Values in the vector corresponded to the smoothed frequencies with which each word directly preceded or followed the represented word.
each word w was assigned a vector (f w,1 , ..., f w,15508 ), such that f w,v is the number of times word v directly precedes (for v ≤ 7754) or follows (for v > 7754) word w. Next, the frequency counts were transformed into Pointwise Mutual Information (PMI) values (see Equation 2), following Bullinaria and Levy's (2007) findings that PMI produced more psychologically accurate predictions than other measures: Finally, the 400 columns with the highest variance were selected from the 7754×15508-matrix of row vectors, making them more computationally manageable, but not significantly less informative.