risks and allocate resources efficiently.

2. Understanding Customer Behaviour

Data mining tools reveal buying patterns, preferences, and engagement levels.
Using these insights, brands can:

• Launch personalized marketing campaigns
• Improve user experience
• Increase customer loyalty

This is especially beneficial for e-commerce and service-based industries looking to enhance targeting strategies.

3. Enhanced Operational Efficiency

Companies use Big Data Analytics to identify inefficiencies, control waste, and streamline internal processes.
For example:

• Logistics companies optimize delivery routes
• Manufacturers detect equipment failures early
• Retailers improve inventory management

These operational improvements translate into reduced costs and increased productivity.

4. Fraud Detection and Risk Management

Financial institutions and online platforms rely on Data Mining to identify unusual activities, suspicious transactions, or fraud attempts.
By analysing patterns and anomalies, businesses can reduce risks and strengthen security systems.

5. Personalized Employee & Customer Experiences

Big data enables organizations to personalize experiences for both customers and employees.
By analysing behavioural data, companies can:

• Improve HR decision-making
• Enhance customer support
• Deliver custom product recommendations

This boost both satisfaction and retention.

Industry-Specific Use Cases

Retail & E-Commerce

• Market basket analysis
• Price optimization
• Customer segmentation
• Inventory forecasting

Healthcare

• Predictive diagnostics
• Patient trend analysis
• Resource planning
• Personalized treatment recommendations

Finance & Banking

• Fraud detection
• Credit scoring
• Market forecasting
• Risk modeling

Manufacturing

• Predictive maintenance
• Quality control
• Supply chain optimization
• Cost reduction

Marketing & Advertising

• Consumer behaviour prediction
• Campaign performance analysis
• Lead scoring
• Cross-channel analytics

How Outsourcing Helps: Role of Professional Data Analysis Services

Businesses often lack in-house expertise, tools, or time to manage complex datasets.
Partnering with a specialized provider like Statswork offers:

• Accurate data modelling
• Expert-driven analytical insights
• Scalable analytics solutions
• Data engineering and pre-processing support
• Secure and confidential analysis

This ensures faster turnaround, improved accuracy, and cost savings.

Conclusion

Data Mining and Big Data Analytics are no longer optional—they are vital drivers of business transformation. Organizations that embrace these technologies enjoy better forecasting, smoother operations, improved customer experiences, and stronger competitive advantage.
As data continues to grow exponentially, adopting expert-led Data Analysis Services ensures that businesses remain relevant, resilient, and ready for the future.

Day 2 Thanksgiving Fuel Insights (28th Nov 2025)

Part 3 of our 6-report Thanksgiving Fuel Series, published across Thursday, Friday, and Sunday.

Fuel prices continue to show a steady momentum into Day 2, but early-morning fuel behavior across major U.S. metros reflects a smoother and more stable start compared to yesterday. Most cities are showing slightly softer Morning averages, indicating a calm reset from Day 1’s holiday-driven volatility rather than new upward pressure.

Tourism-heavy metros like Orlando, Miami/FLL, Las Vegas, Los Angeles, and Phoenix still hold firm pricing, but nearly all posted small dips versus yesterday’s Morning snapshot. Northeastern hubs such as NYC, Philadelphia, and Boston show minimal movement, pointing to steady early travel flow. Texas metros and Chicago/Denver likewise open Day 2 with mild easing and stabilized demand.

This update provides near real-time Morning fuel averages across key Thanksgiving travel cities and highlights how Day 2 is trending versus Day 1 based on actual pricing shifts.

 City-Level Morning Fuel Price Snapshot (28th Nov 2025 — Day 2)

Below are the near real-time Morning averages across the highest-movement Thanksgiving travel cities:

 Day 1 → Day 2 Morning Shift

Most high-travel cities show a mild [rise/drop] in Morning averages.

Florida metros (Orlando, Miami/FLL, Tampa), along with Las Vegas and California cities, continue to hold firmer levels vs Day 1.

