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In fast-moving pandemic, sources of falsehoods spread by text, email, WhatsApp, and TikTok elude …

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Misleading text messages claiming that President Trump was going to announce a national quarantine buzzed into cell phones across the country over the weekend, underscoring how rapidly false claims are spreading — and how often it’s happening beyond the familiar misinformation vehicles of Facebook and Twitter.

The false cell phone texts spread so widely that Sunday night the White House’s National Security Council, fearing the texts were an attempt to spook the stock market as it opened Monday, decided to directly debunk the misleading claims in a Twitter post: “Text message rumors of a national #quarantine are FAKE. There is no national lockdown.”

But by then the messages already had spread widely, as had similar ones both in the United States and Europe in recent days. Text messages, encrypted communication apps such as WhatsApp and some social media platforms have carried similarly alarming misinformation, much of it with the apparent goal of spurring people to overrun stores to buy basic items ahead of a new wave of government restrictions.

The one claiming that Trump was going to impose a national quarantine included the advice, “Stock up on whatever you guys need to make sure you have a two week supply of everything. Please forward to your network.”

In fact, authorities have warned against aggressive buying that could disrupt supply chains and fuel panic.

Trump addressed the misleading text messages at an afternoon news conference Monday, saying, “It could be that you have some foreign groups that are playing games.”

On the possibility of a national quarantine, Trump said, “We haven’t determined to do that at all… Hopefully we won’t have to.”

In Europe, one viral video that was shared on WhatsApp claimed to show shoppers mobbing a store in the Netherlands. A version of the same clip put to music on TikTok, a popular China-based platform for short videos, was viewed more than four million times, according to a report last week by disinformation research group Bellingcat, which determined the video was actually from an incident in Germany several years ago.

Independent researchers, overall, though have struggled to track some of the coronavirus misinformation spreading as a fast-moving pandemic and rapidly evolving government actions spur insatiable demand for information — and opportunities to spread falsehoods. Often the messages are traveling from person to person, or through closed groups of people, through email or texts that are not seen by the general public.

Text messages are particularly difficult for independent researchers to trace, especially when messages ― like the Trump quarantine texts ― are delivered as graphical images as opposed to words that computers can more easily analyze. Those pushing misinformation may be changing tactics away from social media to thwart the major platforms’ efforts to catch and block falsehoods.

“As social media companies focus on keywords like ‘covid’ and ‘coronavirus,’ there are pockets of conspiracy theories that are welling up that potentially have some offline impact,” said Joan Donovan, director of the Technology and Social Change Research Project at Harvard’s Shorenstein Center.

Clemson University researcher Darren Linvill said a version of the false Trump quarantine message spread on Twitter throughout Sunday evening and into Monday morning, peaking before midnight East Coast time, but the total numbers were small, with fewer than 200 tweets. He found a few references on other social media.

What most concerned Linvill was that the misleading messages were spreading on cell phone networks, among friends and colleagues, undermining most readily available tracking technologies.

“That is disturbing,” said Linvill, an associate professor of communication. “The fact that this is texts … makes this impossible to track on social media.”

Graham Brookie, the director of the Atlantic Council’s Digital Forensic Research Lab, which tracks disinformation, said misleading text messages can have great effect because they use the same technology that families and friends use to communicate, meaning people are “more likely to believe” what they read.

“It’s a return to an older threat,” Brookie said. “We saw it on e-mail. This is not new. We’re going to need to figure out more mechanisms to learn about it more quickly.”

In contrast to SMS text messages, WhatsApp has developed controls to prevent mass text messages, imposing limits on the number of messages a single person can send at any one time. Forwarded messages and chain messages are labeled, spokesman Carl Woog said.

Twitter said it too has developed tools to slow the spread of misinformation, especially when there’s a risk of direct harm.

“We will remain vigilant and are committed to collaboration, which is key to protecting the rapidly-evolving public conversation around this critical global public health issue,” said Del Harvey, Twitter’s vice president of trust and safety.

A representative for ByteDance, owner of TikTok, did not respond to a message seeking comment.

As the false texts spread about a looming federal quarantine, the National Security Council began an interagency effort — involving the FBI, intelligence agencies, Homeland Security and State departments — to determine who is behind the apparent disinformation campaign.

The texts were often screenshots of purported text messages sent to friends and relatives to make them look authentic, a degree of sophistication that one U.S. official said might show that it’s a “broader plot” than something one hacker alone could pull off.

Federal Communications Commission spokesman Will Wiquist said, “Although we have not received any consumer complaints on this yet, we are aware of the issue and are looking into it.”

