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

Now a days 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 on 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 current era. There will be one more challenge is data sparsing, where majority of sources contributes only small number of claims. The existing solutions 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. For implementing the proposed system of truth discovery HTcondor system we are going to involved .To solve the truth discovery problem there are principles in data mining and network sensing communities. The above important challenges will be well addressing by the truth discovery solution in social media sensing application. 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

"Reviw on Addressing misinformation spread and data sparsity in truth discovery on social media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.358-361, November 2018, Available :http://www.jetir.org/papers/JETIR1811952.pdf

"Reviw on Addressing misinformation spread and data sparsity 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.5, Issue 11, page no. pp358-361, November 2018, Available at : http://www.jetir.org/papers/JETIR1811952.pdf