This newsletter is published at techpolicy.substack.com
What is this?This newsletter aims to track information disorder largely from an Indian perspective. It will also look at some global campaigns and research
What this is not?A fact-check newsletter. There are organisations like Altnews, Boomlive etc who already do some great work. It may feature some of their fact-checks periodically
Welcome to Edition #7 of MisDisMal-Information.
Sorry for the delayed edition this week.
Once a day, I take a look at Twitter trends to see which hashtags are competing with each other for the trendalympics. I’ve never been sure what it achieves, but it is a mainstay of the Twitter experience nevertheless. Last week, a very curious phrase was trending on Twitter – ArrestSwaraBhaskar. This seemed to occur in the aftermath of Safoora Zargar’s bail petition being denied. Proponents of this trend wanted to Swara Bhaskar to be arrested as well, for a tweet in late January calling for Delhi to ‘get on the streets’. But you probably know this already. On Jun 6th, I was able to pull up around 30000 tweets, around the time it was trending at 1 (congratulations?). I also looked at a subset which contained around 35-40 ‘charged’ words. I won’t post them here, since this is a family newsletter but I am open to share the spreadsheet with anyone who is interested if you swear an oath not to reveal anyone’s personal data.
There was consistency across both the datasets, more than I expected. And there seemed to be no other obvious tell-tale signs of coordinated activity like I saw with male nurses hashtag last week. Other than the obvious one that it was trending at no.1 in a matter of hours.
First, let’s look at a spread of users by activity. Note that left axis corresponds to the green line (number of tweets). As you can see, the pattern is pretty consistent.
Next, the percentage of tweets by when the user accounts were created.