Solomon Messing

Solomon Messing is an academic researcher and data scientist known for his work on how algorithms and social information embedded in new technologies affect the way people understand the political world. He was the founding Director of Pew Research Center's Data Labs and is a staff research scientist with Facebook.

His work quantifying media polarization and filter bubbles was published in Science and has been influential in the field of political communication and sparked media commentary on the role of networks and algorithms in the media ecosystem. His work on how people understand election forecasting was the subject of public debate about the role of election forecasting in the democratic process and was cited by FiveThirtyEight's Politics Podcast as a reason for changing the forecast from percent change of winning to odds.

Most cited peer-reviewed journal articles
Bakshy E, Messing S, Adamic LA. Exposure to ideologically diverse news and opinion on Facebook. Science. 2015 Jun 5;348(6239):1130-2. cited 813 times in Google Scholar
Messing S, Westwood SJ. Selective exposure in the age of social media: Endorsements trump partisan source affiliation when selecting news online. Communication Research. 2014 Dec;41(8):1042-63. cited 340 times in Google Scholar 
Grimmer J, Messing S, Westwood SJ. How words and money cultivate a personal vote: The effect of legislator credit claiming on constituent credit allocation'  American Political Science Review. 2012 Nov;106(4):703-19.cited 150 times in Google Scholar 
Bond R, Messing S. Quantifying social media’s political space: Estimating ideology from publicly revealed preferences on Facebook. American Political Science Review. 2015 Feb;109(1):62-78. cited 95 times in Google Scholar

References 

Category:Living people
Category:Data scientists
Category:Year of birth missing (living people)
Category:Place of birth missing (living people)