Bots tweaking pre-election Twitter trends in India: US experts

Agencies
April 9, 2019

New Delhi, Apr 9: In the run-up to the general elections, automated Twitter bots made a massive attempt to boost political hashtags, both in support of and in opposition to Prime Minster Narendra Modi, according to a research conducted by US experts. 

The automated accounts were deployed on a massive scale on February 9-10, with small groups of accounts pushing out thousands of posts an hour, according to the team from the US think-tank Atlantic Council's Digital Forensic Research Lab (DFRLab). 

The accounts were domestic in origin and substance, researchers said. 

While bots were used on both sides on February 9-10, the pro-Modi traffic was far more heavily manipulated than the anti-Modi traffic. 

According to the team, the pro-Modi traffic far more heavily manipulated than any large-scale traffic flow the DFRLab has analysed as of yet. 

"The incident highlights the sheer scale of attempts to manipulate Twitter traffic as India's main political parties head to the polls. It also underlines the extent to which social media more broadly has become an electoral battleground," the researchers wrote in a blog post.

Ben Nimmo, Senior Fellow for Information Defense at the DFRLab took to Twitter to highlight the findings. 

"These manipulation attempts ranged from large to extreme," Nimmo wrote in a Twitter post. 

"They were too clumsy to have much impact, but the sheer scale of the attempts on both sides is worrying, ahead of the election," Nimmo said. 

While the scale of the activity was vast, its impact was rather muted given the relatively low number of followers of the accounts. 

The massive scale of the attempted manipulation nevertheless bodes ill for the quality of online debate in India as the election approaches. 

It remains important to be able to expose such efforts, researchers said. 

The DFRLab scanned traffic on the hashtag #TNwelcomesModi, short for "Tamil Nadu welcomes Modi," which trended in India on February 9-10 and was mentioned over 777,000 times in two days. 

The most frequently posting account was @SasiMaha6, which posted #TNwelcomesModi tweets 1,803 times during the scan, or roughly one tweet every 15 seconds. 

Another high-volume account was @priyamanaval6, which posted the hashtag 1,677 times, or roughly one tweet every 17 seconds for over seven hours. 

These sustained rates are far too high for human posting, researchers said. The top three accounts alone posted #TNwelcomesModi 4,914 times, or roughly 10 percent of all traffic in the scan. 

The 50 most active accounts generated 30,446 tweets, or 61.2 percent of all traffic. 

The bot-driven praise for Modi's visit was countered, in part, by bots. On February 10, the hashtag #GoBackModi also trended, pushing messages that supported the Congress Party. 

This hashtag trended even faster, racking up 49,538 tweets in just over three hours in the early morning of February 10. It peaked at a lower rate, however, generating 447,000 posts on February 9-10. 

Just like #TNwelcomesModi, #GoBackModi was heavily pushed by a small number of high-volume accounts that posted hundreds of times an hour. Unlike #TNwelcomesModi, these accounts were still not suspended at the time of drafting. 

The most active was @PhillyTdp, which posted on #GoBackModi 2,179 times as the hashtag took off -- a staggering one tweet every 5.3 seconds for over three hours. 

Other accounts were similarly hyperactive. The second most active, @nritdpusa, posted 1,899 times in three hours, or roughly one tweet every 6 seconds. 

Overall, the nearly 50,000 tweets in the #TNwelcomesModi scan were posted by just 891 accounts, while the nearly 50,000 tweets in the #GoBackModi scan were posted by 7,394 accounts. 

By any measure, #TNwelcomesModi saw a much more aggressive attempt to make the hashtag trend from a much smaller user base, researchers wrote in the blog.

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News Network
January 17,2020

Mumbai, Jan 17: A 68-year-old convict of the 1993 Mumbai serial blasts case, Jalees Ansari, went missing on Thursday morning while being on parole, officials said.

Ansari, a resident of Mominpura in Agripada here who is serving a life term, is suspected to be involved in many bomb blast cases across the country, an official said.

He was on parole for 21 days from the Ajmer Central Prison, Rajasthan, and was expected to surrender before prison authorities on Friday, he said.

During the parole period, he was ordered to visit the Agripada Police Station everyday between 10.30 am and 12 pm to mark his attendance, he said.

However, Ansari did not visit the police station on Thursday during the designated time, the official said.

In the afternoon, his 35-year-old son Jaid Ansari approached the police station with a complaint about his “missing” father, he said.

According to the complaint, Jalees Ansari woke up in the early hoursand told family members he is going to offer namaz, but did not return home.

On his complaint, the Agripada Police registered a missing case, he said.

The Crime Branch of the Mumbai Police and the Maharashtra ATS have launched a massive manhunt to trace him, he said.

Jalees, who is known as Doctor Bomb, was allegedly connected with terror outfits like SIMI and Indian Mujahidin and taught terror groups how to make bombs, he said.

He was also questioned by the NIA in 2011 in connection with the 2008 bomb blast in Mumbai, he said.

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Agencies
July 11,2020

Citing the current dismal aviation scenario, Air India is terminating the services of trainee cabin crew and cabin crew by withdrawing the offer of employment of those who were under training.

As per sources, the new crew and trainee pilots might reduce contracts from five years to one year. Sources said Air India is terminating 1,200 crew and employees who are more than 55-yr-old including 190 trainee pilots.

In a letter reviewed by IANS, Air India has informed an applicant who had been selected as cabin crew in August 2019 subject to successful completion of training.

"On behalf of Air India we would like to thank you for the interest shown by you in joining our organization. However, in view of the current aviation scenario, it would not be possible for Air India to impart any further training to you for engaging your services," the company said.

"In view of the above reasons, which are beyond the control of the company, it has been decided to discontinue your training arrangements and dispense with the offer of engagement with immediate effect. The bank guarantee furnished by you at the time of joining is returned herewith," Air India told the cabin crew.

"Once again on behalf of Air India we thank you for your cooperation and trust that you will appreciate the circumstances under which we are constrained to discontinue the training arrangements," the carrier said.

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News Network
February 19,2020

Feb 19: Pay increases across India’s organized sector will probably grow at the slowest pace since 2009 this year, according to a survey from Aon Plc.

Companies will increase average pay by 9.1% in 2020, down from 9.3% in 2019 and 9.5% the previous year, Aon said in a report published Tuesday. The small increase reflects a deep slowdown in Asia’s third-largest economy, where growing pessimism about job prospects have led many to cut down on consumption -- the main driver to growth.

India still leads the Asia-Pacific region in pay rises, but that is mainly due to higher inflation and a “war for key talent and niche skills,” Aon said.

“There is a general air of caution about the economy as we enter into 2020,” Tzeitel Fernandes, partner for rewards solutions at Aon, told reporters in New Delhi. “Low GDP projection and weak consumer sentiment are the reasons behind our lowest ever prediction.”

E-commerce companies and start-ups will probably get the biggest salary increases, projected at an above-average 10%, while financial institutions will hand out 8.5%. Unsurprisingly, the auto sector witnessed the biggest drop in growth -- down to 8.3% from 10.1% in 2018, according to Aon. The survey covered more than 1,000 companies across over 20 industries.

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