Lots of affect lexicons have been proposed. General Inquirer is the oldest lexicon that is defined in a binary way, with a list of 1915 positive word and a list of 2291 negative words.   

University of Notre Dame

The most common algorithms involve supervised classification: a training set is labeled for the affective meaning to be detected, and a classifier is built using features extracted from the training set. Many possible values can be used for lexicon features. The simplest is just an indicator function, in which the value of a feature $f_L$ takes the value 1 if a particular text has any word from the relevant lexicon $L$. 

Lexicons for Affect Recognition

An on-going but a helpful book resource about NLP
https://web.stanford.edu/~jurafsky/slp3/

Speech and Language Processing (3rd ed. draft) 

 General Inquirer

EmoLex lexicon is based on the eight-basic-emotion model , and includes around 14000 high frequency words and words from previous lexicons.

EmoLex Lexicon

LIWC is a lexicon that’s designed for social-psychological tasks. It includes 73 lexicon categories and 2300 words. Besides binary sentiment lexicons, it also included lexicons like anger, sadness, cognitive mechanisms, perception, tentative, and inhibition,

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