INDIA and Pakistan have fought four wars in the past decades, but when India faced the deadly second wave of Covid-19 and resulting oxygen shortage, Pakistan put aside the bitterness and prayed for its recovery, says a recent AI study, claiming that 85 per cent of tweets from Pakistan during the peak of India’s second wave were supportive.
As India struggled with a ferocious second wave of Covid-19, social media users from the either side of the border were seen putting aside their differences in favour of supportive hashtags like #IndiaNeedsOxygen and #PakistanStandsWithIndia.
While hijacking a hashtag to propel opposite ideas or simply to dilute the agenda is quite a common practice on social media, an AI-enabled research done by Carnegie Mellon University’s Language Technologies Institute found that this time, the sentiment in Pakistan-origin tweets were of support and hope for India.
Studying more than 55, 000 tweets from Pakistan posted between April 21 and May 4, the research said in their paper titled, "Empathy and Hope: Resource Transfer To Model Inter-country Social Media Dynamics," that most of them were indeed positive.
Led by Ashique R. KhudaBukhsh of Carnegie Mellon University, the researchers ran the text from these tweets into a "hope speech classifier" - a language processing tool that helps detect positive comments, looking for the text that had "hostility-diffusing positive hope speech", or words like prayer, empathy, distress and solidarity.
More than 85 per cent of the tweets posted about the Covid crisis in India from Pakistan were supportive, the research found, adding that the tweets containing supportive hashtags originating in Pakistan heavily outnumbered those containing non-supportive hashtags and also had substantially more likes and retweets.
"We showed that there is some sort of universality in how we express emotions," KhudaBukhsh said. "And we showed that we can use existing solutions, combine them and attack future crises quickly.
KhudaBukhsh also claimed that hope-speech classifier can be an alternative way to combat hate speech. Instead of detecting and deleting, downplaying or blocking hate speech — which exists in droves on the internet — the researchers said that their hope-speech classifier can be used to identify and amplify supportive messages.
Adding that people are influenced by what they see and read, Khuda Bukhsh said that their method of identifying and amplifying positive messages can help boost public morale and improve relations between communities and countries.
"These two countries have such an acrimonious past," KhudaBukhsh said. "Any positive behavior from either side can help promote world peace."
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