Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Financial markets/investors
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Reducing a complex situation with many contributing factors to a simpler, single-cause explanation.
“European shares fell, extending this week’s selloff on renewed trade-war tensions as focus turns to US President Donald Trump’s scheduled trip to the World Economic Forum in Davos.” “Markets have been rattled this week by the latest threats from Trump on countries that have opposed his demand for Denmark to hand over Greenland to the US.” These sentences imply a relatively direct, dominant causal link between Trump-related political developments and the market selloff, without acknowledging other possible drivers (macro data, earnings, sector-specific news, global risk sentiment, etc.).
Qualify the causal language to reflect uncertainty and multiple factors, e.g.: “European shares fell, extending this week’s selloff. Traders cited renewed trade-war tensions and attention on US President Donald Trump’s scheduled trip to Davos among several factors weighing on sentiment.”
Similarly adjust: “Markets have been rattled this week, with analysts pointing to the latest threats from Trump on countries that opposed his demand for Denmark to hand over Greenland to the US, alongside broader concerns about valuations and global growth.”
Add a brief note that other factors may also be influencing markets, e.g.: “Other influences include recent economic data releases and company-specific earnings reports.”
Presenting two events that occur together as if one clearly caused the other, without sufficient evidence.
“Markets have been rattled this week by the latest threats from Trump on countries that have opposed his demand for Denmark to hand over Greenland to the US.” The article states as fact that Trump’s threats have rattled markets, but does not provide supporting evidence (e.g., quotes from multiple analysts, data on timing of moves vs. statements) or acknowledge that this is an interpretation rather than a proven causal relationship.
Rephrase to indicate this is an interpretation, not a proven causal fact, e.g.: “Markets have been rattled this week, which some investors and analysts attribute in part to the latest threats from Trump…”
Add sourcing to support the causal claim, e.g.: “According to several strategists at major European banks, the latest threats from Trump have contributed to the risk-off mood.”
Alternatively, separate correlation from causation: “This week’s market volatility has coincided with the latest threats from Trump…”, leaving causality more open.
Use of interpretive or emotionally loaded wording that goes slightly beyond neutral description.
“Markets have been rattled this week by the latest threats from Trump on countries that have opposed his demand for Denmark to hand over Greenland to the US.” The word “rattled” is somewhat emotive and interpretive; “threats” is accurate if it reflects actual language used, but without quotation or context it can sound evaluative rather than strictly descriptive.
Use more neutral market language, e.g.: “Markets have been volatile this week…” or “Markets have come under pressure this week…”
If retaining “threats,” provide brief context or quotation to ground the term, e.g.: “after Trump warned he could impose tariffs on countries that opposed his demand…”
Clarify that this is a characterization commonly used in coverage, e.g.: “what many observers have described as threats from Trump…” if direct quotes are not provided.
Statements presented as fact without explicit sourcing or evidence, where some support would improve objectivity.
“The optimism that marked the start of the year has been now put to test as political tensions add to extended valuations and positioning…” This sentence asserts a narrative about earlier optimism and its being ‘put to test’ by political tensions and valuations, but does not reference specific data (e.g., sentiment surveys, valuation metrics) or sources.
Attribute the interpretation to sources, e.g.: “Strategists say the optimism that marked the start of the year is now being tested as political tensions add to concerns about extended valuations and positioning.”
Add a brief data point to support the claim, e.g.: “with the Stoxx Europe 600 trading at [X] times forward earnings, above its [Y]-year average.”
Alternatively, soften the assertion: “The optimism that marked the start of the year may be coming under pressure, as political tensions coincide with already extended valuations and positioning.”
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.