Northeastern metros (NYC, Philadelphia, Boston, D.C.) show lighter early-morning movement, signaling steadier flow into Day 2.

Texas metros (Dallas/Fort Worth, Houston) maintain strong early-day demand, similar to Day 1.

Chicago and Denver show moderate stabilization after yesterday’s volatility.

 Key Morning Movements (Day 2 — 2025)

• Tourism-heavy metros — Orlando, Miami/FLL, Las Vegas, Los Angeles, and Phoenix  continue to post firm Morning levels but generally slightly lower than Day 1, signaling steady demand without fresh upward pressure.
• California cities (L.A. and San Francisco) remain elevated but show subtle early-day softening, matching the national downtrend.
• Northeastern hubs (NYC, Philadelphia, Boston) recorded only marginal shifts, highlighting a smooth Day 2 start with less congestion-driven pricing.
• Texas metros (Dallas/Fort Worth, Houston) show mild declines yet maintain steady corridor movement tied to long-haul travel patterns.
• Midwest & Mountain metros (Chicago, Denver) opened with controlled pricing, reflecting a stabilized demand curve after Day 1 volatility.
• Overall, nearly all cities display micro-movements, indicating softer early pressure and a more balanced travel environment.

 Bottom Line

Day 2 opens with steadier and softer Morning pricing across most major Thanksgiving metros, reflecting a calm reset from Day 1’s higher travel intensity. While demand remains active in tourist and corridor-heavy cities, overall volatility is down, and early-day fuel behavior is more controlled heading into the remainder of the travel weekend.

 Ending Note

We’ll continue tracking real-time movement through the day.
Part 4 (Evening Update) drops later today.

For more fuel intelligence, deeper city dashboards, and tailored insights, connect with us.

Awareness. Listen to the whole thing along with what’s stated about the fact check.

Kaina’s interactions with civilians (EN)

Source

Previous post with all her MHUR lines

Previous post with her interaction lines in MHUR

Previous post with her out of battle lines

Unused MHUR voice lines

I regret I can’t reblog comments to reply to them in a post
Anyway, @lioma-art, addressing your assumption regarding MHUR voice lines, you seem to be right about unreleased or postponed seasonal events

UPD: for clarity, we were discussing the following unused Chisaki’s lines:

Source: this particular pic was posted by my X buddy ike, and full (and outdated) dump of Kai’s lines including the ones above, is here

First, here are lines on the same position as Chisaki’s about bringing sakura to Pops:

Most of them about spring and flowers

Next, lines on the same position as Chisaki’s about enjoying the nature:

It’s clearly about the autumn

Next, the one about unpleasant heat, most of the same positioned lines are about summer:

And last but not least, winter lines accompanied by Chisaki’s about making mochi:

This way, we have a small pack of seasonal lines, and I bet, I’ve never seen anyone mentioned them in this context before.
So it’s a great discovery, and thank you a lot for raising this topic and pushing it in a right direction 🙏

If you would like to, I can format in a way that it’s clear what line belongs to whom

It has been said that ChatGPT may use conversational data to improve the model and it is the default setting unless you opt out.

My suggestion is either opt out, or use another model entirely with better privacy safeguards.

Now, ideally you wouldn’t be sharing personal information with an AI to begin with, but some people do, so it’s worthwhile that you should be aware what’s done with data.

The Role of Web Scraping in Competitive E-commerce Intelligence

Introduction

Every day, e-commerce companies must compete against one another. Prices frequently fluctuate by the hour. Competitors can announce products without notice. Consumers often change their preferences in seconds. With that in mind, to remain competitive, businesses must keep on the pulse of the market using up-to-the-second market intelligence. More specifically, this is why e-commerce businesses must use web scraping to stay ahead of the competition.

Web scraping refers to the automated method of scraping public information from web pages. E-commerce companies utilize web scraping to monitor competitor products and pricing, and to gather an understanding of market flow. Professional data scraping companies such as 3i Data Scraping provide valuable services to help businesses scrape data, and also convert that scraped data into something that can provide businesses with intelligence.

