qinghao-guan/10dimensions

Public repository containing the dataset and code for training the models in "Ten Social Dimensions of Conversations and Relationships" (WWW'20)

10dimensions

Public repository containing the dataset and code for training the models in "Ten Social Dimensions of Conversations and Relationships" (WWW'20) paper

Requirements for code

• The requirements can be found here
• Our LSTM models are based on pretrained GloVe word embeddings. Please refer to the instructions for setting the word embeddings here

Preprocessing dataset

1. Run preprocess_data.py to transform the existing dataset in data/labeled-dataset.tsv to a BERT-friendly form

Using pretrained models

• The instructions for downloading and using pretrained models can be found here
• Once the pretrained weights are placed in the right directories, you can test the models on new sentences using the 'Test BERT' and 'Test LSTM' jupyter notebooks.

Training your own models

• Run train_BERT.py or train_LSTM.py to train the model for each of the 10 dimensions. The dimensions can be modified in the main function.

Citation

If using the package for research purposes, please cite the following work.

@inproceedings{10.1145/3366423.3380224, author = {Choi, Minje and Aiello, Luca Maria and Varga, Kriszti'{a}n Zsolt and Quercia, Daniele}, title = {Ten Social Dimensions of Conversations and Relationships}, year = {2020}, isbn = {9781450370233}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3366423.3380224}, doi = {10.1145/3366423.3380224}, booktitle = {Proceedings of The Web Conference 2020}, pages = {1514–1525}, numpages = {12}, keywords = {conversations, NLP, twitter, reddit, tinghy, enron, social relationships}, location = {Taipei, Taiwan}, series = {WWW ’20} }