Friday September 20, 2019
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Ahead of Israel’s Elections, Twitter Suspends 600 Chinese Religious Group Accounts

The accounts suspended were amplifying political messages for right-wing politicians and vast majority of the content, posted behind fake names in Hebrew, focused on religion, BuzzFeed News reported

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A light gray box will appear before the tweet, notifying users that it's in violation, but it will remain available to them. Pixabay

Ahead of Israel’s upcoming national elections, micro-blogging site Twitter has suspended nearly 600 suspicious Hebrew-language accounts run by a controversial Chinese religious group.

The accounts suspended were amplifying political messages for right-wing politicians and vast majority of the content, posted behind fake names in Hebrew, focused on religion, BuzzFeed News reported on Sunday.

The controversial religious group has been recognised as Church of Almighty God (CAG) — a Christian sect, banned in China, that believes that Jesus Christ reincarnated as a Chinese woman who is currently living in Queens in the New York City.

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A Twitter spokesperson said that the accounts were suspended due to spam violations, the report noted. Pixabay

The accounts were flagged due to what appeared to be co-ordinated amplification of content, according to a source familiar with how the CAG accounts were brought to Twitter’s attention and asked for anonymity to protect ongoing research, the report said.

However, the micro-blogging platform has chosen not to disclose any details about the CAG-affiliated suspended accounts.  A Twitter spokesperson said that the accounts were suspended due to spam violations, the report noted.

The CAG-affiliated Twitter accounts were among hundreds flagged as suspicious, based on initial work done by Noam Rotem and Yuval Adam, two Israeli researchers who study social media manipulation.

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“Roughly 600 accounts have been removed by Twitter as a result of Rotem and Adam’s research, according to the source with knowledge of account removals,” the report added. Wikimedia

“Roughly 600 accounts have been removed by Twitter as a result of Rotem and Adam’s research, according to the source with knowledge of account removals,” the report added.

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It remains unclear exactly why were these CAG accounts from Chinese people of Christian faith spreading mixed political messaging into their activity just days before the Israeli elections commence.

“BuzzFeed News did not identify any Hebrew-language CAG accounts spreading false or misleading information. Given the group’s acrimonious relationship with the Chinese government, its online activity is clearly not state-linked,” the report said. (IANS)

Next Story

Researchers Develop New Algorithm to Identify Cyber-bullies on Twitter

“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn

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FILE - A man reads tweets on his phone in front of a displayed Twitter logo. VOA

Researchers have developed machine learning algorithms which can identify bullies and aggressors on Twitter with 90 per cent accuracy.

For the study published in the journal Transactions on the Web, the research team analysed the behavioural patterns exhibited by abusive Twitter users and their differences from other users.

“We built crawlers — programs that collect data from Twitter via variety of mechanisms,” said study researcher Jeremy Blackburn from Binghamton University in the US.

“We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them,” Blackburn said.

The researchers then performed natural language processing and sentiment analysis on the tweets themselves, as well as a variety of social network analyses on the connections between users.

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Twitter is a social media app that encourages short tweets and brief conversations. Pixabay

They developed algorithms to automatically classify two specific types of offensive online behaviour, i.e. cyber-bullying and cyber-aggression.

The algorithms were able to identify abusive users — who engage in harassing behaviour like those who send death threats or make racist remarks — on Twitter with 90 per cent accuracy.

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“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn.

“Our research indicates that machine learning can be used to automatically detect users that are cyber-bullies, and thus could help Twitter and other social media platforms remove problematic users,” Blackburn added. (IANS)