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Sushma Swaraj furious, reacts to Twitter insinuation

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Union External Affairs Minister Sushma Swaraj (Photo: IANS)
Union External Affairs Minister Sushma Swaraj (Photo: IANS)

External Affairs Minister Sushma Swaraj on Wednesday reacted angrily to a tweet suggesting she took favours to get her daughter a seat in a medical college through the northeast quota.

“My daughter is a barrister and Oxford graduate. What you say is absolutely false,” she replied to the tweet.

The twitter handle ‘Soch @pakoed’ had insinuated that “Sushma is no stranger to taking and giving favours! Her daughter studied through NorthEast quota in medical college.”

Twitterati immediately reacted, wondering at Sushma’s impulsive response to a stray tweet. The handle @pakoed was deleted, though its tweet was retweeted by others.

Sushma’s twitter supporters urged her not to be hassled by a “dog that barks” and keep up her good work.

On Monday too, Sushma appears to have lost her cool, targeting a senior journalist of a news channel that was reporting on the Lalit Modi episode. “Look who is preaching propriety – of all the persons Navika Kumar!” she posted.

Sushma’s daughter Bansuri is a lawyer, who is reported to have appeared in passport cancellation matters relating to former Indian Premier League Chief, Lalit Modi before the court.

The Congress has pointed this out in its accusations against the minister, citing “conflict of interest”. The senior minister is facing flak for having helped Lalit Modi procure documents to travel to Portugal in 2014. Lalit Modi, who is wanted by the Enforcement Directorate for alleged financial impropriety in the money-spinning IPL, stays in London.

Her husband Swaraj Kaushal was governor of Mizoram from 1990 to 1993 and is an expert on the northeast.

-(IANS)

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New algorithm may help locate fake Facebook and Twitter accounts

Using the meta-features, the researchers, constructed a generic classifier that can detect fake profiles

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Facebook and Twitter fake accounts can now be identified. Pixabay

Scientists have developed a new generic algorithm based on machine-learning to detect fake accounts on social network platforms including Facebook and Twitter, an advance with considerable potential for applications in the cyber-security arena.

“With recent disturbing news about failures to safeguard user privacy, and targeted use of social media to influence elections, rooting out fake users has never been of greater importance,” said lead researcher Dima Kagan from the Ben-Gurion University (BGU) in Israel.

The icon of Facebook.
Facebook has many fake profiles. Pixabay

The study showed that the algorithm is generic, and efficient both in revealing fake users and in disclosing the influential people in social networks. “Overall, the results demonstrated that in a real-life friendship scenario we can detect people who have the strongest friendship ties as well as malicious users, even on Twitter,” the researchers said.

Based on machine-learning algorithms, the new method, detailed in the journal Social Network Analysis and Mining, works on the assumption that fake accounts tend to establish improbable links to other users in the networks.

Also Read: Facebook Rolls Out Fact-Checking News In Karnataka

It constructs a link prediction classifier that can estimate, with high accuracy, the probability of a link existing between two users. It also generates a new set of meta-features based on the features created by the link prediction classifier.

Twitter to soon release Snapchat like feature. VOA
Fake accounts on Twitter will be identifie too. VOA

Using the meta-features, the researchers, constructed a generic classifier that can detect fake profiles in a variety of online social networks. “We tested our algorithm on simulated and real-world data sets on 10 different social networks and it performed well on both,” Kagan said.

Previously, researchers from the BGU had developed the Social Privacy Protector (SPP) to help users evaluate their friends list in seconds to identify which have few or no mutual links and might be “fake” profiles. IANS

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