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There need to be a way to programmatically determine how related two words are. The solution to this issue will work similar to the game of 6-degrees.
For each word there is n other words which are related by degrees.
Example: Dangerous is related to Evil by 3 degrees
Dangerous -- > Threatening --> Sinister --> Evil
Data
The following is a sample from a data set generated by counting the sum of the occurrences of words from 30 early american novels.
Below is an example of a humanly identifiable cluster of related words that occur in the data set. Most of the words in this range have the associated meaning of containing something. While there is a few outliers the general pattern is evident.
There need to be a way to programmatically determine how related two words are. The solution to this issue will work similar to the game of 6-degrees.
For each word there is n other words which are related by degrees.
Data
The following is a sample from a data set generated by counting the sum of the occurrences of words from 30 early american novels.
Below is an example of a humanly identifiable cluster of related words that occur in the data set. Most of the words in this range have the associated meaning of containing something. While there is a few outliers the general pattern is evident.
Meta data
Hypothesis
It is possible that trends exist between the sentiment of a statement and the commonality of use of the word in a language.
Trend examples: [WORD, TOTAL, LINE]
Note: The increased frequency of more positive words.
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