This is a liveblog of Lada Adamic's plenary keynote from Political Networks 2014.
When your friends deliver the news
Lada Adamic is a Data Scientist at Facebook and former associate professor at the University of Michigan's School of Information. Her talk is entitled "When your friends deliver the news." Using studies based on Facebook data, she invites us to think about factors of social networks that affect the spread of information.
She opens with a set of questions and concerns raised by the idea of your talk's title: what happens when your friends deliver the news through what they share on Facebook...
- How is your exposure affected? (Your friends are not a random sample of the population nor are they mainstream media journalists.)
- Does it affect political engagement? (How interested you are or likely to vote.)
- What do social movements look like? How does success propagate?
- How does any information spread, is it predictable?
- Is it reliable?
Lada shows us the top five most shared stories from a year ago (i.e. June 2013):
- Drowning doesn't look like drowning (Slate)
- Boy's death highlights a hidden danger: Dry drowning (Today Show piece containing substantial misinformation)
- 22 Maps that Show how american speak English totally different from one other (Business Insider maps that were later integrated in the most read NYT story of 2013)
- Edward Snowden: the whistleblower behind the NSA surveillance revelations (The Guardian)
- 8 Foods we eat in the us that are banned in other countries (Buzzfeed)
She tells us that women in their 40s read the drowning pieces, whereas men in their 20s read the Snowden piece. There are definitely clusters of people more likely to read certain stories. But Lada asks: Is there a filter bubble? Do we get echo chambers, especially across political lines?
Using information from users' profile pages, Lada and team members rated what people's political leanings were: very liberal, moderately liberal, moderately conservative, very conservative. And they coded the different news sites by what was read by users of certain political leanings: from ThinkProgress on the far Left to FoxNews on the far right. They found that content skews liberal in aggregate over Facebook even though ideology is balanced. There is simply more liberal content shared by all users on the network. Lada cites Duncan Watts' Friend Sense app research, and asks: Can we understand what the egonetwork of a conservative looks like?
People's friends aren't exclusive to their political beliefs. They found that the distribution of friendships skews toward their own political leaning but still retains some balance across the spectrum. Then they looked at the interactive patterns between users and news across the political spectrum, breaking them down into four buckets of user-news interaction:
- Potential: all of the news your friends are sharing
- Exposed: what showed up in your news feed (balanced diet of liberal and conservative for conservative users)
- Selected: what was clicked on (no effect, they were clicked on in proportion to what showed up in feed)
- Endorsed: what is liked this is where the difference exists, conservatives are much less likely to endorse liberal news
They found that endorsement was the key difference between users of conservative versus liberal ideology. Conservative users were significantly less likely to endorse liberal news, even though they were served and even clicked to read liberal news at similar rates to the liberal users.
Research by Solomon Messing and Eytan Bakshy looked at and experimented with activity on Facebook prior to the 2012 election.
The treatment involved adding more political news in certain users' news feeds. (Edit: Lada later clarified to me that the treatment involved adding more news content of all kinds to certain users' news feeds, not just political news. - EG, Oct 29 2014) They found that people reported being more interested in politics and government when, unbenkownst to them, they were getting more news in their feed. There was a greater effect for users that don't log in everyday, since people who log in everyday are more likely to read everything. The treatment group also reported they were more likely to vote, with a stronger effect again on less regular users.