Home » How Your Music Playlist Could Help to Predict Economic Sentiment

How Your Music Playlist Could Help to Predict Economic Sentiment

The idea that economists should take into account the musical mood of the nation may seem unexpected or even strange. Meanwhile, studies show that the big data approach to tracking consumer sentiment can actually be useful.
be-in-the-loop - How Your Music Playlist Could Help to Predict Economic Sentiment

Andy Haldane, the chief economist and the Executive Director of Monetary Analysis and Statistics at the Bank of England, has urged his colleagues to examine the musical mood of the nation when contemplating changes to the bank’s interest rate. 

It all boils down to survey of economic sentiment. This is a way to evaluate how people perceive an economy, which is used by behavioral economists to predict reactions to various political decisions. For example, if people are pessimistic about current economic condition, then the increase of interest rates might encourage them to stop taking loans and spending that this will damage the economy. 

be-in-the-loop - How Your Music Playlist Could Help to Predict Economic Sentiment

The bottom line is that songs have an emotional component encoded in songs’ volume, energy, and tempo. Online music services such as Spotify already use these attributes to categorize songs and recommend users new tracks similar to the one they’ve already listened to.

You can also understand the songs’ emotions from their lyrics based on your cultural background. Lyrics can be analyzed using the same software that is used to analyze texts of news and tweets.

This can be done by coding the positive or negative emotional load of the words or comparing the words with the eight basic emotions: joy, sadness, anger, fear, disgust, surprise, trust and expectation. In the second case, the software counts the total number of occurrences of each emotion within a lyrics.

By measure the emotional components of popular songs, researchers can compose a picture of the feelings of listeners and use it to predict economic sentiment.

It is here the benefits of using “big data” from a large number of people come to the fore. Every survey result just show what its participants decided to share with  researchers. While the music charts reflect the actual consumer preferences of a large group of people.

be-in-the-loop - How Your Music Playlist Could Help to Predict Economic Sentiment

The 2008 Crash Caused Emotion Recession

Clermont University researchers applied this technique to music charts before and after the 2008 global economic crisis. They found that after the crisis, the frequency of words related to anger and disgust increased while the frequency of words related to trust decreased. This clearly indicates that consumers’ emotions are related to what kind of music they prefer to buy and listen to.

Clermont University researchers applied this technique to the charts before and after the 2008 global economic crisis. They found that after the crisis, the frequency of words related to anger and disgust increased, and the frequency of words related to trust decreased. This clearly indicates that consumers’ emotions as mind-set are related to what kind of music they prefer to buy and listen to.

This study and Andy Haldane’s comments show that both music and popular song lyrics can really be used to predict economic sentiment and even short-term stock market movements. Streaming services such as Spotify and Apple Music have data that can help create a much more detailed map of economic sentiment than the top 100 listings. Researchers can even create sentiment indices for different groups of people or regions, as online music streaming services have data on individual households. 

Have your say!

0 0

Leave a Reply

Your email address will not be published.

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

Lost Password

Please enter your username or email address. You will receive a link to create a new password via email.

Sign Up

ajax-loader