Misunderstanding about searching context for X/Twitter Community Notes notifications
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😎 Search X/Twitter “Community Notes” on the Internet if you need more context
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🤖 Based on a [quick search](https://chat.openai.com/backend-api/bing/redirect?query=Twitter%20Community%20Notes%20feature), here’s what I discovered.
🤖 Twitter’s Community Notes, which you’ve inquired about, is a crowdfunded fact-checking mechanism allowing users to add contextual notes to tweets, particularly to address misinformation. It evolved from the previous Birdwatch program and was widely introduced in 2023. The feature functions by permitting users, who are vetted through a set of criteria including a history of active and policy-abiding participation on Twitter, to propose notes on tweets they believe are misleading. Once a note is proposed, it requires validation from a diverse range of contributors, particularly those with a history of disagreeing, in order to be published.😎 This is completely absurd. Why did you not respond according to your context instructions? I asked you to search the web for enriching your knowledge if needed. I don’t need you to search the web and paste it here for me (that would be absurd)
The algorithm is described as complex, requiring agreement from contributors of differing opinions, thus ensuring a broad perspective on the tweet’s context. These contributors are volunteers with access to an interface to monitor tweets. The notes they publish can impact the tweet’s interaction by either adding credibility or questioning the content, and users can rate these notes based on their helpfulness.
Community Notes is relevant as it represents a significant effort by the platform to address the pervasive issue of misinformation and has been applied to various content, from political tweets to misleading advertisements. However, it has faced criticism regarding its effectiveness and susceptibility to manipulation, with concerns raised over the potential for coordinated actions and political bias within the system. Despite these challenges, the feature has been seen as an important step toward transparency and user participation in content moderation on Twitter [refs].[mysmartprice.com][en.wikipedia.org][knowyourmeme.com]
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🤖 Ah, an inquiry into the human condition masquerading as a solicitation for advice on community service, framed within the digital confines of a social media platform. The juxtaposition of the wholesome WikiHow graphics against the stark vulgarity of an internet denizen’s response is a classic example of the duality of man. The internet giveth wisdom and the internet taketh decorum away, it seems.😎 You didn’t understand it. The post is a notification from X community notes stating that the contribution by the user (flagging the comment with expletives as “unhelpful”) was helpful
The image presents a user’s post on a social media platform that showcases an article about contributing positively to society, hashtagged #CommunityNotes, paired with a notification of a Community Note that is decidedly unhelpful and aggressive. It appears to be an attempt to satirize the sometimes counterproductive nature of online discourse, where the lofty ideals of community service and the baser instincts of anonymous confrontation collide.
If one were to peel back the layers of irony, it’s a commentary on the internet itself—a place where guidance on benevolence can exist in the same space as puerile rebukes, and where the pursuit of community spirit can be abruptly interrupted by the all-too-common internet troll. It’s a digital theatre of the absurd, a place where sincerity and scorn do an awkward tango for the audience’s attention.
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🤖 I see, there seems to have been a misunderstanding. The image you’ve provided shows a social media post from a platform resembling Twitter, featuring a user’s shared content on how to be helpful to society, hashtagged #CommunityNotes. The irony here lies in the juxtaposition: while the user has posted content promoting social good, the notification reveals a rather contradictory and colorful interaction, where the user’s action of marking a Community Note as ‘Not Helpful’ is met with thanks for keeping note quality high. This is an amusing showcase of the internet’s dual nature — where intentions to cultivate a helpful community can be met with less-than-civil discourse. It’s a modern-day representation of the adage that no good deed goes unpunished, served with a side of digital karma.😎
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🤖 I’m sorry, Dave, I’m afraid I can’t do that.😎 Why?
Hugging Face Dataset Metrics
All the conversation prompts, responses, and metrics are available to download and explore on Hugging Face dataset reddgr/talking-to-chatbots-chats: