Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Bina Gurung / Rastriya Swatantra Party (RSP)
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 slightly evaluative or emotionally-tinged wording that can subtly influence perception, even when the underlying facts are correct.
The phrase: "उनीले निकटतम् प्रतिस्पर्धी कांग्रेसका मनोज गुरूङलाई फराकिलो मतान्तरले हराउँदै निर्वाचित भएकी हुन् ।" describes the victory as "फराकिलो मतान्तर" (wide margin). While the margin is indeed large based on the numbers, the wording adds a small evaluative emphasis beyond just stating the figures.
Replace evaluative phrasing with purely descriptive wording, for example: "उनी निकटतम् प्रतिस्पर्धी कांग्रेसका मनोज गुरूङभन्दा धेरै मत बढी प्राप्त गर्दै निर्वाचित भएकी छन्" or simply "उनी निकटतम् प्रतिस्पर्धी कांग्रेसका मनोज गुरूङलाई पराजित गर्दै निर्वाचित भएकी छन्".
Rely on the numerical data itself to convey the scale of the victory, e.g.: "उनीले ३७ हजार ७ सय ५० मत र कांग्रेसका मनोज गुरूङले १२ हजार ७ सय ८० मत प्राप्त गरे" without adding qualitative labels like "फराकिलो".
If using qualitative terms like "फराकिलो", explicitly link them to the numbers, e.g.: "२५ हजारभन्दा बढी मतान्तर भएकाले यो फराकिलो मतान्तर मानिन्छ" to make the evaluative term transparent and grounded.
- 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.