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What can ChatGPT do?

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ChatGPT Explained

ChatGPT is a large language model developed by OpenAI that is trained on a massive amount of text data. It is capable of generating human-like text and has been used in a variety of applications, such as chatbots, language translation, and text summarization.

One of the key features of ChatGPT is its ability to generate text that is similar to human writing. This is achieved through the use of a transformer architecture, which allows the model to understand the context and relationships between words in a sentence. The transformer architecture is a type of neural network that is designed to process sequential data, such as natural language.

Another important aspect of ChatGPT is its ability to generate text that is contextually relevant. This means that the model is able to understand the context of a conversation and generate responses that are appropriate to the conversation. This is accomplished by the use of a technique called “masked language modeling,” which allows the model to predict the next word in a sentence based on the context of the previous words.

One of the most popular applications of ChatGPT is in the creation of chatbots. Chatbots are computer programs that simulate human conversation and can be used in customer service, sales, and other applications. ChatGPT is particularly well-suited for this task because of its ability to generate human-like text and understand context.

Another application of ChatGPT is language translation. By training the model on a large amount of text data in multiple languages, it can be used to translate text from one language to another. The model is able to understand the meaning of the text and generate a translation that is grammatically correct and semantically equivalent.

In addition to chatbots and language translation, ChatGPT can also be used for text summarization. This is the process of taking a large amount of text and condensing it into a shorter, more concise version. ChatGPT is able to understand the main ideas of the text and generate a summary that captures the most important information.

Despite its many capabilities and applications, ChatGPT is not without its limitations. One of the main challenges with using language models like ChatGPT is the risk of generating text that is biased or offensive. This can occur when the model is trained on text data that contains biases or stereotypes. To address this, OpenAI has implemented a number of techniques to reduce bias in the training data and in the model itself.

In conclusion, ChatGPT is a powerful language model that is capable of generating human-like text and understanding context. It has a wide range of applications, including chatbots, language translation, and text summarization. While there are limitations to its use, ongoing research and development is aimed at improving the model’s performance and reducing the risk of bias.

** The above article has been written 100% by ChatGPT. This is an example of what can be done with AI. This was done to show the advanced text that can be written by an automated AI.

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Google December Product Reviews Update Affects More Than English Language Sites? via @sejournal, @martinibuster

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Google’s Product Reviews update was announced to be rolling out to the English language. No mention was made as to if or when it would roll out to other languages. Mueller answered a question as to whether it is rolling out to other languages.

Google December 2021 Product Reviews Update

On December 1, 2021, Google announced on Twitter that a Product Review update would be rolling out that would focus on English language web pages.

The focus of the update was for improving the quality of reviews shown in Google search, specifically targeting review sites.

A Googler tweeted a description of the kinds of sites that would be targeted for demotion in the search rankings:

“Mainly relevant to sites that post articles reviewing products.

Think of sites like “best TVs under $200″.com.

Goal is to improve the quality and usefulness of reviews we show users.”

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Google also published a blog post with more guidance on the product review update that introduced two new best practices that Google’s algorithm would be looking for.

The first best practice was a requirement of evidence that a product was actually handled and reviewed.

The second best practice was to provide links to more than one place that a user could purchase the product.

The Twitter announcement stated that it was rolling out to English language websites. The blog post did not mention what languages it was rolling out to nor did the blog post specify that the product review update was limited to the English language.

Google’s Mueller Thinking About Product Reviews Update

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Product Review Update Targets More Languages?

The person asking the question was rightly under the impression that the product review update only affected English language search results.

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But he asserted that he was seeing search volatility in the German language that appears to be related to Google’s December 2021 Product Review Update.

This is his question:

“I was seeing some movements in German search as well.

So I was wondering if there could also be an effect on websites in other languages by this product reviews update… because we had lots of movement and volatility in the last weeks.

…My question is, is it possible that the product reviews update affects other sites as well?”

John Mueller answered:

“I don’t know… like other languages?

My assumption was this was global and and across all languages.

But I don’t know what we announced in the blog post specifically.

But usually we try to push the engineering team to make a decision on that so that we can document it properly in the blog post.

I don’t know if that happened with the product reviews update. I don’t recall the complete blog post.

But it’s… from my point of view it seems like something that we could be doing in multiple languages and wouldn’t be tied to English.

And even if it were English initially, it feels like something that is relevant across the board, and we should try to find ways to roll that out to other languages over time as well.

