As opposed to lying by, you know, lying? If it's made by your "think" tanks, sure.
The graph was made by Ad Fontes, the exact same source of data used for your Twitter analysis.
To reduce subjectivity in our classification of political content, we leverage two independently curated media bias rating datasets from AllSides and Ad Fontes Media, and present results for both. Both datasets assign labels to media sources based on their perceived position on the U.S. media bias landscape.
- Your own source, page 5
You have to decide if it’s reliable and your rebuttal is sound or unreliable and your rebuttal is trash. It can’t be both simultaneously, it’s the same dataset. For the record, AllSides reached a similar conclusion when analysing media outlets, their classification is almost identical. In fact, it’s even more scathing in regards to CNN, NYT and MSNBC, classifying them as having a strong bias to the left. To reiterate, I claimed that most media outlets that are considered mainstream are left-leaning, and both sources support that statement.
Is addressed and confirmed: despite their claims of censorship right-wingers enjoy far more coverage than others.
Algorithmic boosting has a strong preference towards popular tweets - it’s designed to do that. The left needs to learn how to tweet better.
EDIT: I forgot to mention that The Guardian is a rag and presented the results of the study dishonestly. I quote:
We presented a comprehensive audit of algorithmic amplification of political content by the recommender system in Twitter’s home timeline. Across seven countries we studied, we found that mainstream right-wing parties benefit at least as much, and often substantially more, from algorithmic personalization as their left-wing counterparts. In agreement with this, we found that content from U.S. media outlets with a strong right-leaning bias are amplified marginally more than content from left-leaning sources. However, when making comparisons based on the amplification of individual politician’s accounts, rather than parties in aggregate, we found no association between amplification and party membership.
Our analysis of far-left and far-right parties in various countries does not support the hypothesis that algorithmic personalization amplifies extreme ideologies more than mainstream political voices. However, some findings point at the possibility that strong partisan bias in news reporting is associated with higher amplification. We note that strong partisan bias here means a consistent tendency to report news in a way favouring one party or another, and does not imply the promotion of extreme political ideology.
tl;dr Right-wing sources are boosted about as much, and sometimes more than left-wing sources. Party affiliation has no impact on amplification of politicians and extreme content isn’t amplified. Strong bias in the content seems to have a direct result on amplification. In other words, biased content that appeals to users is boosted more, and right-wingers are marginally better at curating their own feeds. Marginally. People listen to whatever reinforces their views the most. This isn’t a scathing indictment, it’s a defense against accusations in regards to deboosting at best (that’s the reason why the study was conducted in the first place, as a defense, and that makes it questionable from the get-go). The results are entirely explainable.