Understanding Web Scraping for E-commerce

Web scraping entails the use of automated tools to sort through web pages, identify specific data, extract that data within the tools, and store that extracted data into usable formats. In the case of e-commerce, web scraping can be a process of extracting information about competitors’ products, prices, reviews, and inventory items from countless competitor e-commerce websites.

However, human data collection cannot compete in speed and scale with what is needed today in e-commerce. A single analyst could check 50 product prices a day, while scraping tools can check thousands of products across dozens of competitors every hour. The difference in scale is an important and significant competitive advantage.

The scraping technology sends requests to web servers and downloads the HTML from the web page. The scraping technology would then process the downloaded HTML to extract specific data points. Advanced scraping solutions like 3i Data Scraping use more advanced techniques to accomplish web scraping through complex websites and dynamic content. Advanced scraping solutions can even scrape data that is leveraging anti-scraping technologies.

Related: Web Scraping vs Manual Data Collection: Which is Better?

Key Applications of Web Scraping in Competitive Intelligence

In such a competitive industry, every choice matters; the difference between being ahead or behind your competitors usually comes down to being informed in real-time with actual data.

Real-time Pricing Strategy

Using web scraping, companies can track pricing on all competitors in near real-time. Retailers can now see when a competitor has raised or lowered their price or found a promotion or discount price. This gives businesses the intelligence to act in almost real-time, rather than days later when they find out about a price change.

Also, when businesses have historical pricing data, they are able to recognize patterns. Competitors will often have predictable cycles around dates like holidays, product launches, or certain seasons. 3i Data Scraping provides businesses with the ability to build these historical databases to help predict prices on the market in the future.

Analysis of Product Assortment

It is just as important to know what your competitors sell as it is to know how much they are selling it for. An analysis of the product assortment can put you onto products that are missing from your catalog or identify potential hot-selling items.

The process of web scraping can extract wholesale product assortments from your competitors’ websites. Your business can then look to see what products they are adding, breaking stocks on, categories that are important to their overall assortment, and what products occupy valuable or prime marketing space on the website. This is extremely valuable intel as it will inform your inventory position and product sourcing position.

Additionally, once you have scraped product descriptions and specifications, you can look for opportunities to differentiate your product. If your competitors have similar products with nearly exactly the same product descriptions, you can look to serve your customer a more intriguing value proposition through clearly designated product content and bundling the product in some way.

Review and Sentiment Monitoring

A review is a treasure trove of intelligence about the market, feedback, and most importantly, unmet customer needs. Reviews can expose product weaknesses, strengths, unmet needs for improvement, and emerging trends. However, manually gathering reviews across platforms is extremely time-consuming and cost-prohibitive!

Web scraping works to collect and scrape reviews directly from competitor product pages, marketplace platforms, and social proof review aggregate platforms. 3i Data Scraping can leverage review scraping functionality and insight in sentiment analysis to help you understand the reviews.

Analyzing Inventory and Stock Status

Stock availability can be a signal of the strength of demand and the efficiency of a supply chain. When competitors are frequently out of stock, demand is strong, or there is a supply issue. When a stock is persistently available, it may indicate there is weak selling or issues of overstock.

By scraping inventory status, businesses can identify potential opportunities. If a popular product is out of stock with major competitors, capture that unmet demand by increasing your marketing spend and getting a jump on the sales. Additionally, if you track restocking based on scraping lumber product inventory, you can predict the supply chain cycle of the competitor.

MAP Compliance Monitoring

Brands that operate through multiple sales channels must enforce their Minimum Advertised Price policy (MAP). Unauthorized sellers (those that do not have a direct wholesale relationship with the brand) often violate MAP compliance and which undermines brand value and adds pricing confusion to the marketplace.

