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Social network analysis using deep learning: applications and schemes

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Abstract

Online social networks (OSNs) are part of daily life of human beings. Millions of users are connected through online social networks. Due to very large number of users and huge amount of data, social network analysis is a challenging task. The emergence of deep learning techniques has enabled to carry out a rigorous analysis of OSNs. A lot of research is carried out in the area of social network analysis using deep learning techniques from different perspectives. In this paper, we provide an overview of state-of-the-art research for different applications of social network analysis using deep learning techniques. We consider applications such as opinion analysis, sentiment analysis, text classification, recommender systems, structural analysis, anomaly detection, and fake news detection. We compare different schemes on the basis of their focus and features. Further, we point out directions for future work.

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Notes

  1. https://snap.stanford.edu.

  2. https://www.aminer.cn/data-sna.

  3. https://www.kaggle.com/.

Abbreviations

AENC:

Auto-encoder

AM:

Attention mechanism

ANN:

Artificial neural network

BERT:

Bidirectional encoder representations from transformers

CNN:

Convolutional neural network

DBN:

Deep belief networks

DBM:

Deep Boltzmann machine

DGL:

Deep graph learning

DIR:

Deep integration representation

DJR:

Deep joint reconstruction

DMNF:

Deep multiple network fusion

DRL:

Deep reinforcement learning

FDPL:

Friendship using deep pairwise learning

GAN:

Generative adversarial network

GNN:

Graph neural network

HPPNP:

Hybrid personalized propagation of neural prediction

KG:

Knowledge graphs

LBSN:

Location-based social network

LDA:

Latent Dirichlet allocation

LNN:

Ladder neural network

LSA:

Latent semantic analysis

LSTM:

Long short-term memory

MGGE:

Multi-granularity graph embedding

MLP:

Multilayer perceptrons

MOOC:

Massive open online course

MVDN:

Multi-view deep network

NLP:

Natural language processing

ORBM:

Ontology-based restricted Boltzmann machine

OSN:

Online social network

RNN:

Recurrent neural network

SCS:

Social curation service

SIDL:

Social influence deep learning

SNA:

Social network analysis

SOM:

Self-organizing map

SVM:

Support vector machine

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  1. Department of Computer Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, India

    Ash Mohammad Abbas

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Abbas, A.M. Social network analysis using deep learning: applications and schemes. Soc. Netw. Anal. Min. 11, 106 (2021). https://doi.org/10.1007/s13278-021-00799-z

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