Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
CLICK ANY SECTION TO GIVE FEEDBACK, IMPROVE THE REPORT, SHAPE A FAIRER WORLD!
General market performance (NZX50 and Asia-Pacific equities)
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.
Using emotionally colored or dramatic wording that can subtly influence readers’ perceptions without changing the underlying facts.
1) Section heading: "It’s precious" – a playful, emotive phrase that frames the gold segment rather than neutrally describing it. 2) "Still, Santana Minerals closed at a two-week low amid fears a decision on consenting its proposed open cast mine near Cromwell in Central Otago might face delays..." – the word "fears" attributes an emotional state to the market without specifying whose fears or providing direct sourcing. 3) "Rumours of intervention supported the yen on Friday in New York..." – "rumours" is accurate market jargon but can imply unverified chatter; the article does not specify the nature or source of these rumours.
Replace the heading "It’s precious" with a neutral, descriptive heading such as "Gold rally boosts mining stocks" or "Gold price rise supports miners".
Clarify the source of the "fears" about Santana Minerals, for example: "...closed at a two-week low amid investor concerns that a decision on consenting its proposed open cast mine... might face delays" or "...amid market expectations that..." and, if possible, attribute to analysts, company statements, or specific market commentary.
For "Rumours of intervention supported the yen", add brief clarification such as: "Market speculation about possible intervention supported the yen..." or "Unconfirmed market rumours of intervention supported the yen..." and, if available, reference typical market sources (e.g. trader commentary, prior official statements) to make clear this is standard market speculation rather than baseless gossip.
Arranging facts into a narrative that implies a stronger causal or thematic connection than is strictly demonstrated, even if the facts themselves are accurate.
1) "New Zealand’s S&P/NZX 50 index staged a late recovery, buoyed by heavyweights Fisher & Paykel Healthcare, Ebos Group and Contact Energy..." – this is standard market language, but "staged a late recovery" and "buoyed" create a narrative of a comeback; the causal link is plausible but not quantitatively demonstrated. 2) "The benchmark spent much of the day in negative territory, only to be buoyed in the match period at the end of the session, with index heavyweights lifting it higher." – again, this is typical market reporting, but it frames the end-of-day move as a clear narrative of heavyweights "lifting" the index without explicit data on contribution.
Use slightly more neutral phrasing such as: "New Zealand’s S&P/NZX 50 index ended slightly higher, with gains in Fisher & Paykel Healthcare, Ebos Group and Contact Energy contributing to a late-session rise."
For the match-period description, specify the factual mechanism: "The benchmark spent much of the day in negative territory but moved into positive territory during the closing match period, as larger index constituents including Ebos Group and Contact Energy rose."
Where feasible, add brief quantitative context (e.g. approximate index point contribution of key stocks) to support the implied causal relationships.
- 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.