Recent quotes:

Confessions of an Instagram Influencer - Bloomberg

That night, I signed up for a service recommended to me by Socialyte called Instagress. It’s one of several bots that, for a fee, will take the hard work out of attracting followers on Instagram. For $10 every 30 days, Instagress would zip around the service on my behalf, liking and commenting on any post that contained hashtags I specified. (I also provided the bot a list of hashtags to avoid, to minimize the chances I would like pornography or spam.) I also wrote several dozen canned comments—including “Wow!” “Pretty awesome,” “This is everything,” and, naturally, “[Clapping Hands emoji]”—which the bot deployed more or less at random. In a typical day, I (or “I”) would leave 900 likes and 240 comments. By the end of the month, I liked 28,503 posts and commented 7,171 times.

Instagram photos reveal predictive markers of depression

Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Statistical features were computationally extracted from 43,950 participant Instagram photos, using color analysis, metadata components, and algorithmic face detection. Resulting models outperformed general practitioners' average diagnostic success rate for depression. These results held even when the analysis was restricted to posts made before depressed individuals were first diagnosed. Photos posted by depressed individuals were more likely to be bluer, grayer, and darker. Human ratings of photo attributes (happy, sad, etc.) were weaker predictors of depression, and were uncorrelated with computationally-generated features. These findings suggest new avenues for early screening and detection of mental illness.