Use-Dynamic-network-embedding-for-Social-Network-Aligment-

###in this part, I will provide many tools for social networking, Link prediction and so on

We use this paper for dynamic social network alignment：

Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding

if you meet some trouble about this code ,pls contact with me (Zihan Yan yzhcqupt@163.com)

https://www.ijcai.org/Proceedings/2018/288

We use this work to do dynamic Social-Network-Aligment You should frist run 'comebine_network.py', the data comes from IONE(Aligning Users Across Social Networks Using Network Embedding),With the permission of sharing anonymous twitter_foursquare data from Prof.Jiawei Zhang, we share the anonymous data and code of IONE here. the data and code only can be used for research purposes. then:

# running the following command in code repos
conda env create -f dne_env.yml
c

• Using the following command in ./src directory:

python main.py --conf amherst0.25

###data 1\twitter or foursquare

278  5

6    5

56  5

... ...

meas node 278 link with node 5 with network 2\train or test

1

2

5

6

meas this is the anchor node, you can use 'devite_node.py' clip train file and test file for 10%-90%

###last You can

       run 'result.py'  to get this work's result

#combine_network: -foursquare -twitter

run ronghe.py 

you should combine foursquare with twitter

run split_graph.py

you should trans mat

run flag.py 

get flat file