Abstract
Post-millennium has seen advent of use of social media in people with sharing articles and interaction. Social media has become an important source of information like news for people. Researchers have identified fake news as serious issue which needs to be worked. In this paper, we have reviewed many papers based on studying the techniques employed by authors for fake news detection. We presented tabular format which consists of method, datasets used, and future scope of all reviewed papers. Approaches and challenges are identified from literature survey which are also presented.
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References
Ghani NA, Hamid S, Hashem IAT, Ahmed E (2019) Social media big data analytics: a survey. Comput Hum Behav 101:417–428
Zhou X, Zafarani R (2018) Fake news: survey of research, detection methods, and opportunities. ar**v preprint ar**v:1812.00315
Chen Y, Conroy NJ, Rubin VL (2015) Misleading online content: recognizing clickbait as false news. In: Proceedings of the 2015 ACM on workshop on multimodal deception detection. ACM, pp 15–19
Wei W, Wan X (2017) Learning to identify ambiguous and misleading news headlines. ar**v preprint ar**v:1705.06031
Rubin V, Conroy N, Chen Y, Cornwell S (2016) Fake news or truth? Using satirical cues to detect potentially misleading news. In: Proceedings of the second workshop on computational approaches to deception detection, pp 7–17
Thota A, Tilak S, Lohia N (2018) Fake news detection: a deep learning approach. SMU Data Sci Rev 1(3):10
Agrawal V, ParveenSultana H, Malhotra S, Sarkar A (2019) Analysis of classification for fake news detection. In: International conference on recent trend in advanced computing 2019
Nakamura K, Levy S, Wang WY (2020) r/Fakeddit: A new multimodal benchmark dataset for fine-grained fake news detection. In: 12th conference on language and evaluation LRCE 2020
Nasir JA, Khan OS, Varlamis I (2021) Fake news detection: a hybrid CNN-RNN based deep learning approach. Int J Inf Manage Data Insight
Aslam N, Khan IU, Alotaibi FS, Aldaei LA, Aldubaikil AK (2021) Fake detect: a deep learning ensemble model for fake news detection. Hindwai Complex 2021:5557784
Kaliyar RK, Goswami A, Narang P (2020) DeepFakE: improving fake news detection using tensor decomposition- based deep neural network. J Supercomput
Aldwairi M, Alwahedi A (2018) Detecting fake news in social media network. In: The 9th international conference on emerging ubiquitous system and pervasive networks (EUSPN 2018)
Kaur S, Kumar P, Kumarguru P (2019) “Automating fake news detection system using multi-level voting model” soft computing, part of Springer Nature
Kaliyar RK, Gowami A, Narang P, Sinha S (2020) FNDNET—a deep Convolution neural network for fake news detection. ScienceDirect, Elsevier
Faustini PHA, Covoes TF (2020) Fake news detection in multiple platform and languages. Exprt Syst Appl
Ahmad I, Yousaf M, Yousaf S, Ahmad MO (2020) Fake news detection using machine learning ensembling methods. Hindwai Complex 2020:8885861
Kaliyar RK (2018) Fake news detection using a deep learning neural network. In: 4th international conference on computing and automation (ICCCA)
Kula S, Choraś M, Kozik R, Ksieniewicz P, Woźniak M (2020) Sentiment analysis for fake news detection by means of neural networks. ICCS 2020, LNCS 12140, pp 653–666
Sabeeh V, Zohdy M, Mollah A, Al Bashaireh R (2020) Fake news detection on social media using deep learning and semantic knowledge sources. IJCSIS 18(2)
Amine BM, Drif A (2019) Merging deep learning model for fake news detection. In: International conference on advanced electrical engineering (ICAEE)
Rodríguez ÁI, Rodríguez ÁI (2019) Fake news detection using deep learning. Comput Soc
Tanvir AA, Mahir EM, Akhterand A, Akhter S (2019) Detecting fake news using machine learning and deep learning algorithms. In: 7th ICSCC
Kumar S, Asthana R, Upadhyay S, Upreti N, Akbar M (2019) Fake news detection using deep learning models: a novel approach. Trans Emerging Tel Tech, Wiley
Kaliyar RK, Kumar P, Kumar M, Narkhede M, Namboodiri S, Mishra S. DeepNet: an efficient neural network for fake news detection using news-user engagements. IEEE Xplore
Kaliyar RK, Goswami A, Narang P (2021) FakeBERT: Fake news detection in social media with a BERT-based deep learning approach. Multimedia Tools Appl 80:11765–11788
Kaliyar RK, Fitwe K, Rajarajeswari P, Goswami A (2021) Classification of hoax/non-hoax news articles on social media using an effective deep neural network. ICCMC
Jiang T, Li JP, Haq AU, Saboor A (2020) Fake news detection using deep recurrent neural networks. In: 17th ICCWAMTIP 2020
Kim K, Jeong C. Fake news detection system using article abstraction. IEEE Xplore
Singh L (2020) Fake news detection: a comparison between available deep learning techniques in vector space. IEEE
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Rathod, N.A., Ramteke, P.L. (2024). Challenges and Future Scope in Fake News Detection: A Survey. In: Dhote, N.K., Kolhe, M.L., Rehman, M. (eds) Recent Evolutions in Energy, Drives and e-Vehicles. REEDEV 2022. Lecture Notes in Electrical Engineering, vol 1162. Springer, Singapore. https://doi.org/10.1007/978-981-97-0763-8_14
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DOI: https://doi.org/10.1007/978-981-97-0763-8_14
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