01-06-2020, 05:37 PM
Yes, there were some mistakes in my code... I had missed to correctly capture the = signs at line-breaks. It was corrected and I rerun the program. The data now changed more, but I don't think the changes to the graph is that significant, but here it is anyway.
Yes, I had planned this as well, it will make a separate analysis. But since the idea is to compare it with an unknown writing system which might also have separate incidents of characters with identical meaning, I think it could tell something as well.
The new basic data looks as following:
Average word length (counting each unique word only once): 8.53786 characters, standard deviation: 5.3916
Average word length (text aggregate): 7.52895 characters, standard deviation: 4.99348
Number of unique words: 1149
Total number of words (tokens): 1658
So, the type-token ratio is now 69% (not a big change from 72%).
Changes to the number of repeated phrases:
Number of pairs: 59
# Triplets: 31
# Quadruplets: 22
# Quintuples: 16
# Sixtuples: 13
Here is the updated graph:
[attachment=4433]
Quote:I would also suggest not to make the search case sensitive. Maybe this would decrease the unique word percentage to a more reasonable number.
Yes, I had planned this as well, it will make a separate analysis. But since the idea is to compare it with an unknown writing system which might also have separate incidents of characters with identical meaning, I think it could tell something as well.
The new basic data looks as following:
Average word length (counting each unique word only once): 8.53786 characters, standard deviation: 5.3916
Average word length (text aggregate): 7.52895 characters, standard deviation: 4.99348
Number of unique words: 1149
Total number of words (tokens): 1658
So, the type-token ratio is now 69% (not a big change from 72%).
Changes to the number of repeated phrases:
Number of pairs: 59
# Triplets: 31
# Quadruplets: 22
# Quintuples: 16
# Sixtuples: 13
Here is the updated graph:
[attachment=4433]