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Editorial Team
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Editorial Team
Asked: May 27, 20262026-05-27T00:46:52+00:00 2026-05-27T00:46:52+00:00

I’m using MALLET for topic analysis which is outputting results in text files (topics.txt)

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I’m using MALLET for topic analysis which is outputting results in text files (“topics.txt”) of several thousand rows and a hundred or so rows where each row consists of tab-separated variables like this:

Num1 text1 topic1 proportion1 topic2 proportion2 topic3 proportion3,  etc.
Num2 text2 topic1 proportion1 topic2 proportion2 topic3 proportion3,  etc.
Num3 text3 topic1 proportion1 topic2 proportion2 topic3 proportion3,  etc.

Here’s a snippet of the actual data:

> dat[1:5,1:10]

  V1 V2 V3    V4 V5        V6 V7        V8 V9        V10
1  0 10.txt   27 0.4560785 23 0.3040853 20 0.1315621 21 0.03632624
2  1 1001.txt 20 0.2660085 12 0.2099153  8 0.1699586 13 0.16922928
3  2 1002.txt 16 0.3341721  2 0.1747023 10 0.1360454 12 0.07507119
4  3 1003.txt 12 0.5366148  8 0.2255179 18 0.1388561  0 0.01867091
5  4 1005.txt 16 0.2363206  0 0.2214441 24 0.1914769  7 0.17760521

I’m trying to use R to convert this output into a data table where the topics are column headers and each topic contains the values of the variable ‘proportion’ directly to the right hand side of each variable ‘topic’, for each value of ‘text’. Like this:

      topic1       topic2       topic3
text1 proportion1  proportion2  proportion3
text2 proportion1  proportion2  proportion3

or with the data snippet above, like so:

           0         2         7         8         10        12        13        16        18       20        21         23        24         27
10.txt     0         0         0         0         0         0         0         0         0        0.1315621 0.03632624 0.3040853 0          0.4560785        
1001.txt   0         0         0         0.1699586 0         0.2099153 0.1692292 0         0        0.2660085 0          0         0          0
1002.txt   0         0.1747023 0         0         0.1360454 0.0750711 0         0.3341721 0        0         0          0         0          0
1003.txt   0.0186709 0         0         0.2255179 0         0.5366148 0         0         0.138856 0         0          0         0          0
1005.txt   0.2214441 0         0.1776052 0         0         0         0         0.2363206 0        0         0          0         0.1914769  0

This is the R code I’ve got to do the job, sent from a friend, but it doesn’t work for me (and I don’t know enough about it to fix it myself):

##########################################
dat<-read.table("topics.txt", header=F, sep="\t")
datnames<-subset(dat, select=2)
dat2<-subset(dat, select=3:length(dat))
y <- data.frame(topic=character(0),proportion=character(0),text=character(0))
for(i in seq(1, length(dat2), 2)){ 
z<-i+1
x<-dat2[,i:z]
x<-cbind(x, datnames)
colnames(x)<-c("topic","proportion", "text")
y<-rbind(y, x)
}

# Right at this step at the end of the block 
# I get this message that may indicate the problem:
# Error in c(in c("topic", "proportion", "text") : unused argument(s) ("text")

y[is.na(y)] <- 0 
xdat<-xtabs(proportion ~ text+topic, data=y)  
write.table(xdat, file="topicMatrix.txt", sep="\t", eol = "\n", quote=TRUE, col.names=TRUE, row.names=TRUE)
##########################################

I’d be most grateful for any suggestions on how I can get this code working. My problem may be related to this one and possibly this one also, but I don’t yet have the skills to make immediate use of the answers to those questions.

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  1. Editorial Team
    Editorial Team
    2026-05-27T00:46:52+00:00Added an answer on May 27, 2026 at 12:46 am

    Here is one approach to your problem

     dat <-read.table(as.is = TRUE, header = FALSE, textConnection(
      "Num1 text1 topic1 proportion1 topic2 proportion2 topic3 proportion3
       Num2 text2 topic1 proportion1 topic2 proportion2 topic3 proportion3
       Num3 text3 topic1 proportion1 topic2 proportion2 topic3 proportion3"))
    
     NTOPICS = 3 
     nam <- c('num', 'text', 
       paste(c('topic', 'proportion'), rep(1:NTOPICS, each = 2), sep = ""))
    
     dat_l <- reshape(setNames(dat, nam), varying = 3:length(nam), direction = 'long',
       sep = "")
     reshape2::dcast(dat_l, num + text ~ topic, value_var = 'proportion')
    
    num  text      topic1      topic2      topic3
    1 Num1 text1 proportion1 proportion2 proportion3
    2 Num2 text2 proportion1 proportion2 proportion3
    3 Num3 text3 proportion1 proportion2 proportion3
    

    EDIT. This will work irrespective of whether the proportions are text or numbers. You can also modify NTOPICS to suit the number of topics you have

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