We are currently beta testing our public API.
To obtain the endpoint url and an API key, email us at firstname.lastname@example.org with the use-case and approximate requests/min/hour.
Please do not try to use a bot to imitate human requests, as this will result in your IP being banned completely.
In further efforts to fight biased news on social media, we created a bot that runs on Reddit, one of the most popular social media and link sharing sites.
The bot’s only and official username is “u/politicalbiasai.” Its official subreddit is “r/PoliticalBiasBot.”
The bot can be summoned by commenting “!analyzebias” in one of the eligible subreddits when there’s a link post.
The bot will then extract the article text using the newspaper python library and call our political bias API to analyze the bias. Then it will comment on the post the bias value that was returned, on a scale of -1 to 1, with 1 being the most biased towards the right and -1 towards the left.
For example, a post that gets a score of -0.8 can be assumed to have a considerable amount of left bias and should be read with caution.
On the other hand, an article from a generally unbiased source like Reuters will usually yield a score of -0.07 to 0.07, meaning it’s pretty unbiased.
For reference, we documented the process of building the bot and you can find more information here to see how the AI works and the approximate accuracy.
Please read our “Interpreting Results” section below to learn in detail what the results mean.
This bot runs on our second most powerful, BERT model, which also powers our classifier tool.
Keep in mind, our AI isn’t 100% accurate and will make mistakes, especially if the article isn’t related to politics. In case of error, you can reply to the bot’s comment with what you think the bias should be and we will periodically check it and tune the bot.
Furthermore, we remind you to make your own decisions about an article and simply use the bias as a reference point.
For issues or questions with the bot, please email us at email@example.com.
Eligible Subreddits (We are working to add more. Please email us if you want your subreddit included):
Our various tools can return two types of results. Either a numerical value or a label.
Our API and Reddit Bot return numerical values that are on a scale of 1 to -1.
As described above, the quantity of the value denotes how biased the article is, with 0 being the least and 1 being the most.
Positive or negative values denote which side the content is biased towards. For reference, the approximate classifications for the range of bias are below.
Our self-hosted classification tool returns labels which are self-explanatory. These labels are based on the raw numerical values returned from our AI.
An article with “Minimal Bias” has a numerical value of 0 – 0.20 (absolute value).
An article with “Moderate Bias” has a numerical value of 0.21 – 0.45 (absolute value).
An article with “Strong Bias” has a numerical value of 0.46 – 0.70 (absolute value).
An article with “Extreme Bias” has a numerical value of 0.71+ (absolute value).
Negative or Positive values denote direction. Negative for “Left” while Positive is for “Right.”
The direction (left or right) of bias refers to the direction the content favors.
During our testing, we found AI model currently deployed for public use had an average deviation of +/- 0.18 from the actual accuracy. Therefore, when interpreting the values, it important to take note of this and not take them too literally.
We cannot be held liable for any consequence that results from using this bias value.
If you are interested in helping us develop integrations or add them to your application, please email us at firstname.lastname@example.org.
We are looking to collaborate with organizations that are fighting fake news and trying to provide readers with more balanced coverage.
Integrations we are currently working on:
- Browser Extensions
- Daratos (In Development)
- Discord Bot
- Public API (Beta)
- News Aggregator