Effective preprocessing and feature analysis on Twitter data for Fake news detection using RWS algorithm

Authors

DOI:

https://doi.org/10.4108/eetsis.5157

Keywords:

Machine Learning, Fake news detection, Data analytics, Data science, Feature analysis

Abstract

The tremendous headway of web empowered gadgets develops the clients dependably strong in virtual redirection affiliations. Individuals from social affairs getting moment notices with respect to news, amusement, training, business, and different themes.  The development of artificial intelligence-based classification models plays an optimum role in making deeper analysis of text data. The massive growth of text-based communication impacts the social decisions also. People rely on news and updates coming over in social media and networking groups. Micro blogs such as tweeter, facebooks manipulate the news as faster as possible.

The quality of classification of fake news and real news depends on the processing steps. The proposed articles focused on deriving a significant method for pre-processing the dataset and feature extraction of the unique data. Dataset is considered as the input data for analyzing the presence of fake news. The extraction of unique features from the data is implemented using Bags of relevant tags (BORT) extraction and Bags of relevant meta words (BORMW).

References

De Oliveira, N, R, Medeiros D, S, V, and Mattos, D, M, F.: A Sensitive Stylistic Approach to Identify Fake News on Social Networking, IEEE Signal Processing Letters. 2020; 27:1250-1254.

Park, M, Chai, S.: Constructing a User-Centered Fake News Detection Model by Using Classification Algorithms in Machine Learning Techniques, IEEE Access. 2023; 11: 71517-71527.

Radhika S, Prasanth A, An Effective Speech Emotion Recognition Model for Multi-Regional Languages Using Threshold-based Feature Selection Algorithm. Circuits, Systems, and Signal Processing. 2023; 1-22.

Boualouache, A and Engel, T.: A Survey on Machine Learning-Based Misbehavior Detection Systems for 5G and Beyond Vehicular Networks, IEEE Communications Surveys & Tutorials. 2023; 25:1128-1172.

Albalawi, R, M, Jamal, A, T, Khadidos, A, O and Alhothali, A, M.: Multimodal Arabic Rumors Detection, IEEE Access. 2023; 11:9716-9730.

Elhadad, M, K, Li, K, F and Gebali, F.: "Detecting Misleading Information on COVID-19," in IEEE Access. 2020; 8:165201-165215.

Wei, P, Wu, F, Sun, Y, Zhou, H and Jing, X, Y.: Modality and Event Adversarial Networks for Multi-Modal Fake News Detection, IEEE Signal Processing Letters. 2022; 29: 1382-1386.

Rong, X, Yi, C and Tian, Y.: Unambiguous Text Localization, Retrieval, and Recognition for Cluttered Scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022; 44(3):1638-1652.

Yang, C, Chen, M, Xiong, Z, Yuan, Y and Wang, Q.: CM-Net: Concentric Mask Based Arbitrary-Shaped Text Detection, IEEE Transactions on Image Processing. 2022; 31:2864-2877.

Abonizio, H, Q, Paraiso, E, C and S. Barbon, S.: Toward Text Data Augmentation for Sentiment Analysis, in IEEE Transactions on Artificial Intelligence. Oct 2022; 3(5): 657-668.

Li, R, Liu, Z, Ma, Y, Yang, D and Sun, S.: Internet Financial Fraud Detection Based on Graph Learning, in IEEE Transactions on Computational Social Systems. June 2023; 3:1394-1401.

Alsuwaiket, M, A.: Feature Extraction of EEG Signals for Seizure Detection Using Machine Learning Algorthims, Engineering, Technology & Applied Science Research. Oct 2022; 12(5):9247–9251.

Jayachitra, S, Prasanth, A, Rafi, A Hierarchical-Based Binary Moth Flame Optimization for Feature Extraction in Biomedical Application. Proceedings in 4th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences. 2023; 27-38.

Anwer, M, Khan, S, M, Farooq, M, U and Waseemullah.: Attack Detection in IoT using Machine Learning, Engineering, Technology & Applied Science Research, Jun. 2021; 11(3):7273–7278.

Aramaki, Y, Matsui, Y, Yamasaki, T and Aizawa, K.: Text detection in manga by combining connected-component-based and region-based classifications, IEEE International Conference on Image Processing. 2016; 2901-2905.

Mol, J, Mohammed, A and Mahesh, B, S.: Text recognition using poisson filtering and edge enhanced maximally stable extremal regions, International Conference on Intelligent Computing, Instrumentation and Control Technologies. 2017; 302-306.

Satwashil, K, S and Pawar, V, R.: English text localization and recognition from natural scene image, 2017 International Conference on Intelligent Computing and Control Systems. 2017; 555-559.

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Published

20-02-2024

How to Cite

1.
Santhoshkumar M, Divya V. Effective preprocessing and feature analysis on Twitter data for Fake news detection using RWS algorithm. EAI Endorsed Scal Inf Syst [Internet]. 2024 Feb. 20 [cited 2024 Apr. 20];. Available from: https://publications.eai.eu/index.php/sis/article/view/5157

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Section

Short communications