<p>An investigation into manipulated Twitter traffic by a team of digital forensic analysts has raised concerns about the quality of online debate in India as it has unearthed how rival political parties are deploying automated Twitter 'bot' accounts on a massive scale ahead of the upcoming general elections. </p>.<p>The investigation undertaken by the Atlantic Council’s Digital Forensic Research Lab (DFRLab) showed that during the month of February, starting around Feb. 9-10, bots of "domestic origin" and “boosted hashtags” were deployed on a massive scale “in support of and in opposition to incumbent Prime Minister Narendra Modi, with small groups of accounts pushing out thousands of posts an hour”. </p>.<p>The investigation also said that “the pro-Modi traffic was far more heavily manipulated than the anti-Modi traffic”. The probe noted that while the volume of manipulated traffic was unprecedented, the impact of the bots was suspect and “muted”, due to the “relatively low number of followers of the accounts”. </p>.<p>It is, however, notable in terms of “sheer effort it represents”, argued DFRLab, adding that Twitter’s systems are designed to “detect large-scale automated efforts like this without necessarily suspending the accounts straight away.” The analysis by DFRLab used the Coefficient of Traffic Manipulation method, which allows researchers to compare given Twitter flow with known organic traffic and traffic that was heavily gamed by small groups.<br /><br /> </p>.<p>DFRLab elaborated on examples of manipulated Twitter trends like the hashtag ‘#TNwelcomesModi’ and the hashtag ‘#GoBackModi’. </p>.<p>#TNwelcomesModi references Modi’s visit to the southern state of Tamil Nadu. During Feb. 9–10, it was mentioned over 777,000 times in two days. A bot user identified as @SasiMaha6 was found to post #TNwelcomesModi tweets with maximum frequency — 1,803 times during the scan, or roughly one tweet every 15 seconds. Several of these bot accounts were suspended by Twitter. </p>.<p>Analysing more such accounts, DFRLab concluded that “these sustained rates are far too high for human posting.”</p>.<p>“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. In other words, almost two-thirds of the posts that initiated #TNwelcomesModi and pushed it to trend came from just 50 accounts. This was an attempt at manipulation on an industrial scale, using a small number of hyper-tweeting bots to give the hashtag a massive boost,” said the report. </p>.<p>Similarly, DFRLab also analysed the Congress’ Twitter bots who used the hashtag ‘#GoBackModi’ on Feb. 10, generating 447,000 posts on Feb. 9–10.<br /> <br />“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,” said the report. </p>
<p>An investigation into manipulated Twitter traffic by a team of digital forensic analysts has raised concerns about the quality of online debate in India as it has unearthed how rival political parties are deploying automated Twitter 'bot' accounts on a massive scale ahead of the upcoming general elections. </p>.<p>The investigation undertaken by the Atlantic Council’s Digital Forensic Research Lab (DFRLab) showed that during the month of February, starting around Feb. 9-10, bots of "domestic origin" and “boosted hashtags” were deployed on a massive scale “in support of and in opposition to incumbent Prime Minister Narendra Modi, with small groups of accounts pushing out thousands of posts an hour”. </p>.<p>The investigation also said that “the pro-Modi traffic was far more heavily manipulated than the anti-Modi traffic”. The probe noted that while the volume of manipulated traffic was unprecedented, the impact of the bots was suspect and “muted”, due to the “relatively low number of followers of the accounts”. </p>.<p>It is, however, notable in terms of “sheer effort it represents”, argued DFRLab, adding that Twitter’s systems are designed to “detect large-scale automated efforts like this without necessarily suspending the accounts straight away.” The analysis by DFRLab used the Coefficient of Traffic Manipulation method, which allows researchers to compare given Twitter flow with known organic traffic and traffic that was heavily gamed by small groups.<br /><br /> </p>.<p>DFRLab elaborated on examples of manipulated Twitter trends like the hashtag ‘#TNwelcomesModi’ and the hashtag ‘#GoBackModi’. </p>.<p>#TNwelcomesModi references Modi’s visit to the southern state of Tamil Nadu. During Feb. 9–10, it was mentioned over 777,000 times in two days. A bot user identified as @SasiMaha6 was found to post #TNwelcomesModi tweets with maximum frequency — 1,803 times during the scan, or roughly one tweet every 15 seconds. Several of these bot accounts were suspended by Twitter. </p>.<p>Analysing more such accounts, DFRLab concluded that “these sustained rates are far too high for human posting.”</p>.<p>“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. In other words, almost two-thirds of the posts that initiated #TNwelcomesModi and pushed it to trend came from just 50 accounts. This was an attempt at manipulation on an industrial scale, using a small number of hyper-tweeting bots to give the hashtag a massive boost,” said the report. </p>.<p>Similarly, DFRLab also analysed the Congress’ Twitter bots who used the hashtag ‘#GoBackModi’ on Feb. 10, generating 447,000 posts on Feb. 9–10.<br /> <br />“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,” said the report. </p>
