Research material & open-source software by and for the community
Within the growing and fascinating landscape at the frontier of text mining, sentiment analysis, and econometrics, the field sentometrics has emerged. Researchers in sentometrics investigate the transformation of qualitative sentiment embedded in textual data (and other alternative data sources) into quantitative sentiment variables, and their subsequent application in an econometric analysis of the relationships between sentiment and other variables.
Many researchers steer forward sentometrics by doing tremendous work across the domains of economics, finance, politics and beyond. The objective of this hub is to provide resources and open-source software to help the community of these researchers interact with each other and showcase their work, while also introducing those interested to enter the field.
The Structural Topic Model (STM) allows researchers to estimate topic models with document-level covariates.
You can contribute by submitting a resource using this form. Please include what type of resource (index, post, software, publication) as well as a link to the resource and we will get in touch!