Vectorize loop with if statement over dataframe and lists

I have a dataframe of text documents:

structure(list(
rowname = c("1", "2", "3", "4"), 
Datetime = c("2017-06-19", "2017-04-19", "2017-11-17", "2017-11-03"), 
content = c("aren t you absolut fed up with ", "the line between tax", "there ar peopl you ve", "ivan putrov 37 becam "), 
word_count = c(806L, 2808L, 741L, 766L), 
split = list(c("aren", t", "you", "absolut", "fed", "up", "with"), c("the", "line", "between", "tax"), c("there", "ar", "peopl", "you", "ve"), c("ivan", "putrov", "37", "becam")), 
allNOT = list(c(23L, 46L, 54L, 62L, 93L, 104L, 113L, 277L, 387L, 401L, 411L, 439L, 492L, 526L, 653L, 749L), c(59L, 74L, 96L, 160L, 368L, 588L, 764L, 813L, 819L, 949L, 955L, 1276L, 1382L, 1463L, 
1478L, 1500L, 1564L, 1772L, 1992L, 2168L, 2217L, 2223L, 2353L, 2359L, 2680L, 2786L), c(6L, 95L, 686L), c(107L, 372L, 414L, 627L, 643L)), 
allSTOPS = list(c(3L, 6L, 7L, 8L, 9L, 11L, 12L, 17L, 18L, 21L, 22L, 23L, 24L, 26L, 27L, 29L, 30L, 33L, 34L, 35L, 39L, 41L, 43L, 45L, 48L, 49L, 51L, 53L, 56L, 59L, 61L, 63L, 
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564L, 566L, 567L, 571L, 572L, 575L, 576L, 577L, 579L, 581L, 582L, 585L, 586L, 593L, 594L, 595L, 597L, 599L, 601L, 603L, 605L, 607L, 608L, 609L, 611L, 613L, 615L, 617L, 619L, 621L, 622L, 623L, 626L, 
627L, 629L, 631L, 632L, 635L, 636L, 638L, 640L, 641L, 643L, 644L, 646L, 651L, 652L, 654L, 655L, 656L, 659L, 660L, 662L, 664L, 666L, 671L, 672L, 674L, 675L, 677L, 680L, 682L, 683L, 686L, 687L, 688L, 
689L, 691L, 693L, 694L, 696L, 698L, 699L, 701L, 703L, 705L, 707L, 708L, 710L, 712L, 713L, 717L, 720L, 726L, 727L, 738L, 740L, 742L, 743L, 744L, 749L, 752L, 754L, 755L, 761L, 762L, 763L, 766L)), 
stops_count = list(412L, 1120L, 319L, 380L), 
count = list(3L, 2L, 1L, 1L), 
allYES = list(c(133L, 550L, 560L), c(12L, 1416L), 144L, 248L), 
test = c(0, 0, 0, 0), 
.Names = c("rowname", "id", "Datetime", "content", "word_count", "split", "allNOT", "allSTOPS", "stops_count", "count", allYES", "test"), 
row.names = c(NA, -4L), 
groups = structure(list(id = (1", "2", "3", "4"), 
.rows = list(1L, 2L, 3L, 4L)), 
.Names = c("id", ".rows"), 
row.names = c(NA, -4L), 
class = c("tbl_df", "tbl", data.frame"), .drop = TRUE), 
class = c("grouped_df", "tbl_df", "tbl", "data.frame"))

the allYES & allNOT & allSTOPS columns are lists of positions of words that I search for in the documents. I am trying to use these positions to find various patterns based on distance (e.g. negations). The code below, does this and works fine, however, it does not scale and is extremely slow (the dreaded for loop!)

for(i in 1:nrow(temp_good)) {
    if(nrow(temp_good)==0) { next}
    a <- temp_good$allYES[[i]]
    b <- temp_good$allNOT[[i]]
    c <- abs(unlist(lapply(a, function(k) k - b)))
    d <- length(c[c>0&c<3])
    if(d>0) {
        temp_good$test[i] <- d
    } 
}

Now I am aware that the ifelse construct in R is vectorized but I can't get it to work. I tried a few different varieties and I am sure I am doing something silly somewhere, but I honestly can't see it. The code below generates the variable "c" from above

temp_good$newCol <- ifelse(nrow(temp_good)==0, {next}, abs(unlist(lapply(unlist(temp_good$allYES), function(k) k - unlist(temp_good$allNOT)))))

but returns the first value in the first iteration of the loop. If I run the inner calculation:

abs(unlist(lapply(unlist(temp_good$allYES[1]), function(k) k - unlist(temp_good$allNOT[1]))))

The result is correct, but I can't seem to coerce it into a dataframe element using the ifelse construct.

 110  87  79  71  40  29  20 144 254 268 278 306 359 393 520 616 527 504 496 488 457 446 437 273 163 149 139 111  58  24 103 199 537 514 506 498 467 456 447 283 173 159 149 121  68 34  93 189

Now this doesn't solve the entire problem but the I can't even get past this first step.

I also tried to wrap this code in a function:

calculateDiff <- function(x){ abs(unlist(lapply(unlist(temp_good$allYES), function(k) k - unlist(temp_good$allNOT))))}

and use lapply again to create the new column, but no luck.

Any advice and guidance on this is much appreciated.