For brands, scraping available inventory status can help identify violations of MAP pricing through a marketplace, unauthorized retailer or third-party sellers. Once that violation is identified, brands can get out in front and take action against delinquent sellers before their pricing starts to confuse consumers, and to bring the relevant stakeholders back into compliance. 3i Data Scraping offers fully customized MAP solutions. We are able to scrape thousands of sellers simultaneously, and report on the related data, including prices, flagging non-compliant sellers, etc.

With the right data scraping strategy, businesses can be one step ahead by forecasting changes, recognizing niche opportunities and gaining control in a rapidly changing environment. 3i Data Scraping provides brands with actionable insights for better strategy, better insights and better outcomes for their businesses.

The Technical Edge of Professional Scraping Solutions

Under the smooth competitive intelligence lies a difficult technical process that is often overlooked by many businesses. Today’s websites are dynamic, heavy in data, and protected, which makes it very difficult to get a reliable extraction of data. This is where professional scraping solutions really outshine – they combine advanced infrastructure, automation, and compliance skills to extract clean, verified, usable data that businesses can actually trust to use.

Dealing with Complex Website Technology

Modern e-commerce sites utilize complex technologies that load dynamic content through JavaScript, infinite scroll actions and protect their data through multiple security features. Basic scraping solutions will often fail against these challenges.

Professional scraping service providers such as 3i Data Scraping utilize advanced technology and techniques to deal with these challenges. They use headless browsers to render JavaScript, intelligent scrolling algorithms, and rotating IP addresses to ensure detection and consistent data is retrieved, among many others.

Scale and Speed

Competitive Intelligence efforts uncover thousands of products across potentially hundreds of competitors. Internal teams cannot scale internally to monitor such bandwidth of competitive intelligence.

Professional scraping solutions leverage widespread, distributed infrastructure and teams to compile millions of graphic and numeric data points, on a daily basis.  Professional scraping implementations can process such amounts and deliver the output in formats easily consumable by business intelligence tools.

Data Quality and Precision

Data from web scraping is rarely pristine. There are often errors, mistakes, and inconsistencies, as well as a lack of formatting. Product names may have superfluous characters. Prices may be represented in myriad ways. Links to images may only point at placeholder graphics.

Quality data scraping services employ data cleansing pipelines during the scraping. They can standardize data formats, eliminate duplicates, validate accuracy, and mark errors. This allows companies the ability to make data-based decisions without being misled by worthless data.

Legal and Ethical Considerations

The web scraping profession exists in an environment rife with confusion in relation to legal compliance. From a general perspective, scraping publicly available data is legally permissible. However, companies must do so with respect to robots.txt files, terms of service, and many data protection laws.

Professionally managed companies such as 3i Data Scraping are who understand the legal improvements related to web scraping. They have established network acquisition, ethical web scraping methods that is aligned with their technical standards and will respect the website’s policy as well as the relative local compliance requirements. These actions will protect the scraping companies from unnecessary legal risks as well.

Implementing Competitive Intelligence Programs

Defining Intelligence Requirements

The best scraping initiatives start with well-defined objectives. Companies should consider which competitors to observe, which data points are most meaningful, and how often updates are necessary.

The frequency of updates for pricing intelligence can range from hourly for quickly changing categories to daily or weekly for product catalog monitoring. By articulating the intelligence needs, there can be a more efficient allocation of resources.

Choosing the Right Data Points

Data points from web scraping do not all provide equal value. Companies should be focused on specific metrics that will improve decision-making. Common data points from scraping are:

• Current prices and promotional pricing.
• Product availability and inventory levels.
• Shipping costs and delivery timelines.
• Customer ratings and review counts.
• Product specifications and features.
• Search results and category ranking

3i Data Scraping engages at the beginning to determine the most valuable data points within its competitive landscape.

Integration with Business Processes

Scraped data is only valuable when it links with business decision-making. Organizations will want to link outputs from scraping to pricing engines, inventory management tools, and business intelligence dashboards.

Modern scraping technologies start with seamless integration by offering APIs and data feeds. This automation means competitive intelligence is continually flowing within operational systems without any manual effort.