So I’m not particularly surprised that you see changes in Germany.

But I also don’t know what we actually announced with regards to the locations and languages that are involved.”

Does Product Reviews Update Affect More Languages?

While the tweeted announcement specified that the product reviews update was limited to the English language the official blog post did not mention any such limitations.

Google’s John Mueller offered his opinion that the product reviews update is something that Google could do in multiple languages.

One must wonder if the tweet was meant to communicate that the update was rolling out first in English and subsequently to other languages.

It’s unclear if the product reviews update was rolled out globally to more languages. Hopefully Google will clarify this soon.

Citations

Google Blog Post About Product Reviews Update

Product reviews update and your site

Google’s New Product Reviews Guidelines

Write high quality product reviews

John Mueller Discusses If Product Reviews Update Is Global

Watch Mueller answer the question at the 14:00 Minute Mark

[embedded content]

Searchenginejournal.com

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Survey says: Amazon, Google more trusted with your personal data than Apple is

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survey-says:-amazon,-google-more-trusted-with-your-personal-data-than-apple-is-–-phonearena
 

MacRumors reveals that more people feel better with their personal data in the hands of Amazon and Google than Apple’s. Companies that the public really doesn’t trust when it comes to their personal data include Facebook, TikTok, and Instagram.

The survey asked over 1,000 internet users in the U.S. how much they trusted certain companies such as Facebook, TikTok, Instagram, WhatsApp, YouTube, Google, Microsoft, Apple, and Amazon to handle their user data and browsing activity responsibly.

Amazon and Google are considered by survey respondents to be more trustworthy than Apple

Those surveyed were asked whether they trusted these firms with their personal data “a great deal,” “a good amount,” “not much,” or “not at all.” Respondents could also answer that they had no opinion about a particular company. 18% of those polled said that they trust Apple “a great deal” which topped the 14% received by Google and Amazon.

However, 39% said that they trust Amazon  by “a good amount” with Google picking up 34% of the votes in that same category. Only 26% of those answering said that they trust Apple by “a good amount.” The first two responses, “a great deal” and “a good amount,” are considered positive replies for a company. “Not much” and “not at all” are considered negative responses.

By adding up the scores in the positive categories,

Apple tallied a score of 44% (18% said it trusted Apple with its personal data “a great deal” while 26% said it trusted Apple “a good amount”). But that placed the tech giant third after Amazon’s 53% and Google’s 48%. After Apple, Microsoft finished fourth with 43%, YouTube (which is owned by Google) was fifth with 35%, and Facebook was sixth at 20%.

Rounding out the remainder of the nine firms in the survey, Instagram placed seventh with a positive score of 19%, WhatsApp was eighth with a score of 15%, and TikTok was last at 12%.

Looking at the scoring for the two negative responses (“not much,” or “not at all”), Facebook had a combined negative score of 72% making it the least trusted company in the survey. TikTok was next at 63% with Instagram following at 60%. WhatsApp and YouTube were both in the middle of the pact at 53% followed next by Google and Microsoft at 47% and 42% respectively. Apple and Amazon each had the lowest combined negative scores at 40% each.

74% of those surveyed called targeted online ads invasive

The survey also found that a whopping 82% of respondents found targeted online ads annoying and 74% called them invasive. Just 27% found such ads helpful. This response doesn’t exactly track the 62% of iOS users who have used Apple’s App Tracking Transparency feature to opt-out of being tracked while browsing websites and using apps. The tracking allows third-party firms to send users targeted ads online which is something that they cannot do to users who have opted out.

The 38% of iOS users who decided not to opt out of being tracked might have done so because they find it convenient to receive targeted ads about a certain product that they looked up online. But is ATT actually doing anything?

Marketing strategy consultant Eric Seufert said last summer, “Anyone opting out of tracking right now is basically having the same level of data collected as they were before. Apple hasn’t actually deterred the behavior that they have called out as being so reprehensible, so they are kind of complicit in it happening.”

The Financial Times says that iPhone users are being lumped together by certain behaviors instead of unique ID numbers in order to send targeted ads. Facebook chief operating officer Sheryl Sandberg says that the company is working to rebuild its ad infrastructure “using more aggregate or anonymized data.”

Aggregated data is a collection of individual data that is used to create high-level data. Anonymized data is data that removes any information that can be used to identify the people in a group.

When consumers were asked how often do they think that their phones or other tech devices are listening in to them in ways that they didn’t agree to, 72% answered “very often” or “somewhat often.” 28% responded by saying “rarely” or “never.”

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