Use Helium’s balanced news feed & search engine to read from diverse and engaging sources. Dive deeper into source-by-source bias and news analysis for any search term. Updated daily.
Instead of analyzing media bias in ideological or political terms, Helium uses the following guiding questions to measure news bias:
1.) What terms & topics do sources publish more about and less about?
2.) Which terms tend to be written about with highly emotional language?
3.) How often and for how long do sources talk about events?
4.) How does media coverage change over time and in response to events?
5.) Do sources use a lot of prescriptive language?
Sentiment analysis uses statistical patterns in language to try and identify emotional texture. To measure this emotion, Helium uses an (arbitrary) scale from -10 to +10 where 0 is emotionally neutral, -10 is emotionally angry or negative and +10 is emotionally happy or positive.
While emotional pieces of news are not necessarily a bad thing, highly emotional language can be manipulative and ideological. Emotional content is effective at spreading but tends to be less truth-seeking.
Since sentiment analysis doesn’t really “understand” complex ideas and meanings, it should not be interpreted too literally, especially on just one piece of text. However, over hundreds of articles, sentiment analysis is a relatively robust way of measuring how emotionally charged something is.
Gain deeper context with sentiment analysis and mentions-over-time analysis for search phrases and information sources. Orient your interpretation of information within larger narratives and themes and improve your holistic understanding. Step outside from jarring headlines and towards understanding why you read what you read and how to synthesize complex ideas.
With mentions-over-time, each headline is not a singular piece of information, but a small piece of the over-arching story. Helium gives you the tools to ask questions like:
How does this piece of information fit into the (ever-evolving) greater media landscape?
Is the author using highly-emotional language to try and push my beliefs?
How does the language used describing certain people/events/ideas change over time?
How does the usage or omission of certain phrases affect how I interpret and assign meaning?
By understanding global patterns in news coverage and sentiment you can gain longer-term insights into the subtleties of interpreting what the news is really communicating.