 "Twitter launches Tamil topics for all of its Android, iOS and web users")
Microblogging site Twitter on Wednesday announced that it is launching Tamil topics for 100 per cent of its android, iOS and web users who have set Tamil as their primary language.
The launch is part of Twitter's commitment to build for India and serve the country's diverse and multilingual audiences and will help people with Tamil as their primary language to find the most relevant and interesting conversations in the language across literature, music, poetry, and much more, the company said.
Tamil is the third most used language on the service in India and Tamil topics will let people choose and personalise the content that they want to see on their home timeline whether it's more tweets on artists like Vijay, Rajinikanth, A.R. Rahman or sports teams like Chennai Super Kings.
"Over the years, Twitter has broadened the scope and scale of real-time conversation and connection by providing greater possibilities for intimate and authentic interactions through features such as Spaces. In fact, Tamil audiences were early adopters of Spaces and to celebrate their enthusiasm we introduced a dedicated #TamilSpaces emoji," said Cheryl-Ann Couto, Head of Partners at Twitter India, in a statement.
"With Topics and #OnlyOnTwitter activations in Tamil, such as the recent #FanTweets video with music maestro Ilaiyaraaja and a 'Voice Tweet from Rajnikanth' on the occasion of #15YearsOfSivaji, we are bringing relevant and exclusive content to people respectively and trying to help them connect directly with the things that they care about as well as with one another. We are excited to support and elevate the incredible community that surrounds all things Tamil Twitter and see it grow further," she added.
Twitter first introduced topics in 2019 and the following year launched it in Hindi. Currently, there are more than 15,000 topics available across 13 languages and approximately 280 million accounts follow at least one of these topics.
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Twitter topics follow machine learning to find tweets related to a specific subject. When a user follows a topic, they will see tweets from a whole host of accounts that are experts, fans or just tend to talk about that thing a lot on Twitter.
--IANS
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