The Indraprastha Institute of Information Technology (IIIT) Delhi’s Laboratory for Computational has launched “Project Robinhood” which will track content on the microblogging site Twitter related to the 2022 Indian Assembly elections.
Based on the data collected so far, the team found that Uttar Pradesh, Delhi and Uttrakhand reported the highest number of hateful content – as geotagged by the tweets. Members of the project include Drishya Uniyal, a master’s student, Sarah Masud, a PhD student, and Dr. Tanmoy Chakraborty, assistant professor.
Most politicians’ leaders and their affiliates use social media platforms to share updates on their political campaigns during elections. They make announcements about contesting candidates and even criticize members of other competing parties, the students say. “To analyze such language patterns from the point of view of hateful content, members of LCS2 at IIIT-Delhi launched Project Robinhood,” she added.
The project maintains content on the Twitter platform of the Assembly Elections 2022 and collects information from January to March. To share the insights with a wider audience, the team has launched a portal that provides aggregated and detailed statistics on the different groups of users generating political hatred and the groups it targets. This information is further analyzed at the state level.
Data collection for the project began in January 2022, starting with 50 political leaders from five major parties: BJP, INC, BSP, SP and AAP. In addition, the official state-wise Twitter handles of these parties are also kept. Based on the data collected so far, the team found that Delhi and Uttrakhand reported the second highest rate of hateful content after Uttar Pradesh. “This is an interesting observation as Delhi is the hub for 3 of our major parties (BJP, INC and AAP). Despite not holding elections, Delhi still produces a significant number of politically hateful tweets,” the students said.
Another observation of the team is that direct attacks in political parties prevail over attacks on individual politicians. The students attributed this to calling out the name of the party and creating more involvement from the opposing party and ordinary citizens. Around the end of January, there was an increase in hateful content analyzed by the team, which was due to the political rally held in Punjab around the same time.
Furthermore, the team expects that as the frequency of physically coordinated meetings increases, the influx of political hatred on Twitter will increase. The ongoing data curation for February will likely reveal those insights, they say, adding that the portal’s aggregated and daily stats are regularly updated.
“On the basis of the data collected so far, it can be said that no political leader or organization is guilt-free when it comes to engaging in hateful dialogue. While some leaders are more explicit in their utterances, others prefer to taunt. Despite the best efforts of the Election Commission and strict scrutiny by social media platforms, these expressions of political hatred continue to evade the online platforms,” the students told News18.com.
A small percentage of ordinary citizens initiate and participate in most trending political hashtags. These opinions, while trending, do not reflect democratic opinion. Voters need to be educated and informed to read these trending hashtags, she added. “We strongly believe that both politicians and ordinary citizens need to be sensitized about the quality of the political discourse that we want to enable on the social platforms and that we need to be trained in the ethical handling of political expressions,” the students said. of IIIT Delhi.
To analyze the different categories of political attacks and hate, the team had to iteratively analyze and formalize the content as directly or indirectly hateful. Direct attacks specifically mentioned a political party or a politician. While indirect attacks in the form of taunts do not name a party or person but contain contextual evidence of political hatred. In addition, some of the hateful content was religious and not political in nature. Given India’s long history of politics and religion, the team added religious attacks as an additional category of damage,” the team concluded.
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