Acceso abierto

Fake online review recognition algorithm and optimisation research based on deep learning

Jiani Hou
Jiani Hou
 y 
Aimin Zhu
Aimin Zhu
   | 31 mar 2022
Applied Mathematics and Nonlinear Sciences's Cover Image
Acerca de este artículo
Artículo anterior
Artículo siguiente
Cite
Publicado en línea: 31 mar 2022
Páginas: 861 - 874
Recibido: 20 jul 2021
Aceptado: 06 dic 2021
DOI: https://doi.org/10.2478/amns.2021.2.00170
Palabras clave
© 2021 Jiani Hou et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

The flow chart of data preprocessing in Chinese
The flow chart of data preprocessing in Chinese

Fig. 2

Hybrid neural network model
Hybrid neural network model

Fig. 3

The Relu activation function
The Relu activation function

Fig. 4

Indicator diagram
Indicator diagram

The results of the deep learning model after the improved training words

The evaluation index The type of model
CNN LSTM BILSTM-e BILSTM-av Hybrid-e Hybrid-av Hybrid-at F-Hybird-av
precision_fake 0.891 0.887 0.892 0.864 0.905 0.902 0.895 0.902
recall_fake 0.905 0.907 0.909 0.850 0.923 0.920 0.912 0.921
identify_fake 0.898 0.897 0.900 0.857 0.914 0.911 0.903 0.898
precision_true 0.902 0.905 0.908 0.853 0.921 0.919 0.919 0.923
recall_true 0.892 0.892 0.894 0.862 0.902 0.903 0.899 0.905
identify_true 0.897 0.898 0.901 0.857 0.911 0.911 0.909 0.897
precision 0.899 0.898 0.901 0.859 0.912 0.913 0.908 0.915

Data set information

The total number of samples The number of positive samples The number of negative samples
The original data set 38,874 21,213 17,661
The data set after de-duplication 36,674 20,038 16,636
Sampled data set 40,076 20,038 20,038

Deep learning model results

The evaluation index The type of model
CNN LSTM BILSTM-e BILSTM-av Hybrid-e Hybrid-av Hybrid-at F-Hybird-av
precision_fake 0.882 0.878 0.880 0.798 0.892 0.893 0.887 0.894
recall_fake 0.901 0.894 0.902 0.832 0.912 0.912 0.909 0.911
identify_fake 0.891 0.886 0.891 0.815 0.902 0.902 0.898 0.902
precision_true 0.897 0.892 0.899 0.829 0.915 0.916 0.914 0.917
recall_true 0.879 0.881 0.878 0.802 0.897 0.899 0.891 0.903
identify_true 0.888 0.887 0.888 0.815 0.906 0.907 0.902 0.910
precision 0.893 0.890 0.892 0.824 0.902 0.905 0.898 0.906

User behaviour characteristics

Reviewer buying behaviour characteristics The characteristics of buying behaviour of fake shopping reviewers
The correlation between the search term and the product The correlation between keywords and final products is low
Time to complete the shopping activity Lower browsing time
The similar items by browsing other shop Browse less of the same kind of goods
Browsing number of other items purchased in the store Browsing number of other items purchased in the store is less
The act of collecting goods and paying attention to stores They don’t collect and pay attention
eISSN:
2444-8656
Idioma:
Inglés
Calendario de la edición:
Volume Open
Temas de la revista:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics
RSS Feed de revista