Systematic Approach for Detection and Prevention of False Information on Social Media Platform

Authors

  • Satinder Pal Research Scholar (CSE), Geeta University, Panipat, Haryana, India
  • Anil Kumar Lamba Professor (CSE), Geeta University, Panipat, Haryana, India

Keywords:

False information, multi-media, platform, research, social media, spam

Abstract

The rise of social media has transformed the dissemination of real-time information, making it imperative to address the issues surrounding fake news on platforms like Twitter, Instagram, Facebook, and WhatsApp. This paper provides a comprehensive overview of the current state of fake news detection, encompassing traditional machine learning techniques and recent advances in deep learning. By exploring state-of-the-art models and evaluating their effectiveness, it offers valuable insights into the evolving landscape of fake news detection. The inclusion of real-world data from an online survey and visual aids enhances the paper's relevance and accessibility, making it a timely and significant contribution to combating misinformation in today's digital age.

Downloads

Download data is not yet available.

References

Di Domenico, Giandomenico, Jason Sit, Alessio Ishizaka, and Daniel Nunan. "Fake news, social media and marketing: A systematic review." Journal of Business Research 124 (2021): 329-341.

Pierri, Francesco, and Stefano Ceri. "False news on social media: a data-driven survey." ACM Sigmod Record 48, no. 2 (2019): 1827.

Hamdi Tarek, Hamda Slimi, Ibrahim Bounhas, and Yahya Slimani. "A hybrid approach for fake news detection in twitter based on user features and graph embedding." In International conference on distributed computing and internet technology, pp. 266-280. Springer, Cham, 2020.

Preston, Stephanie, Anthony Anderson, David J. Robertson, Mark P. Shephard, and Narisong Huhe. "Detecting fake news on Facebook: The role of emotional intelligence." Plos one 16, no. 3 (2021): e0246757.

Herrero-Diz Paula, JesúsConde-Jiménez, and Salvador Reyes-de Cózar. "Teens’ motivations to spread fake news on WhatsApp." Social Media+ Society 6, no. 3 (2020): 2056305120942879.

Monti Federico, Fabrizio Frasca, Davide Eynard, "Fake news detection on social media using geometric deep learning." arXiv preprint arXiv:1902.06673 (2019).

Stahl, Kelly. "Fake news detection in social media." California State University Stanislaus 6 (2018): 4-15.

Okoro, E. M., B. A. Abara, A. O. Umagba, A. A. Ajonye, and Z. S. Isa. "A hybrid approach to fake news detection on social media." Nigerian Journal of Technology 37, no. 2 (2018): 454-462.

Elhadad Mohamed K., Kin Fun Li, and Fayez Gebali. "Fake news detection on social media: a systematic survey." In 2019 IEEE Pacific Rim conference on communications, computers and signal processing (PACRIM), pp. 1-8. IEEE, 2019.

Akinyemi Bodunde, Oluwakemi Adewusi, and Adedoyin Oyebade. "An improved classification model for fake news detection in social media." international journal of Information Technology and Computer Science (IJITCS) 12, no. 1 (2020): 34-43.

Patil Pradnya, and Sanjeev J. Wagh. "Data‐Driven Approches for Fake News Detection on Social Media Platforms." Object Detection by Stereo Vision Images (2022): 195-206.

Xue, Junxiao, Yabo Wang, YichenTian, Yafei Li, Lei Shi, and Lin Wei. "Detecting fake news by exploring the consistency of multimodal data." Information Processing & Management 58, no. 5 (2021): 102610.

Zhang, Xichen, and Ali A. Ghorbani. "An overview of online fake news: Characterization, detection, and discussion." Information Processing & Management 57, no. 2 (2020): 102025.

Dabbous, Amal, KarineAounBarakat, and Beatriz de Quero Navarro. "Fake news detection and social media trust: a cross-cultural perspective." Behaviour & Information Technology (2021): 1-20.

Szczepański, Mateusz, MarekPawlicki, RafałKozik, and MichałChoraś. "New explainability method for BERT-based model in fake news detection." Scientific Reports 11, no. 1 (2021): 1-13.

Liao Shu-Hsien, RetnoWidowati, and Yu-Chieh Hsieh. "Investigating online social media users’ behaviors for social commerce recommendations." Technology in Society 66 (2021): 101655.

Shu Kai, Ahmadreza Mosallanezhad, and Huan Liu. "Cross-Domain false information detection on Social Media: A Context-Aware Adversarial Approach." In Frontiers in Fake Media Generation and Detection, pp. 215-232. Springer, Singapore, 2022.

