منابع
انصاری، وحید؛ مومنزاده، حسین و ارفعینیا، حسن؛ (1403). تشخیص اخبار جعلی با استفاده از شبکه عصبی عمیق CNN،
هفتمین کنفرانس بین المللی مهندسی برق، کامپیوتر، مکانیک و هوش مصنوعی،
https://civilica.com/doc/2046572
ایزی، جلال و حسن پور، حسام؛ (1402). تشخیص و طبقه بندی اخبار جعلی به کمک پردازش زبان طبیعی و یادگیری عمیق، ششمین کنفرانس ملی فناوری های نوین در مهندسی برق و کامپیوتر،https://civilica.com/doc/1876620
ایزی، جلال و رضایی، پوریا؛ (1402). بهبود تشخیص در طبقه بندی اخبار جعلی در رسانه های اجتماعی با استفاده از الگوریتم کا - نزدیکترین همسایه، نهمین کنفرانس بین المللی تحقیقات بین رشته ای در مهندسی برق، کامپیوتر، مکانیک و مکاترونیک در ایران و جهان اسلام،https://civilica.com/doc/1994927
شفیعی وشاره، زهرا؛ علی عسگری رنانی، فاطمه و محمدی، شهرام؛ (1403). تشخیص اخبار جعلی به کمک الگوریتم های هوش مصنوعی،
هشتمین کنفرانس ملی پژوهشهای کاربردی در مهندسی برق، مکانیک و مکاترونیک، https://civilica.com/doc/2024063
فرضی، سعید؛ (1400). استفاده از شبکه مولد متخاصم شرطی برای تولید داده با هدف بهبود کلاس بندی کاربران منتشرکننده اخبار جعلی،
دوفصلنامه فناوری اطلاعات و ارتباطات ایران، دوره: 13، شماره: 47 .https://civilica.com/doc/1858925
وظیفه آبان، هادی و حسنی آهنگر، محمدرضا؛ (1402). استفاده از تکنیک رایگیری اکثریت در طبقهبندی اخبار جعلی از واقعی با الگوریتمهای درخت تصمیم، رگرسیون لجستیک و کا-نزدیکترین همسایگی،
ششمین همایش ملی فناوریهای نوین در مهندسی برق، کامپیوتر و مکانیک ایران،
https://civilica.com/doc/1744364
References
Afroz, S., Brennan, M., & Greenstadt, R. (2012). Detecting hoaxes, frauds, and deception in writing style online. 2012
IEEE Symposium on security and Privacy. DOI:
10.1109/SP.2012.34
Ahmed, H. (2017). Detecting opinion spam and fake news using n-gram analysis and semantic similarity
Ansari, V., Moomenzadeh, H., & Arfaeinia, H. (1403). Fake News Detection Using Deep Neural Network CNN, 7th International Conference on Electrical Engineering, Computer Science, Mechanics, and Artificial Intelligence, (in Persian) https://civilica.com/doc/2046572.
Banerjee, R., Feng, S., Kang, J. S., & Choi, Y. (2014). Keystroke patterns as prosody in digital writings: A case study with deceptive reviews and essays. Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP(
Bigne, E., Andreu, L., Hernandez, B., & Ruiz, C. (2018). The impact of social media and offline influences on consumer behavior. An analysis of the low-cost airline industry. Current Issues in Tourism, 21(9), 1014-1032. https://doi.org/10.1080/13683500.2015.1126236
Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on Twitter. Proceedings of the 20th International Conference on World Wide Web.https://doi.org/10.1145/1963405.1963500
Chu, Z., Gianvecchio, S., Wang, H., & Jajodia, S. (2012). Detecting automation of Twitter accounts: Are you a human, bot, or cyborg?
IEEE Transactions on dependable and secure computing,
9(6), 811-824. DOI:
10.1109/TDSC.2012.75
Di, R., Wang, H., Fang, Y., & Zhou, Y. (2018). Fake comment detection based on time series and density peaks clustering. Algorithms and Architectures for Parallel Processing: ICA3PP 2018 International Workshops, Guangzhou, China, November 15-17, 2018, Proceedings 18
Farajtabar, M., Yang, J., Ye, X., Xu, H., Trivedi, R., Khalil, E., Li, S., Song, L., & Zha, H. (2017). Fake news mitigation via point process based intervention. International conference on machine learning
Farokhian, M., Rafe, V., & Veisi, H. (2022). Fake news detection using parallel BERT deep neural networks. arXiv preprint arXiv:2204.04793.
Farzi, S. (2021). Utilizing Conditional Generative Adversarial Networks for Data Generation to Improve the Classification of Users Spreading Fake News, Iranian Journal of Information and Communication Technology, Volume: 13, Issue: 47. (in Persian). https://civilica.com/doc/1858925
Horne, B., & Adali, S. (2017). This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. Proceedings of the international AAAI conference on web and social media . https://doi.org/10.1609/icwsm.v11i1.14976
Izi, J., & Hassanpour, H. (2023). Detection and Classification of Fake News Using Natural Language Processing and Deep Learning, Sixth National Conference on New Technologies in Electrical Engineering and Computer (in Persian) Science, https://civilica.com/doc/1876620.
