Analysis: I don’t blame China, I blame the incompetence of past Admins...

8y ago Nov 9, 2017 at 11:39 PM

I don’t blame China, I blame the incompetence of past Admins for allowing China to take advantage of the U.S. on trade leading up to a point where the U.S. is losing $100's of billions. How can you blame China for taking advantage of people that had no clue? I would've done same!

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AI Analysis

Machine-generated analysis of the post above on 2026-03-12. Not written by the author of the post.

Danger Level

None

Narcissistic State

Grandiose

Authorship

Self-Written

Intensity

45%

Authorship Analysis

Self-Written

Indicators:

Conversational rhetorical question
Colloquial phrasing ('people that had no clue')
Self-insertion ('I would've done same!')
Early morning Beijing time posting
Stream-of-consciousness quality

Psychological Profile

▶ State

Grandiose State

Trigger: Supply Seeking (State visit to China, desire to maintain positive relationship with Xi while asserting own superiority)

Sentiment

-0.15

▶ Clinical

Malignant Narcissism:

Narcissistic

60%

Antisocial

40%

Paranoid

10%

Sadism

20%

Defense Mechanisms:

splittingidealizationdevaluation

Cognitive Complexity:

Complexity

55%

Parasocial Techniques:

Rhetorical question engaging audience as co-reasonersCommon-sense framing to build consensus

Fact Checks (1)

"U.S. is losing $100's of billions on trade with China"

Mostly True

The 2017 U.S. goods trade deficit with China was approximately $375 billion. The phrasing '$100s of billions' is roughly accurate for goods, though economists note trade deficits are more complex than simple 'losses.'

Receipts

No contradictions with other posts detected yet.

Psychological Analysis: Post x_928769154345324544

Context

Trump is in Beijing during his state visit to China (November 9, 2017). The post timestamp is 23:39 UTC, which is approximately 7:39 AM local time in Beijing (UTC+8). This is early morning, consistent with authentic Trump posting.

Authorship

The post reads as authentic Trump. Key indicators: conversational stream-of-consciousness style, rhetorical questions, colloquial phrasing ("people that had no clue"), the characteristic self-insertion ("I would've done same!"), and the contrarian framing that simultaneously flatters his host (Xi) while attacking predecessors.

Psychological Dynamics

This is a fascinating post because it performs multiple psychological functions simultaneously:

Flattery of Xi/China — While visiting Beijing, Trump explicitly exonerates China for exploitative trade practices. This is strategic narcissistic supply-seeking: by praising his host, he secures reciprocal admiration.
Attack on predecessors — The real target is "past Admins" (Obama, Bush, Clinton). This elevates Trump by contrast: they were incompetent, he is not.
Identification with the aggressor — "I would've done same!" is remarkable. Trump identifies with China's exploitation, admiring the predatory behavior and implicitly claiming he possesses similar cunning. This reveals a transactional, zero-sum worldview where exploitation is admired rather than condemned.
Projection of competence — By framing predecessors as having "no clue," Trump implicitly claims superior negotiating acumen.

Defense Mechanisms

Splitting: Past admins = all bad, incompetent; Trump = competent, savvy
Idealization: China/Xi idealized during the visit (contrast with later rhetoric)
Projection: Incompetence attributed entirely to others

Rhetorical Analysis

The post uses a rhetorical question ("How can you blame China...?") to make the argument feel self-evident. The $100s of billions figure is hyperbolic but grounded in real trade deficit numbers. The closing exclamation personalizes and dramatizes.

Fact Verification

Claim	Verdict	Evidence
"U.S. is losing $100's of billions on trade with China"	Mostly True	The 2017 U.S. goods trade deficit with China was approximately $375 billion. The phrasing '$100s of billions' is roughly accurate for goods, though economists note trade deficits are more complex than simple 'losses.'

Overall Veracity: 80%