#Purple Feed: Identifying High Consensus News Posts on Social Media
- Users play a role to select their sources for information as opposed to the past.
- Many users limit themselves to news stories that reinforce their views.
- This leads to a more politically fragmented, less cohesive society.
- There are systems to promote blue information for red users and viceversa but users do not like them.
- Purple news are news with high consensus of reader reactions. Hopefully these evoke a more unified response across society which might help to understand each other.
- "high consensus if there is a general agreement in readers' reaction despite readers' political leaning"
- consensus = abs((democrats disagree/number of democrats) - (republicans disagree/number of republicans))
- Mechanical turk used to measure consensus from WSJ blue/red feed and Twitter top 10 publishers.
- Confirmed that political extremes tend to pick lower consensus content.
- Count Retweets to measure popularity. High consensus (158) and low consensus (177) on avg. Similar engagement.
- Do they cover similar or different topics? Consensus seems to cover non-US centric political topics.
- High cross-cutting exposure: # opposite leaning retweeters > baseline of opposite leaning retwitters for a publisher
- Clearly high consensus correlates with high cross cutitng exposure
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Features found
- followers - on avg 67% are of the same political leaning
- retweeters - active supporters, 78% of the same politicall leaning
- repliers - 35% are of opposite political leaning
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Use Kulshrestha et al 2017 to measure political leaning in [-1, 1]
- Supervised learning using ground truth from the AMt dataset. Used SVM, Naive Bayes, Logistic Regression and Random forest.
- Pruned insignificant features and used 5-fold cross validation.
- Accuracies near 60/70% for predicting consensus.
- Publisher-based features are better than tweet-based features. Poor performance due to short size of tweet.
- 74% of high consensus posts identified, 70% of low consensus.
- We propose a complementary approach to inject diversity in users news consumption.
- First attempt at operationalizing consensus of news posts on social media.
- Deployed 'purple feed', a system to highlight high consensus posts.
- Possibilities to study further evaluating the impact of showing high consensus posts on social media.