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@article{168492,
        author = {K. Nagananthini and Gomathi Annadurai and G. S. Geethamani},
        title = {A Survey on Spam Detection System for Social Network with Remote Monitoring with Big Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {1186-1190},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168492},
        abstract = {Social media systems heavily depend on users for content contribution and sharing. Information is spread across social networks quickly and effectively. However, at the same time social media networks become susceptible to different types of unwanted and malicious spammer or hacker actions. In this work, we present a social network spam detection application based on texts. Particularly, we tested on the Facebook spam. We develop an application to test the prototype of Facebook spam detection. The features for checking spams are the number of keywords, the average number of words, the text length, the number of links. The methodology can be extended to include other attributes. The prototype application demonstrates the real use of the Facebook application. There is a crucial need in the society and industry for security solution in social media. In this demo, we propose a scalable and online social media spam detection system for social network security},
        keywords = {},
        month = {October},
        }