• Dhanave Pallavi
• Tulsa Chavan
• Mira Bhavar
• Aruna Salunke

The sources of data from online social media may be consist of some data which are noisy and sparse. While handling of big data related social sensing media application their challenges like misinformation spread are data sparsity and fake news. The system is going to use of advanced algorithms to discover the dynamic truth information and frequently used information. The addressing misinformation spread in big data (e.g. whatsaap, twitter, instagram) is difficult task in the present days. There will be one more challenge is data sparsing, where majority of sources contributes only small number of claims. The existing solution are not enough for large scale social sensing events, since existing algorithms have centralized in nature. We are going to use of the SRTD scheme for identifying both source realibility as well as crediability of the claims. In the honeypots system we can For implementation of the system we use the social honeypot system to find out the spammers and legitimates which can upload the tweets on social media. By using the honeypot system we analyze the different tweets which are true or false. In truth discovery significant amount of attentions has recieved in recent years and we will be developing various models to address truth information.

Big Data, Truth Discovery, Scalable, Data Sparsity, Realibility.

"Addressing misinformation spread and uncovering spammersusing social honeypot in truth discovery on social media. ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.521-527, May-2019, Available :http://www.jetir.org/papers/JETIR1905O82.pdf

"Addressing misinformation spread and uncovering spammersusing social honeypot in truth discovery on social media. ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp521-527, May-2019, Available at : http://www.jetir.org/papers/JETIR1905O82.pdf