I am looking for scholarly, peer-reviewed articles that discuss natural language processing (NLP) involving chat or text messaging lingo/acronyms and the affect of chat participants based on language and emoticons. Anyone have a good recommendation?

I am already familiar with the recent work involving using Twitter to assess the general mood of society as a means of predicting the stock market. They used the Google-Profile of Mood States (GPOMS) that measures mood as Calm, Alert, Sure, Vital, Kind, or Happy. I am looking for other examples that assess general affect, ideally by applying more scientific psychometric tests to NLP.

I am not trying to predict anything. I am seeking to use machine learning algorithms to classify/categorize conversations.

I am looking for scholarly, peer-reviewed articles that discuss natural language processing (NLP) involving chat or text messaging lingo/acronyms and the affect of chat participants based on language and emoticons. Anyone have a good recommendation?

I am already familiar with the recent work involving using Twitter to assess the general mood of society as a means of predicting the stock market. They used the Google-Profile of Mood States (GPOMS) that measures mood as Calm, Alert, Sure, Vital, Kind, or Happy. I am looking for other examples that assess general affect, ideally by applying more scientific psychometric tests to NLP.

I am not trying to use the data for prediction. I am seeking to use machine learning algorithms to classify/categorize conversations.

References:

Bollen, J., Mao, H., Zeng, X-J. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1),1-8. [DOI]