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Misinformed through social media, Trump supporters take to the streets to challenge election result




Harrisburg, Pennsylvania (CNN Business)In the capital of Pennsylvania — the state that ultimately tipped the election in favor of President-elect Joe Biden — supporters of President Donald Trump gathered to protest the election result this weekend.

The past four years in America have been an education in how grievances and misinformation on social media don’t just stay online — they spill out onto the streets, can manifest as violence, and, as seen in Harrisburg, this weekend, be used in attempts to undermine the bedrock of American democracy: free and fair elections.

Trump supporters here gathered under the banner “Stop the Steal,” convinced the election had been stolen.

One woman told me she had seen so much “evidence” that the election had been rigged she would support a total re-vote.

“When you have video footage of people taking bags of ballots and showing that they are for Donald Trump and lighting them on fire,” she said, “there’s a problem.”

But the video she cited as evidence of a rigged American election is not real.

    It has been circulating on social media for days, even being retweeted by Eric Trump, the President’s son, but the video does not show Trump ballots being burned, as some have claimed.

    Election officials in Virginia, where the papers that looked like ballots appeared to be from, have explained that what you see in the video are sample ballots. They have been trying to correct the viral misinformation for days.

    “Note the absence of the bar code markings that are on all official ballots. The ballots in the video were sample ballots,” the City of Virginia Beach said in press release last week.

    Trump supporters’ use of false information in this way is not unique; it is not a one-off.

    Other protesters I spoke to in Harrisburg cited a sudden change in an online result map in favor of Biden on election night in Michigan as evidence that something had gone awry. Trump had amplified that claim himself on his Twitter account. But that too has been shown to be misinformation (a thorough debunk here). Twitter labeled Trump’s post with a message that read “Some or all of the content shared in this Tweet is disputed and might be misleading”

    The use of false information didn’t start with “Stop the Steal.” Trump and some of his supporters have weaponized misinformation throughout the election campaign. CNN has previously shown how deceptively edited videos of Biden had contributed to some Trump supporters’ belief that Biden was not fit for office.

    This, of course, does not happen in a vacuum.

    The President himself, his allies, and Fox News personalities, embrace misinformation. Sometimes Trump will retweet a post with false claims that is already going viral. At other times, Trump will create his own misinformation by posting false claims. Trump and his followers have used misinformation as “evidence” to prove the validity of more misinformation.

      Social media exacerbates the problem — serving as an engine for misinformation to spread.

      Over the past week, Twitter, and to a lesser extent Facebook, have taken aggressive steps to label as misinformation false posts from the President as he seeks to undermine the integrity of the election.

      But those labels won’t convince Trump supporters who have already embraced conspiracy theories about the election. Some view labels and fact-checks as proof that they are actually correct and that Big Tech is trying to censor them.

      “I think that’s not their place. That’s not their place to determine what the truth is for the people. We have a mind of our own. We can determine what the truth is,” the woman in Harrisburg, who had cited the fake burning ballots video, told me.

      The middle-aged woman told me her name was Melissa but did not want to share her full name citing “cancel culture.”

      Although she might have been wrong about that video, she did identify the role platforms like Facebook play in shaping American political discourse as catalysts for confirmation bias.

      “We’re like one big science experiment for social media,” she said. “If I’m seeking a certain viewpoint and they seem to see that I favor that viewpoint more, that’s the viewpoint that they’re going to feed me and then the other side’s going to get a different viewpoint,” she said.

        Asked if it concerns her, “I mean it concerns me, yes. Because of the fact that, unfortunately, people fail to think for themselves. They feed into everything that they’re seeing without questioning it.”

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        What can ChatGPT do?



        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



        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.


        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]

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




        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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