Transforming Raw Data to Actionable Insights

Unrefined data must be evaluated to be converted into purposeful knowledge. Companies need different systems to detect behavior differences, observe trends, and then establish alerts for critical situations.

For instance, a dashboard may note when, say, one of your competitors is planning large deals/promotions, when your most demanded items for a season become out of stock, or when prices are noticeably off the historical pattern. Companies are empowered to act with capability and timeliness with the knowledge, as opposed to reacting quickly.

The Real-World Impact on Business Results

Case Study: Fashion Retailer

A mid-sized fashion retail company engaged with 3i Data Scraping company in 2018 to monitor 15 of its competitors. The company scraped pricing, product launches, and promotional activity on 5,000 products.

Within three months, the fashion retailer identified that competitors were launching 48 hours before major holiday events. Equipped with this intelligence, the retailer made a calendar adjustment to launch their promotions 24 hours in advance. The retailer captured early holiday shoppers and increased holiday income by 23%.

In addition, the scraper program identified gaps in the competitors’ product assortments and products in the sustainable fashion category. As a result, the retailer increased its sustainable fashion product assortment, capturing market share from competitors and expanding an underserved industry.

Must read: How Price Scraping Increased Sales for an E-commerce Store

Case Study: Electronics Marketplace

An electronics marketplace engaged in web scraping to identify unauthorized sellers who were breaching their manufacturer’s agreement on minimum advertised pricing (“MAP”). Prior to setting up automated monitoring, they employed manual interventions that perhaps saw about 50 violations monthly.

After using the 3i Data Scraping, the first month of scraping the website resulted in the detection of over 300 violations. Brand relationship integrity and uninterrupted pricing integrity across all vendors were quickly protected through desired enforcement. Within six months, brand partners increased their product allocation by over 40%.

Core Challenges and Solutions

Anti-Scraping Technologies

Many websites provide technology to prevent automated data collection. Techniques used include CAPTCHA, IP blocking, rate limiting, and honeypot traps. Ongoing technical adjustments are needed to sustain reliable scraping functionality.

Professional scraping organizations continuously invest in countermeasures. They use residential proxy networks, do intelligent scramble request patterns to avoid bot detection, and implement machine learning techniques to use human-like behavior to mask their scraping. These all lead to uninterrupted collection.

Changing Website Structures

Websites undergo redesigns occasionally, which include modifications to their HTML structure. This alteration breaks the scraping scripts that rely on particular elements on the page. Consequently, any scraping solution would require maintenance and updates.

Reliable web data scraping service providers, like 3i Data Scraping, will routinely check the scrapers and update them as needed when websites are redesigned. Many also use artificial intelligence tools that automatically adjust to slight changes in structure.

Data Density Management

Full-scale competitive intelligence often will generate huge data volumes. Storing, processing, and analyzing extensive data will require a substantial infrastructure and efficient algorithms.

Cloud-based scraping solutions scale to the degree of data density. These types of solutions utilize efficient storage techniques and provide a method to query and analyze large datasets without hindering performance.

Future Trends in E-commerce Scraping

AI-Enhanced Analysis

Artificial intelligence changes raw scraped data into greater intelligence. Machine learning can predict competitor pricing, identify new product trends, and identify anomalies signaling market changes. Pending scraping solutions will enable multi-dimensional integration of AI into predictive intelligence and not just descriptive intelligence in raw data snapshots.

Visual Intelligence

In addition to textual data, image scraping and analysis provide even more intelligence. AI can assess product images to see if there are design trends, measure presentation quality, and even determine if product photography has been reproduced. 3i Data Scraping continues to develop image intelligence capabilities to work in tandem with traditional data scraping.

Real-Time Decision Automation

As data scraping and analysis become even faster, businesses will be able to automate more decisions. Pricing algorithms can change prices automatically based on competitor behavior. Inventory systems may prompt or automatically reorder inventory based upon a stock-out at a competitor, indicating demand for customers to reorder items. The evolution from intelligence to automation is the next iteration of competitive e-commerce.

