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How will Twitter determine bad vibes in a conversation?

Twitter wants to give users a heads up on ‘intense’ conversations, but what happens to those tweets that are posted in jest?

“Ever want to know the vibe of a conversation before you join in? We’re testing prompts on Android and iOS that give you a heads up if the convo you’re about to enter could get heated or intense,” read a tweet by Twitter announcing that the company was exploring labels to let users know when they are entering a toxic conversation. The platform claims the move will foster “healthy conversation” but it is unclear what kind of parameters will determine the vibe of a conversation.

Image Credits: Twitter

The test labels appear under a tweet and display a little warning that “conversations like this can be intense.” To participate, it looks like you’ll need to click through the prompt encouraging users to be factual, open to diverse perspectives, and reminding them of their shared humanity, according to the image shared by the social media platform.

Twitter, in response to a user’s query, said that “the criteria being used to determine which conversations will show this prompt may change” as they learn from this test and because it’s an early test, the company “may not get it right every time”. One criterion that the company revealed was that it will consider the topic of the tweet and the relationship between the tweet’s author and replier.

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Of late, Twitter has been busy trying to curb toxicity on its platform. It has several features empowering users to block trolls and mute uninvited participants. The latest move, however, might backfire given the complexity of the task at hand. Not to mention the cultural nuances that differ from country to country.

What are the concerns around determining bad vibes?

The parameters are of particular interest in this case as TechCrunch put it: “people on Twitter will fight about anything and everything— it’s the internet’s premier destination for high-speed, low-information opinion slinging.”

The concern arises from the fact that many a time, Twitter users engage in an ironic sparring contest for the sake of fun or underscore the importance of an issue using sarcasm. This prompt might just appear on such tweets as it is unlikely that an algorithm will be able to distinguish between an actual heated conversation and a faux one.

For now, we will have to wait and watch how this prompt shapes up in the future and the extent of its fallout.

Which prompts has Twitter introduced in the past?

Hateful replies: Twitter announced last year that it was giving users a second chance before they tweet in order to address rampant harassment. The new feature was limited to replies and users using “harmful” language saw a prompt advising them to self-edit before posting a reply. It must be noted that Twitter’s early tests ran into some problems because its algorithms sometimes struggled to understand the nuance that occurs in many conversations, TechCrunch reported then.

Read articles before retweeting: The social media service rolled out a prompt in which it suggested users to “read the article before you retweet it” last year. It shows up when people retweet a story they haven’t clicked through as headlines don’t tell the whole story and might be actively misleading.

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Prompts during important events: The company shows prompts in the Explore tab or the Home Timeline that link to a public service announcement (PSA) Moment during events such as elections or public health emergencies. These prompts include information from trusted sources on topics like how to vote safely in a pandemic or trustworthy information about getting vaccinated.

Summary of Twitter’s features in the last two years

Twitter has added or is considering the following new features to its platform:

  • Communities: Twitter said it is testing Communities, a feature similar to Facebook Groups and Reddit subreddits that lets users find and tweet to people with similar interests.
  • Tips: Users will now be able to support their favourite profiles on Twitter by tipping them using several payment options including cryptocurrencies, the company announced in a blog. Twitter will charge no commission as per the blog.
  • Good bots: Automated accounts on Twitter will carry a label that lets users know they are bots, the microblogging site announced in a tweet. The company said that it will offer the label, in a test run first, to over 500 developer accounts, TechCrunch reported. The microblogging service did not reveal the duration of the test run but The Verge added that the feature will be available to all developers by the end of this year.
  • Ticketed Spaces: Handpicked users will be able to create paid gatherings on Twitter’s audio chat room feature, Spaces. The company opened up applications for content monetisation on Spaces in June. It is experimenting with the feature on iOS for now but hopes to bring it to all users soon.
  • Super Follow: The company launched its paid subscription feature called ‘Super Follow’ last month. It said that the feature will at present only be available to iOS users in the US and Canada, although it will expand to iOS, Android, and web users worldwide over time.
  • Emoji reactions for tweets: The feature will provide emoji reactions for tweets that go beyond a “Like” reaction. The feature will initially be available to users in Turkey.
  • Full-width photos and videos: It is testing edge-to-edge media in tweets on iOS to give users a borderless view for photos and videos on their timelines.
  • Labels for misleading tweets: The platform rolled out a feature in the United States, South Korea, and Australia, where users will be able to flag tweets that come across as misleading in August 2021. It introduced labels such as manipulated media and synthetic media first in February 2020.
  • Birdwatch: Twitter tested a tool called “Birdwatch” in January this year which lets users identify the information they believe is false or misleading. The tool allows users to write notes about tweets they consider untrue or that may contain misinformation.

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