This is an interesting analysis of the relative frequency of usage of words associated with particular moods over the years.
This is the research paper:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059030
At a very high level this is what they did.
1. Sourced the number of occurrences of the words across the years from the google ngram project.
2. Got the mood scores associated with the words from WordNet.
3. Computed the relative frequency of words associated particular moods across the years.
Here is a demo of the Bag of Words model and a sentiment analysis model from Stanford.
http://googleresearch.blogspot.com/2006/08/all-our-n-gram-are-belong-to-you.html
https://aws.amazon.com/datasets/google-books-ngrams/
http://sentiwordnet.isti.cnr.it/
This is the research paper:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059030
At a very high level this is what they did.
1. Sourced the number of occurrences of the words across the years from the google ngram project.
2. Got the mood scores associated with the words from WordNet.
3. Computed the relative frequency of words associated particular moods across the years.
Here is a demo of the Bag of Words model and a sentiment analysis model from Stanford.
Reference Links:
https://books.google.com/ngramshttp://googleresearch.blogspot.com/2006/08/all-our-n-gram-are-belong-to-you.html
https://aws.amazon.com/datasets/google-books-ngrams/
WORD NET
http://wordnet.princeton.edu/http://sentiwordnet.isti.cnr.it/