How shared partisanship leads to social media connections

It is no secret that U.S. politics is polarized. An experiment conducted by MIT researchers now shows just how deeply political partisanship directly influences peoples behavior within online social networks.

Deploying Twitter bots to help examine the online behavior of real people the researchers found that the likelihood that individuals will follow other accounts on Twitter triples when there appears to be a common partisan bond involved.

’When partisanship is matched people are three times more likely to follow other accounts back’ says MIT professor David Rand co-author of a new paper detailing the studys results. ’Thats a really big effect and clear evidence of how important a role partisanship plays.’

The finding helps reveal how likely people are to self-select into partisan ’echo chambers’ online long discussed as a basic civic problem exacerbated by social media. But methodologically the experiment also tackles a basic challenge regarding the study of partisanship and social behavior: Do people who share partisan views associate with each other because of those views or do they primarily associate for other reasons with similar political preferences merely being incidental in the process?

The new experiment demonstrates the extent to which political preferences themselves can drive social connectivity.

’This pattern is not based on any preexisting relationships or any other common interests — the only thing people think they know about these accounts is that they share partisanship and they were much more likely to want to form relationships with those accounts’ says first author Mohsen Mosleh who is a lecturer at the University of Exeter Business School and a research affiliate at the MIT Sloan School of Management.

The paper ’Shared Partisanship Dramatically Increases Social Tie Formation in a Twitter Field Experiment’ appears this week in Proceedings of the National Academy of Sciences. In additional to Rand who is the Erwin H. Schell Professor at the MIT Sloan School of Management and director of MIT Sloans Human Cooperation Laboratory and Applied Cooperation Team the authors are Mosleh; Cameron Martel a PhD student at MIT Sloan; and Dean Eckles the Mitsubishi Career Development Professor and an associate professor of marketing at MIT Sloan.

To conduct the experiment the researchers collected a list of Twitter users who had retweeted either MSNBC or Fox News tweets and then examined their last 3200 tweets to see how much information those people shared from left-leaning or right-leaning websites. From the initial list the scholars then constructed a final roster of

842 Twitter accounts evenly distributed across the two major parties.

At the same time the researchers created a set of eight clearly partisan bots — fake accounts with the appearance of being politically minded individuals. The bots were split by party and varied in intensity of political expression. The researchers randomly selected one of the bots to follow each of the 842 real users on Twitter. Then they examined which real-life Twitter users followed the politically aligned bots back and observed the distinctly partisan pattern that emerged.

Overall the real Twitter users in the experiment would follow back about 15 percent of Twitter bots with whom they shared partisan views regardless of the intensity of political expression in the bot accounts. By contrast the real-life Twitter users would only follow back about 5 percent of accounts that appeared to support the opposing party.

Among other things the study found a partisan symmetry in the user behavior they observed: People from the two major U.S. parties were equally likely to follow accounts back on the basis of partisan identification.

’There was no difference between Democrats and Republicans in this in that Democrats were just as likely to have preferential tie formation as Republicans’ says Rand.

The bot accounts used in this experiment were not recommended by Twitter as accounts that users might want to follow indicating that the tendency to follow other partisans happens independently of the account-recommendation algorithms that social networks use.

’What this suggests is the lack of cross-partisan relationships on social media isnt only the consequence of algorithms’ Rand says. ’There are basic psychological predispositions involved.’

At the same time Rand notes the findings do suggest that if social media companies want to increase cross-partisan civic interaction they could try to engineer more of those kinds of interactions.

’If you want to foster cross-partisan social relationships you dont just need the friend suggestion algorithm to be neutral. You would need the friend suggestion algorithms to actively counter these psychological predispositions’ Rand says although he also notes that whether cross-partisan social ties actually reduce political polarization is unclear based on current research.

Therefore the behavior of social media users who form connections across party lines is an important subject for future studies and experiments Mosleh suggests. He also points out that this experimental approach could be used to study a wide range of biases in the formation of social relationships beyond partisanship such as race gender or age.

Support for the project was provided in part by the William and Flora Hewlett Foundation the Reset project of Luminate and the Ethics and Governance of Artificial Intelligence Initiative.


Modern Online Shopping: A Comprehensive Guide to Maximizing Savings with Coupons


The Mysteries of CEFR: A Guide to Understanding English Proficiency Exams


Lee Lakosky Net Worth, Age and relationsips with Tiffany


Ultimate Guide to Finding Your Dream Flat in Dubai's Real Estate Market


Escape room puzzles and props: Top-10 ideas


Disposable emails and phone numbers: are they a threat?


Boosting Your Crypto Presence: The Benefits of Hiring a Crypto PR Firm


Why is Maternity Photography so popular on Social Media


Family counseling approach research paper assignment


How a car sharing service works


How to use Chat GPT to write an essay


Incorporating in British Virgin Islands


Abortion in Texas essay


Dartmouth introduce yourself essay


Why is the veteran important essay


Abortion pros and cons essay


Essay about Mexico


College essays about immigrant parents


Writing a narrative essay about being judged


Writing an argumentative essay about the nobel prize in literature


An essay about the differences between tomatoes and corn


Argumentative essay about abortion


Writing a research-based informative essay about the benefits of humor


College essay about music


Essay about suicidal


Argumentative essay on stem cells


Orderliness essay


Why abortion should be banned essay


ChatGPT: how it impacts business and social media


Choosing a game server


3 reasons to open a small business


Classic 1972 Ford F 250: social media star