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How will COVID-19 impact NEGATIVE affect on social media in 6 months (Oct 2020)?

The Behavioral Forecasting Collaborative organized by researchers at the University of Waterloo has been studying positive and negative affect (i.e. emotions) on US English-language Twitter data. Their research methods are as follows:

Estimates for NEGATIVE affect were calculated by applying a custom lexicon to message unigrams. The estimates provide the monthly sum of the pointwise mutual information of each unigram with positive and negative affect theme. The scores quantify the extent to which the monthly tweets contain language that is associated with negativity.

We standardized estimates based on all prior time series data (M = 0.145 / SD = 0.0215), maintaining difference between the groups. Here, unit of change reflects standard deviations above or below the average of all prior data (Jan 2017-Mar 2020) for both positive and negative affect language.

Recently, they have expanded their research to include a new interest in how COVID-19 affects positive and negative affect on social media. This question asks:

What will the negative affect score value be on social media, for October 2020?

We will collect predictions until May 22nd as part of a tournament, and this question will resolve mid-November, according to the dataset available on their website.

2020-05-18 JBoyles changed "Twitter data" to "US English-language Twitter data"


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