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.
4/8 Instead of reducing political polarization, our intervention INCREASED it. Republicans who followed our bots became substantially more conservative. Democrats became slightly more liberal, but this effect was not statistically significant.
5/8 We think this happened because people experience cognitive dissonance when they are exposed to opposing views and begin to think about all the different reasons why they disagree with them, leaving them with even more reasons to reject opposing views.
6/8 Our study DOES NOT bringing Democrats and Republicans into conversation with each other is inherently doomed. Studies tell us intergroup contact is only effective if it is mostly positive and especially when people are cooperating to solve shared problems (i.e. not Twitter)
7/8 But we also can’t move all attempts to reduce political polarization offline. Social media is now the preferred medium for political discussion for too many people, and particularly young people.
8/8 Instead of leaving social media, we should try to fix it. I founded the @polarizationlab @DukeU to develop tools that combine machine learning, network analysis, and natural language processing to help people rewire their social media networks and find common ground
Ps thanks to @GuggFellows @CarnegieCorp @RussellSageFdn for funding this and @dukeu @DukeNewsT @ASAnews for promoting our research.

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More from @chris_bail

Dec 21, 2021
1/4 Do you want to learn computational social science (for free) and start research projects with scholars from many different fields? The Summer Institutes in Computational Social Science (sicss.io) will run in *THIRTY-ONE* locations around the world in 2022!!!!
2/4 Though many 2022 #SICSS locations hope to run in-person, some will be virtual institutes at a variety of exciting institutions as well. For a full list of sites, see sicss.io (where details about each institute will be posted in the very near future)
3/4 If you are unable to attend one of our 2022 locations, stay tuned for our all new digital curriculum, which will feature video tutorials from dozens of leading scholars in a searchable video database hosted on sicss.io
Read 4 tweets
Aug 10, 2021
YouTube's algorithm is *not* radicalizing people according to a study by leading scholars that examined 29 million YouTube viewing sessions and recently appeared in a prestigious peer reviewed journal: pnas.org/content/118/32…
There is more research/work to be done (especially with experimental designs and on other platforms), but this is the most comprehensive and careful analyses I've yet seen by @homahmrd @aaronclauset @duncanjwatts @markusmobius @DavMicRot and Amir Ghasemian.
And to be clear this does not indicate there are not major issues with extreme content on YouTube (and other platforms)... only that the algorithm does not seem to be the most likely culprit for producing extremism.
Read 6 tweets
Mar 23, 2021
1/ Do you feel hopeless about political polarization on social media? Introducing a new suite of apps, bots, and other tools that you can use to make this place less polarizing from our Duke Polarization Lab: polarizationlab.com/our-tools
One of the biggest problems with social media is that it amplifies extremists and mutes moderates, leaving us all feeling more polarized than we really are. Our tools can help you avoid extremists and identify moderates with whom you might engage in more productive conversations.
The Duke Polarization Lab’s Bipartisanship Leaderboard identifies politicians, celebrities, activists, journalists, media outlets, and advocacy groups whose posts get likes from people in both parties: polarizationlab.com/bipartisanship… Image
Read 13 tweets
Nov 9, 2020
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
Read 9 tweets
Sep 9, 2020
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.
Read 7 tweets
Jun 26, 2020
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
Read 6 tweets

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