A Survey on Reliable Source Discovery in Social Media for Big Data

Abstract

The increasing growth and usage of online social network has set a spark to the big data era. Massive amount of data from various online social media sources are being generated by the humans now-a-days. Human act as social sensors through their observations and claims. The crucial task is to identify the reliability of these observations made, which is referred as truth discovery in the presences of noisy data.  As the reliability of information must be identified where the observation made by the sensor may be true or false leading to binary claims. The truth discovery problem is to infer the correctness in the claimed observations. This problem is addressed by finding the reliability of the source. This survey concentrates on the existing truth discovery solutions available for social media sensing applications that are used to identify true information from among the conflicting data and an appropriate method can be chosen grounded on the comparison of methods and type of data.