Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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नेपाल एपीएफ क्लब
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.
Use of subtly evaluative wording that goes beyond neutral description of performance.
“कप्तान रोहित पौडेलले ४५ र सुमित महर्जनले ४५ रन बनाए पनि अन्यले खासै योगदान दिन नसक्दा एपीएफ २ सय रनमुनि समेटिएको थियो ।” This sentence characterizes the rest of the batters’ performance as ‘खासै योगदान दिन नसक्दा’ (could not contribute much), which is a mild evaluative judgment rather than a purely neutral description of runs scored and dismissals.
Replace evaluative phrasing with neutral description of statistics, for example: “कप्तान रोहित पौडेल र सुमित महर्जनले ४५–४५ रन बनाए भने अन्य ब्याटरले सानो योगफल जोड्दा एपीएफको इनिङ २ सय रनमुनि १ सय ८५ मा समाप्त भयो ।”
Alternatively: “रोहित र सुमितबाहेक अन्य ब्याटरले दोहोरो अंकमा ठूलो स्कोर बनाउन सकेनन्, जसका कारण एपीएफको योगफल १ सय ८५ रनमै सीमित रह्यो ।”
Avoid value-laden terms like ‘खासै योगदान दिन नसक्दा’ unless clearly defined in quantitative terms or supported by comparative context.
- 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.