Conclusion

Web scraping is now a critical infrastructure in support of competitive e-commerce enterprises. This is due to the fact that it supplies the market intelligence in real-time that is needed to compete effectively in such dynamic digital marketplaces. With scraping, e-commerce businesses are able to make data-driven decisions surrounding pricing strategy, product selection, review monitoring, and MAP compliance for every business function.

However, for scraping to be effective, it requires people with technical skills, legal knowledge, and operational experience. This is where professional service providers like 3i Data Scraping come in, as they facilitate the process for businesses that prefer to focus on strategy rather than technical implementation.

As e-commerce competition continues to ramp up, companies leveraging robust competitive intelligence will have clear advantages over companies relying on gut-feel or slow information. Companies not deploying web scraping as a program will fall progressively behind the competition in the industry. Therefore, web data scraping should be seen as a requirement of business infrastructure, not an optional technology.

It is no longer whether businesses should employ competitive intelligence scraping. Businesses should turn their attention to how quickly these capabilities can be deployed, but more importantly, how well this scraped data will lend itself to a competitive advantage.

For more details on 3i Data Scraping’s professional web data scraping services, contact us today!

My toxic trait is that I love to argue. Even if I’m just playing devil’s advocate and I don’t believe in the argument I will still make it to hear your answer.

De-identifying or anti-identity on platforms. I wonder if it is possible to strip yourself of an identity online at all. I have been thinking a lot about data mining, digital id and age verification. The Australian government is making it illegal for under 16s to access social media so over 16s have to verify their age.

A date of birth is a powerful identity tool, as is a passport or a driver’s license. I do not want to give billionaire tech bros my id. Or the government.

But if you question any of this you are “hiding something”. Or accused of something much worse.

But what about protecting something? I don’t really post on gender identity or political views anymore. Because I don’t know where my bit of brain fart goes when I press “Post”.

That bothers me.

Did a bit more digging through Slay the Princess’s code.

Here are some interesting details about the Shifting Mound fight that shed a little light on the development cycle going into the Pristine Edition:

• The Spectre has a commented out Violent response that could contribute to the “Your New World” ending. It would have been accessible if you attempted to exorcise the Spectre. Now trying to do that leads to the Princess and the Dragon
• Most vessels have a script label associated with them felina__start. Some of the chapter 3 vessels that can only be reached from a specific chapter 2 such as Eye of the Needle and Den are instead labeled as 2. The only vessel that doesn’t have a unique label is the Apotheosis. Her script is a subset of the Tower’s script instead.
• There’s a boolean variable called come_from_tower which is only true if you activate the felina_tower_start script and it’s set to false after you respond to her. The game has to track whether the Tower and Apotheosis was the vessel you just spoke to because they appear in the background while all the other vessels appear in the foreground. It’s probably also why the Apotheosis doesn’t have her own script section. It was just easier to put both under the same label since they both had a special variable associated with them.
• For the chapter 3 vessel names, all the ones added in Pristine Edition are given their own names rather than being named after their chapter 2 vessels. For example, the Cage’s script label is felina_cage_start instead of felina_prisoner2_start. Interestingly, the Thorn’s script label is called felina_thorn_start instead of felina_witch2_start despite being in the original version.
• The Thorn and the Moment of Clarity are the only Chapter 3 vessels that cannot contribute toward getting the “Your New World” ending. Moment of Clarity is understandable because you’re not able to fight her at all. Meanwhile, I wouldn’t be surprised if the Thorn accidentally got overlooked when adding the new dialogue options since she’s not labeled the same as the other vessels. There are opportunities to enact violence against her that should warrant a point toward the ending.

So anyway, I’d guess that the “Your New World” ending was one of the earlier additions made to the game. Then the new routes were made after. When the Spectre’s exorcism ending was changed into the route to the Princess and the Dragon, the violence line got commented out.