Many have expressed skepticism about calls for healing and #depolarization over the past few days. But what does the latest research indicate about the prospects for reconciliation? Let’s look at the #SocSciResearch...1/9
An experiment that asked Democrats and Republicans to discuss politics in person for just 15 minutes improved their attitudes towards each other by *70 percent* compared to a control group. See @m_levendusky ‘s forthcoming book “Our Common Bonds” 2/9
Brief cross-party conversations seem to be effective even if they occur on an online chat platform created to pair partisans to discuss controversial topics (~9 point increase on a 0-100 point “feeling thermometer”. See @erinrossiter’s job market paper (then hire her ;) 3/9
Most people overestimate how negative cross-party contact will be, and people who engage in brief contact tend to want more of it later. See multiple recent papers by @JuliaMinson and co-authors 4/9
Contact with members of the other side might not even be necessary to reduce polarization. Simply correcting misperceptions Dems and Reps have about each other can create significant reductions in polarization as well (see the work of @profcikara, Ahler and Sood, and others) 5/9
This is still an emerging line of research MUCH more work must be done. But new stuff from our @polarizationlab reinforces findings above and gives further grounds for hope about not only inter-group attitudes but #depolarization in policy opinions as well (paper soon). 6/9
In the meantime, if you are appalled by how people are acting on social media right now (or the past few years), remember that ***social media is not real life*** and polarizing elites *want* you to attack their poor behavior during this critical juncture in our democracy. 7/9
NO ONE should ever feel compelled to reach across the aisle— and many wounds are too deep to heal. Debates about moral relativism will (and should) play out. But will the battle for the senate depend upon mobilization alone given historic voter registration rates in GA? 8/9
Regardless of where you stand on the prospect of #depolarization, I hope we will continue to share research to inform the debate (especially any studies I’ve overlooked by those whose voices are not yet part of the conversation) 9/9
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1/n Are you a *complete beginner* in computational social science who wants to learn how to code? I'm happy to announce our new "coding bootcamp" video tutorials for the Summer Institutes in Computational Social Science: compsocialscience.github.io/summer-institu…
2/n I cover everything from setting up Rstudio to data cleaning (and "wrangling"), visualization, programming, modeling, communicating (w/Markdown, Rpres, and Shiny) as well as collaboration w/Github
3/n Though there are MANY great intro tutorials out there, this one is designed with computational social scientists in mind-- it offers examples w/ Twitter data, mobility data for COVID-19, and data about the opioid crisis.
1/n How do computational social scientists land non-academic jobs? I asked this question to a panel of senior leaders in for-profit and non-profit companies on a wonderful webinar yesterday, and I’d like to share what I learned:
2/n The cadence of non-academic work is very different. Academics like to take their time developing the perfect research design, but in other settings, people need answers, fast. Also, many academics are used to working alone, whereas most non-academic work is team-based.
3/n You need a good elevator pitch—one that makes it immediately clear how you can add value to a business or organization, BUT
1/n Did Russian trolls actually influence the attitudes and behaviors of U.S. social media users? Our Polarization Lab’s new article suggests the answer might be “no” pnas.org/content/early/…
2. Many people think Russian trolls exerted strong influence upon U.S. social media users because of the sheer scale and apparent sophistication of their techniques. There is also anecdotal evidence that IRA accounts succeeded in inspiring American activists to attend rallies.
3. Though many studies have analyzed the content and strategy of these campaigns, to our knowledge, no studies have examined whether they actually shaped the attitudes or behaviors of large groups of U.S. social media users.
1/5 Interested in learning how to collect and analyze social media data using topic models, text networks, or word2vec? I'm pleased to announce I am releasing an open source version of my "Text as Data" class from Duke's Data Science program: cbail.github.io/textasdata/Tex…
2/5 The course website (above) includes tutorials on a range of subjects with annotated R code. The class assumes basic knowledge of R and describes the techniques we use in the @polarization lab to run studies like this: pnas.org/content/115/37… and this: pnas.org/content/113/42…
3/5 All datasets used in the tutorials are hosted on my Github site, which also includes all source files for the tutorials themselves: github.com/cbail
1/8 Did you know that Twitter is experimenting with new features that would expose its users to opposing political views? In this @nytimes piece, I describe why this idea could backfire based upon a large online experiment recently conducted by my lab: nyti.ms/2Nu45gL
2/8 We surveyed, 1,225 Republican and Democratic Twitter users about their views on social policies. One week later, we offered them money to follow a Twitter account which they were told would tweet 24 times each day for one month. They were not told what the bots would tweet.
3/8 The Twitter account gradually began tweeting messages from politicians, media organizations, and advocacy groups with opposing political views. We tracked whether people paid attention by asking them questions about these messages.