Project related to emotional classification on reddit dataset which fuses language and image modality.
Project related to multimodal classification of emotion utilizing langugage and image modalities. It was part of CS-594 course (under Prof. Natalie Parde) requirement at UIC
Details included in the report
Installation Intructions:
1) Extract the zip file in root/
2) Navigate to root/language_vision directory
3) Create a virtual env with conda (assuming the anaconda is already installed)
a. conda env create -f environment.yml
4) Activate the environment
a. Source activate multimodal-env
5) Install the glove embeddings (glove.twitter.27B.zip) from (http://nlp.stanford.edu/data/glove.twitter.27B.zip)
6) Extract the zip and place the glove.twitter.27B.100d (100-Dimension) file in the root/language_vision/embeddings directory
7) Reddit dataset is already filtered and present in the input directory (input_data.csv)
8) Navigate to the root/language_vision/src directory
9) To run the code
a. python3 driver.py
10) Unimodal and fusion results will be printed in the console
Some of common issues:
1) You might encounter memory error for creating word2vec for language model as conversion of binary file to dictionary tend to take up lot of space [2-3GB approx.]
Anaconda installation
• https://docs.anaconda.com/anaconda/install/
References:
[1]Duong, Chi Thang, Remi Lebret, and Karl Aberer. “Multimodal classification for analysing social media.” arXiv preprint arXiv:1708.02099 (2017).