misinformation-exposure score: a score calculated based on public figures accounts followed on Twitter

You can use the R package or the API service we have develope to calculate misinformation-exposure score at scale.

Citation

If you use our method please cite the following: Mosleh, M., Rand, D.G. Measuring exposure to misinformation from political elites on Twitter. Nat Commun 13, 7144 (2022). https://doi.org/10.1038/s41467-022-34769-6

Website

You can use the following webiste to check the misinformation exposure score for a give Twitter handle or user id.

https://misinfoexpose.com/

API service

All you need is to create an account on https://rapidapi.com/ (it is free!)

You can find the instruction to use the API here: https://rapidapi.com/mescalcapi-mescalcapi-default/api/mescalc It is very strightforward:

The input is either Twitter screen_name or Twitter ID and the output is misinifo exposure in [0,1], partisanship [-1,1] (-1 dem, 1 rep), and list of political elites the user followers.

For example in R:

library(httr)

screen_name<-'aoc'
url <- paste("https://mescalc.p.rapidapi.com/account/",tolower(screen_name),sep='')

response <- VERB("GET", url, add_headers('X-RapidAPI-Host' = 'mescalc.p.rapidapi.com', 'X-RapidAPI-Key' = 'SIGN-UP-FOR-KEY'), content_type("application/octet-stream"))

content(response, "text")

And in Python:

import requests

screen_name='aoc'
url = "https://mescalc.p.rapidapi.com/account/{}".format(screen_name.lower())

headers = {
	"X-RapidAPI-Host": "mescalc.p.rapidapi.com",
	"X-RapidAPI-Key": "SIGN-UP-FOR-KEY"
}

response = requests.request("GET", url, headers=headers)

print(response.text)

R package

R version 4.0.4

About

This package provides an R implementation to calculate misinformation-exposure score based falsity score of public figures a user follows.

The falsity score is based on PolitiFact fact-checks of the public figures.

Installation

The development version of the misinformation-exoposure library can be installed in R with the following:

# install.packages("devtools")
devtools::install_github("mmosleh/minfo-exposure")

Quick start guide

All you need to do is give a list of Twitter users (either screen names or user IDs) and the function returns the number of rated public figures followed along with the misinformation-exposure score.

The functions relies on Rtweets library and needs to authenticate with your Twitter account first time you run the code.

library(misinfo.exposure)

misinfo.scores <- misinfo.exposure::get_misinfo_exposure_score(c('user1','user2'))
print(misinfo.scores)