Constructed example data to demonstrate the Wordscores algorithm, from Laver Benoit and Garry (2003), Table 1.



A dfm object with 6 documents and 37 features.


This is the example word count data from Laver, Benoit and Garry's (2003) Table 1. Documents R1 to R5 are assumed to have known positions: -1.5, -0.75, 0, 0.75, 1.5. Document V1 is assumed unknown, and will have a raw text score of approximately -0.45 when computed as per LBG (2003).


Laver, Michael, Kenneth Benoit, and John Garry. 2003. "Estimating policy positions from political text using words as data." American Political Science Review 97(2): 311-331.