Nature: Forecasting the onset and course of mental illness with Twitter data

Nature: Forecasting the onset and course of mental illness with Twitter data. “We developed computational models to predict the emergence of depression and Post-Traumatic Stress Disorder in Twitter users. Twitter data and details of depression history were collected from 204 individuals (105 depressed, 99 healthy). We extracted predictive features measuring affect, linguistic style, and context from participant tweets (N = 279,951) and built models using these features with supervised learning algorithms. Resulting models successfully discriminated between depressed and healthy content, and compared favorably to general practitioners’ average success rates in diagnosing depression, albeit in a separate population.”

Medium: One person’s history of Twitter, from beginning to end

Medium: One person’s history of Twitter, from beginning to end. “On November 8, 2008 I watched Barack Obama win the presidency of the United States while I was sitting on Twitter’s office couch. I forget who invited me, but I was excited to be there because this felt like the first presidential election that the internet had an active part in. Whatever that meant. It felt like all of the tools the web community had spent the last ten years or more building had actually culminated in this moment. And I sat on that couch crying. I was getting to see this moment as a guest in the place that got all of these voices communicating. And all of those voices helped elect a president. In 2008 I thought Twitter helped elect a president. I was off by eight years.”

Tweeting rage: How immigration policies can polarize public discourse (U of Washington)

University of Washington: Tweeting rage: How immigration policies can polarize public discourse. “To René D. Flores, an assistant professor of sociology at the University of Washington, Twitter is a trove of insight into people’s beliefs and their willingness to express them. By analyzing tweets in the months before and after the 2010 passage of the controversial Arizona law, Flores found that the average tweet about Mexican immigrants and Hispanics, in general, became more negative. Social media data, Flores found, was useful in determining whether people had changed their attitudes about immigrants as a result of the law or whether they had begun behaving differently.”

New York Magazine: Twitter Should Stop Pretending

New York Magazine: Twitter Should Stop Pretending. “Twitter has a bad habit of losing itself deep inside the rabbit hole of its own rules, and its attempts at unthinking, both-sides consistency tend to make them seem all the more weak and arbitrary. The platform is rife with stories from people who’ve been harassed or threatened in ways that would seem to specifically violate the terms of service, but whose reports fell on deaf ears.”

New York Times: A Bot That Makes Trump’s Tweets Presidential

New York Times: A Bot That Makes Trump’s Tweets Presidential. “With a single burst of tweets, President Trump can fire and hire a chief of staff, bar transgender soldiers from the military and undercut negotiations with foreign nations. It’s ‘diplomacy by tweeting,’ said Russel Neiss, a software engineer for an educational technology nonprofit.”

Trump’s lawyers: Courts have no say over his Twitter feed (Daily Collegian)

Daily Collegian: Trump’s lawyers: Courts have no say over his Twitter feed. “President Donald Trump can block his critics from following him on Twitter without violating the First Amendment despite a lawsuit’s claims that it violates the Constitution to do so, government lawyers say. Trial attorneys with the U.S. Department of Justice in Washington submitted papers late Friday to a New York federal judge, saying a lawsuit challenging Trump over the issue should be thrown out.”

Bloomberg: Twitter Is Crawling With Bots and Lacks Incentive to Expel Them

Bloomberg: Twitter Is Crawling With Bots and Lacks Incentive to Expel Them. “On Wednesday, the exterior of Twitter’s San Francisco headquarters bore an eerie message: ‘Ban Russian Bots.’ Someone— the company doesn’t know who— projected the demand onto the side of its building. Bots, or automated software programs, can be programmed to periodically send out messages on the internet. Now Twitter is scrambling to explain how bots controlled by Russian meddlers may have been used to impact the 2016 president election.”