MortonWang / geo_IF

This is an implementation of the paper ”Interpreting Twitter User Geolocation“.

This repo provides an implementation of the paper Interpreting Twitter User Geolocation.

Dataset

You can download GeoText and TwitterUS from amazondrive and put them into "./dataset_cmu" and "./dataset_na" folder separately.

The following content will take GeoText dataset as an example of usage.

Requirements

The code was tested with Python 3.7, tensorflow-gpu 1.14.0 on windows 10. Install the dependencies via Anaconda:

conda install tensorflow-gpu==1.14.0

pip install -r requirements.txt

Usage

This repo includes three main parts:

1. Data processing (script folder: "./data_process", data folder: "./dataset_cmu")
2. Model construction with influence functions (script files: "./main_SGC_inf.py", "./main_N2V_inf.py")
3. Plot analysing (script folder: "./plot_functions", data folder: "./plot_data")

Data Processing

cd data_process
python preprocess.py
python handle_n2v.py --input ../dataset_cmu/edge/edge_pair.ungraph  --output ../dataset_cmu/edge/out_of_order.emd  --dimensions 128

Model with IF

python main_SGC_inf.py
python get_influ_matrix.py --ResFolder "./Res_inf_SGC" --SaveFile "./plot_data/sgc_all_inf.txt"
python main_N2V_inf.py
python get_influ_matrix.py --ResFolder "./Res_inf_N2V" --SaveFile "./plot_data/n2v_all_inf.txt"

Plot analysing

cd plot_functions
python plot_degree.py
python plot_comparison.py
python plot_geo_dist.py
python plot_cluster.py

Cite

If you find this work useful for your research, please consider citing us:

@inproceedings{Ting2020Interpreting,
author = {Ting Zhong, Tianliang Wang, Fan Zhou, Goce Trajcevski, Kunpeng Zhang and Yi Yang}, 
title = {Interpreting Twitter User Geolocation},
booktitle = {the 58th Annual Meeting of the Association for Computational Linguistics (ACL)}, 
year = {2020},
}