Kalin Igor, Milan Mirković, and Aleksandra Kolak. "Fake News Detection on Social Networks–a Brief Overview of Methods and Approaches." Industrial Innovation in Digital Age (2022): 510-517.

Raza Shaina, and Chen Ding. "Fake news detection based on news content and social contexts: a transformer-based approach." International Journal of Data Science and Analytics 13, no. 4 (2022): 335-362.

Natarajan, Rathika, Abolfazl Mehbodniya, Kantilal Pitambar Rane, Sonika Jindal, Mohammed FaezHasan, Luis Vives, and Abhishek Bhatt. "Intelligent gravitational search random forest algorithm for fake news detection." International Journal of Modern Physics C 33, no. 06 (2022): 2250084.

Senhadji Sarra, and Rania Azad San Ahmed. "Fake news detection using naïve Bayes and long short term memory algorithms." Int J ArtifIntell ISSN 2252, no. 8938: 8938.

Yang, Yang, Lei Zheng, Jiawei Zhang, Qingcai Cui, Zhoujun Li, and Philip S. Yu. "TI-CNN: Convolutional neural networks for fake news detection." arXiv preprint arXiv:1806.00749 (2018).

Dixit, Dheeraj Kumar, Amit Bhagat, and Dharmendra Dangi."Automating fake news detection using PPCA and levy flightbased LSTM." Soft Computing 26, no. 22 (2022): 12545-12557.

Tembhurne, Jitendra Vikram, Md Moin Almin, and TausifDiwan. "Mc-DNN: Fake News Detection Using Multi-Channel Deep Neural Networks." International Journal on Semantic Web and Information Systems (IJSWIS) 18, no. 1 (2022): 1-20.

Li, Dun, HaimeiGuo, Zhenfei Wang, and ZhiyunZheng. "Unsupervised fake news detection based on autoencoder." IEEE Access 9 (2021): 29356-29365.

Sahin, Muammer Eren, Chunyang Tang, and Mohammad Al-Ramahi. "Fake News Detection on Social Media: A Word EmbeddingBased Approach." (2022).

Sciucca, Laura Della, Marco Mameli, Emanuele B alloni, Luca Rossi, Emanuele Frontoni, Primo Zingaretti, and Marina Paolanti. "FakeNED: A Deep Learning Based-System for Fake News Detection from Social Media." In International Conference on Image Analysis and Processing, pp. 303-313. Springer, Cham, 2022.

Aslam, Nida, IrfanUllah Khan, Farah Salem Alotaibi, Lama AbdulazizAldaej, and Asma Khaled Aldubaikil. "Fake detect: A deep learning ensemble model for fake news detection." complexity 2021 (2021).

Jain Vidit, Rohit Kumar Kaliyar, AnuragGoswami, Pratik Narang, and Yashvardhan Sharma. "AENeT: an attention-enabled neural architecture for fake news detection using contextual features." Neural Computing and Applications 34, no. 1 (2022): 771-782.

Palani, Balasubramanian, SivasankarElango, and VigneshViswanathan K. "CB-Fake: A multimodal deep learning framework for automatic fake news detection using capsule neural network and BERT." Multimedia Tools and Applications 81, no. 4 (2022): 5587-5620.

Ni, Shiwen, Jiawen Li, and Hung-Yu Kao. "MVAN: Multi-View Attention Networks for Fake News Detection on Social Media." IEEE Access 9 (2021): 106907-106917.

Sastrawan, I. Kadek, I. P. A. Bayupati, and Dewa Made Sri Arsa. "Detection of fake news using deep learning CNN–RNN based methods." ICT Express 8, no. 3 (2022): 396-408.

Ali, Abdullah Marish, Fuad A. Ghaleb, Bander Ali Saleh Al-Rimy, FawazJaber Alsolami, and Asif Irshad Khan. "Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique." Sensors 22, no. 18 (2022): 6970.

Kaliyar, Rohit Kumar, Anurag Goswami, and Pratik Narang. "EchoFakeD: improving fake news detection in social media with an efficient deep neural network." Neural computing and applications 33, no. 14 (2021): 8597-8613.

Kaliyar, Rohit Kumar, Anurag Goswami, and Pratik Narang. "FakeBERT: Fake news detection in social media with a BERT-based deep learning approach."

Downloads

Published

27.12.2023

How to Cite

Pal, S. ., & Lamba, A. K. . (2023). Systematic Approach for Detection and Prevention of False Information on Social Media Platform. International Journal of Intelligent Systems and Applications in Engineering, 12(9s), 291–300. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4276

Issue

Vol. 12 No. 9s (2024)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.