Izi, J., Rezaei, P. (1402). Improving Detection in Fake News Classification on Social Media Using K-Nearest Neighbors Algorithm,
9th International Conference on Interdisciplinary Research in Electrical Engineering, Computer Science, Mechanics, and Mechatronics in Iran and the Islamic World, (in Persian),
https://civilica.com/doc/1994927.
Kaliyar, R. K., Goswami, A., & Narang, P. (2021). FakeBERT: Fake news detection in social media with a BERT-based deep learning approach. Multimedia Tools and Applications, 80(8), 11765-11788.
Kuntur, S., Wróblewska, A., Paprzycki, M., & Ganzha, M. (2024). Fake News Detection: It's All in the Data! arXiv preprint arXiv:2407.02122.
Mukherjee, A., Liu, B., & Glance, N. (2012). Spotting fake reviewer groups in consumer reviews. Proceedings of the 21st International Conference on World Wide Web.https://doi.org/10.1145/2187836.2187863
Oshikawa, R., Qian, J., & Wang, W. Y. (2018). A survey on natural language processing for fake news detection. arXiv preprint arXiv:1811.00770.
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003). Psychological aspects of natural language use: Our words, our selves. Annual review of psychology, 54(1), 547-577. https://doi.org/10.1146/annurev.psych.54.101601.145041
Russell, M. A. (2013). Mining the social web: data mining Facebook, Twitter, LinkedIn, Google+, GitHub, and more. " O'Reilly Media, Inc.".
Shafiei-Shara, Z., Ali-Asgari-Renani, F., & Mohammadi, S. (1403). Fake News Detection Using Artificial Intelligence Algorithms.
8th National Conference on Applied Research in Electrical Engineering, Mechanics, and Mechatronics, Tehran, (in Persian)
https://civilica.com/doc/2024063.
Shao, C., Ciampaglia, G. L., Flammini, A., & Menczer, F. (2016). Hoaxy: A platform for tracking online misinformation. Proceedings of the 25th International Conference Companion on World Wide Web. https://doi.org/10.1145/2872518.2890098
Shu, K., Bernard, H. R., & Liu, H. (2019). Studying fake news via network analysis: detection and mitigation. Emerging research challenges and opportunities in computational social network analysis and mining, 43-65.
Shushkevich, E., Alexandrov, M., & Cardiff, J. (2023). Improving multiclass classification of fake news using Bert-based models and CHATGPT-augmented data. Inventions, 8(5), 112. https://doi.org/10.3390/inventions8050112
Su, J., Cardie, C., & Nakov, P. (2023). Adapting fake news detection to the era of large language models. arXiv preprint arXiv:2311.04917.
Tschiatschek, S., Singla, A., Gomez Rodriguez, M., Merchant, A., & Krause, A. (2017). Detecting fake news in social networks via crowdsourcing. arXiv preprint arXiv:1711.09025.
Vazifeh Aban, H., & Hasani Ahangar, M. R.; (1402). Using Majority Voting Technique in Classifying Fake News from Real News with Decision Tree, Logistic Regression, and K-Nearest Neighbors Algorithms,
6th National Conference on New Technologies in Electrical Engineering, Computer Science, and Mechanics of Iran, Tehran, (in Persian)
https://civilica.com/doc/1744364.
Vicario, M. D., Quattrociocchi, W., Scala, A., & Zollo, F. (2019). Polarization and fake news: Early warning of potential misinformation targets. ACM Transactions on the Web (TWEB), 13(2), 1-22. https://doi.org/10.1145/3316809
Vyas, P., Liu, J., & Xu, S. (2024). Real-Time Fake News Detection on the X (Twitter): An Online Machine Learning Approach.
Wang, Y., & Li, B. (2015). Sentiment analysis for social media images. 2015
IEEE International Conference on Data Mining Workshop (ICDMW). DOI:
10.1109/ICDMW.2015.142
Yang, F., Liu, Y., Yu, X., & Yang, M. (2012). Automatic detection of rumor on sina weibo. Proceedings of the ACM SIGKDD workshop on mining data semantics. https://doi.org/10.1145/2350190.2350203
Zhang, X., & Ghorbani, A. A. (2020). An overview of online fake news: Characterization, detection, and discussion. Information Processing & Management, 57(2), 102025.
Zhao, Z., Resnick, P., & Mei, Q. (2015). Enquiring minds: Early detection of rumors in social media from enquiry posts. Proceedings of the 24th International Conference on world wide web.
Zhou, X., & Zafarani, R. (2020). A survey of fake news: Fundamental theories, detection methods, and opportunities. ACM Computing Surveys (CSUR), 53(5), 1-40. https://doi.org/10.1145/3395046
Zhu, Y., Li, Y., Wang, J., Gao, M., & Wei, J. (2024). FaKnow: A Unified Library for Fake News Detection. arXiv preprint arXiv:2401.16441.
