Apple, Google news algorithms on Michigan Senate hopeful Abdul El-Sayed, study says

framing by emphasis: The sentence frames the absence of negative headlines as a potential problem, implying bias by omission without establishing whether negative coverage was warranted or proportionate.

“displayed no negatively framed headlines about progressive Michigan Democratic Senate candidate Abdul El-Sayed”

vague attribution: The study is attributed generically without specifying methodology details in this sentence, setting up later critique.

“according to a Media Research Center study published Friday”

editorializing: Bozell's statement is presented as a warning without counterbalance, implying algorithmic suppression of truth.

“could leave voters without a complete picture of a candidate”

fear appeal: Implies passive consumption of curated content leads to voter manipulation, stoking concern about media control.

“They open Apple News or Google News and read what’s presented to them”

selective coverage: Highlights exclusion of right-leaning stories without assessing their quality or representativeness, framing omission as bias.

“identified at least 104 stories from right-leaning outlets about El-Sayed's record, statements and policies that did not appear in the feeds”

source asymmetry: Emphasizes right-leaning sources without equivalent mention of left-leaning omissions, creating imbalance.

“104 stories from right-leaning outlets”

misleading context: Presents methodology without acknowledging limitations such as keyword dependence and lack of personalization controls.

“used sentiment analysis to classify relevant headlines as negative, neutral and positive”

cherry picking: Acknowledges methodological flaws but only after establishing the narrative, minimizing their impact.

“The methodology examined one morning snapshot rather than every story available throughout the day”

vague attribution: Points out internal inconsistencies in the MRC report without challenging its overall credibility.

“The report also cited 13 stories from left-leaning and other outlets in one section but placed the total at 16 later in the report”

narrative framing: Uses Platner’s disqualification due to serious allegations to imply El-Sayed’s controversies are similarly grave, creating false equivalence.

“Platner was forced to exit the race after a rape accusation from a former girlfriend that was the latest of numerous scandals and controversies during his candidacy”

false equivalence: Equates El-Sayed’s policy controversies with Platner’s criminal allegations, distorting severity.

“did not feature more than 250 stories covering controversies involving Michigan Senate candidate Abdul El-Sayed and Maine Senate candidate Graham Platner”

cherry picking: Cites disproportionate left/right outlet representation without context on editorial standards or audience reach.

“69% of the outlets featured in Google News’ top news selections were left-leaning, compared with just 3% that were right-leaning”

editorializing: Presents Bozell’s interpretation as neutral observation, framing algorithmic curation as inherently suspect.

“raised questions about whether the platform was giving users a comprehensive view”

glittering generalities: Uses vague, positive-sounding terms like 'comprehensive' to imply deficiency without proof.

“Google News presents itself as a comprehensive news product”

fear appeal: Suggests users are being deceived, fostering distrust in tech platforms.

“should not have to wonder whether major, newsworthy reporting about candidates is being left out”

editorializing: Repeats the framing of doubt without offering evidence that omissions were material or intentional.

“raise serious questions about whether Google News is providing users with the complete picture”

loaded labels: Labels Hasan Piker as 'far-left streamer' to delegitimize association.

“campaigning with far-left streamer Hasan Piker”

moral framing: Lists policy positions in a way that frames them as extreme without context.

“support for Medicare for All, abolishing ICE and shifting funding away from police departments”

decontextualised statistics: Presents El-Sayed’s quote without specifying the context of the Israel-Hamas conflict or casualty figures, risking misinterpretation.

“"Yes, killing tens of thousands of people makes you pretty damn evil," El-Sayed said”

narrative framing: Reinforces the idea of systemic bias by linking two studies without independent verification.

“failed to promote at least 112 stories scrutinizing Platner”

single source reporting: Google's rebuttal is included but only in response to Platner, not El-Sayed, creating imbalance.

“These claims are totally false and based on a completely flawed methodology”