Understanding the Meaning of Emoji in Mobile Social Payments

This project uses the external emoji library, the nltk library, the gensim library, the pandas library, and the numpy library.

Documentation

• co_oc*.py - Files that showcase the co-occurrence code.
• emoji_grame.py, emoji_grame2.py, n4ModE.py, n4ModN.py, trials.py, trials2.py, trials3.py - Files that all showcase n-grame code from n=1, n=2, n=3, and n=4.
• final_codings.csv - Encoding of top common emojis into their categories and hedonic and/or utilitarian characteristic.
• flattenModE.py - Flattens the heavy-duty dataset into a more streamlined version that's easier to load into memory.
• lda*.py, overallTM*.py, topicModelling*.py - Files that do LDA topic modelling